https://wiki.luntti.net/api.php?action=feedcontributions&feedformat=atom&user=Molwikiluntti - User contributions [en]2026-07-16T01:54:26ZUser contributionsMediaWiki 1.40.0https://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16595CFD OpenFoam Sauna2026-07-14T19:28:05Z<p>Mol: /* Installation and using */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation and using ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
<syntaxhighlight lang="bash"><br />
source /opt/OpenFOAM/OpenFOAM-13/etc/bashrc<br />
</syntaxhighlight><br />
<br />
Create an OpenFOAM case directory<br />
<syntaxhighlight lang="bash"><br />
mkdir -p ~/Documents/ofoam/constant/polyMesh<br />
mkdir -p ~/Documents/ofoam/system<br />
mkdir -p ~/Documents/ofoam/0<br />
</syntaxhighlight><br />
Put your Gmsh mesh there:<br />
<syntaxhighlight lang="bash"><br />
cp thermal_test.msh ~/Documents/ofoam/<br />
cd ~/Documents/ofoam<br />
</syntaxhighlight><br />
Copy the tutorials to start easier <br />
<syntaxhighlight lang="bash"><br />
cp -r $FOAM_TUTORIALS/heatTransfer/chtMultiRegionFoam/* ~/Documents/ofoam/<br />
</syntaxhighlight><br />
<br />
Then convert:<br />
<syntaxhighlight lang="bash"><br />
gmshToFoam thermal_test.msh<br />
</syntaxhighlight><br />
This will populate:<br />
<syntaxhighlight lang="bash"><br />
constant/polyMesh/<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
gmshToFoam model.msh<br />
</syntaxhighlight><br />
generates 3d triangulation and converts it. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16594CFD OpenFoam Sauna2026-07-14T19:22:44Z<p>Mol: /* Installation and using */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation and using ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
<syntaxhighlight lang="bash"><br />
source /opt/OpenFOAM/OpenFOAM-13/etc/bashrc<br />
</syntaxhighlight><br />
<br />
Create an OpenFOAM case directory<br />
<syntaxhighlight lang="bash"><br />
mkdir -p ~/Documents/ofoam/constant/polyMesh<br />
mkdir -p ~/Documents/ofoam/system<br />
mkdir -p ~/Documents/ofoam/0<br />
</syntaxhighlight><br />
Put your Gmsh mesh there:<br />
<syntaxhighlight lang="bash"><br />
cp thermal_test.msh ~/Documents/ofoam/<br />
cd ~/Documents/ofoam<br />
</syntaxhighlight><br />
Then convert:<br />
<syntaxhighlight lang="bash"><br />
gmshToFoam thermal_test.msh<br />
</syntaxhighlight><br />
This will populate:<br />
<syntaxhighlight lang="bash"><br />
constant/polyMesh/<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
gmshToFoam model.msh<br />
</syntaxhighlight><br />
generates 3d triangulation and converts it. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16593CFD OpenFoam Sauna2026-07-14T19:22:08Z<p>Mol: /* Installation */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation and using ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
<syntaxhighlight lang="bash"><br />
source /opt/OpenFOAM/OpenFOAM-13/etc/bashrc<br />
</syntaxhighlight><br />
<br />
Create an OpenFOAM case directory<br />
<syntaxhighlight lang="bash"><br />
mkdir -p ~/Documents/ofoam/constant/polyMesh<br />
mkdir -p ~/Documents/ofoam/system<br />
mkdir -p ~/Documents/ofoam/0<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
gmshToFoam model.msh<br />
</syntaxhighlight><br />
generates 3d triangulation and converts it. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16592CFD OpenFoam Sauna2026-07-14T19:20:07Z<p>Mol: /* Installation */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
<syntaxhighlight lang="bash"><br />
source /opt/OpenFOAM/OpenFOAM-13/etc/bashrc<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
gmshToFoam model.msh<br />
</syntaxhighlight><br />
generates 3d triangulation and converts it. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16591CFD OpenFoam Sauna2026-07-14T19:17:18Z<p>Mol: /* gmsh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
gmshToFoam model.msh<br />
</syntaxhighlight><br />
generates 3d triangulation and converts it. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16590CFD OpenFoam Sauna2026-07-14T19:16:22Z<p>Mol: /* gmsh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== Images ===<br />
<br />
<gallery><br />
Gmsh sauna mesh1.png| The mesh with three different parts. <br />
</gallery><br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
</syntaxhighlight><br />
generates 3d triangulation. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=File:Gmsh_sauna_mesh1.png&diff=16589File:Gmsh sauna mesh1.png2026-07-14T19:15:41Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16588CFD OpenFoam Sauna2026-07-14T13:12:32Z<p>Mol: /* gmsh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<br />
The command<br />
<syntaxhighlight lang="Bash"><br />
gmsh model.geo -3<br />
</syntaxhighlight><br />
generates 3d triangulation. <br />
<br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16587CFD OpenFoam Sauna2026-07-14T12:30:17Z<p>Mol: /* Workflow */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
Use <code>foamSearch <keyword></code> or <code>find $FOAM_TUTORIALS -type f | grep <keyword> </code>. For example: <code> find $FOAM_TUTORIALS -type f | grep laplacian</code> will show every diffusion example. Start with laplacianFoam → buoyantSimpleFoam → conjugate heat transfer examples.<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16586CFD OpenFoam Sauna2026-07-14T12:28:49Z<p>Mol: /* 1 */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== Workflow ===<br />
<br />
#Generate mesh<br />
#* For example: blockMesh<br />
#Run solver<br />
#* Example: laplacianFoam or: buoyantSimpleFoam<br />
# View results<br />
#*paraFoam<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16585CFD OpenFoam Sauna2026-07-14T12:26:24Z<p>Mol: /* OpenFOAM */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
=== 1 ===<br />
<br />
=== Tutorials ===<br />
<br />
ls $FOAM_TUTORIALS<br />
<br />
=== Installation ===<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16584CFD OpenFoam Sauna2026-07-14T12:24:26Z<p>Mol: /* Creating the mesh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
=== gmsh ===<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles. <br />
<syntaxhighlight lang="Bash"><br />
yay -S gmsh-bin<br />
</syntaxhighlight><br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16583CFD OpenFoam Sauna2026-07-14T12:20:30Z<p>Mol: /* OpenFOAM */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
Installation is a long process, it takes many hours using yay. <br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16582CFD OpenFoam Sauna2026-07-14T12:16:31Z<p>Mol: /* OpenFOAM */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
</syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16581CFD OpenFoam Sauna2026-07-14T12:15:58Z<p>Mol: /* OpenFOAM */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
<syntaxhighlight lang="bash"><br />
ofoam<br />
<(syntaxhighlight><br />
<br />
== Creating the mesh ==<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16580CFD OpenFoam Sauna2026-07-14T10:00:51Z<p>Mol: /* Creating the mesh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
== Creating the mesh ==<br />
<br />
[https://gmsh.info/ Gmsh] to generate the triangles<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16579CFD OpenFoam Sauna2026-07-14T09:57:22Z<p>Mol: /* Creating the mesh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
== Creating the mesh ==<br />
<br />
Gmsh to generate the triangles<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16578CFD OpenFoam Sauna2026-07-14T09:50:15Z<p>Mol: /* Creating the mesh */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
== Creating the mesh ==<br />
<br />
== Analyzing ==<br />
<br />
== Results ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16577CFD OpenFoam Sauna2026-07-14T09:49:59Z<p>Mol: /* Introduction */</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math><br />
but I'd like to include Navier-Stokes equations and perhaps energy equation: ice melts into water,<br />
water freezes, latent heat is released and the interfaces move. <br />
<br />
== OpenFOAM ==<br />
<br />
== Creating the mesh ==</div>Molhttps://wiki.luntti.net/index.php?title=CFD_OpenFoam_Sauna&diff=16576CFD OpenFoam Sauna2026-07-14T09:48:31Z<p>Mol: Created page with "==Introduction == Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. Other possibilities would be to create a simple Laplacian solver. <math> \rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T) </math>"</p>
<hr />
<div>==Introduction ==<br />
<br />
Use OpenFOAM to analyze the heating of water above sauna's oven. The problem is during the winter when the water freezes. <br />
<br />
Other possibilities would be to create a simple Laplacian solver. <br />
<math><br />
\rho c_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T)<br />
</math></div>Molhttps://wiki.luntti.net/index.php?title=Short_introduction_to_Manim&diff=16575Short introduction to Manim2026-07-13T11:56:09Z<p>Mol: /* Introduction */</p>
<hr />
<div>== Introduction ==<br />
Manim or manimgl. <br />
<br />
Virtual engine<br />
<br />
<syntaxhighlight lang="bash"><br />
python -m venv .<br />
source bin/activate<br />
</syntaxhighlight><br />
<br />
For faster rendering use smaller resolution <code>resolution=(15,15)</code> and smaller fps rate<br />
<syntaxhighlight lang="bash"><br />
manim -pql --fps 10 ma_animatedplanewave.py PlaneWave3D<br />
</syntaxhighlight ><br />
<br />
Some short manim scrips to generate easy visualizations.<br />
<syntaxhighlight lang="bash"><br />
manim shorts.py MyScene -r 1080,1920<br />
</syntaxhighlight ><br />
<br />
<pre><br />
manim -pql bez2.py<br />
manim -pqh bez2.py BezierSplineExample<br />
<br />
--format=png<br />
f: open the directory/ folder<br />
i: generate gif file<br />
p: play<br />
qm, qh, qk: quality (low, high, 4k)<br />
qh: high quality<br />
s: save last frame<br />
t: transparent background<br />
</pre><br />
<br />
<pre><br />
config.background_color = WHITE<br />
</pre><br />
<br />
Add a background image<br />
<pre><br />
bg_image = ImageMobject("bg_P5.png")<br />
self.add( bg_image )<br />
</pre><br />
<br />
Add the background plane<br />
<pre>plane = NumberPlane( background_line_style={<br />
"stroke_color": BLACK,<br />
"stroke_width": 4,<br />
"stroke_opacity": 1<br />
},<br />
x_range=[-10, 10, 1],<br />
y_range=[-10, 10, 1],<br />
)<br />
self.add( plane )<br />
</pre><br />
<br />
=== Install Manim on Arch Linux ===<br />
<br />
Pip is not working on a virtual environment. However use <code>uv</code> to install it. That works (on Sep 2024):<br />
<br />
<code><br />
uv pip install manim<br />
</code><br />
<br />
It is now installed on virtual environment, but the global system is not affected (not working outside virtual environment).<br />
<br />
== BG plane ==<br />
<br />
<syntaxhighlight lang="python"><br />
number_plane = NumberPlane(<br />
background_line_style={<br />
"stroke_color": TEAL,<br />
"stroke_width": 1,<br />
"stroke_opacity": 0.2<br />
}<br />
)<br />
self.add(number_plane)<br />
</syntaxhighlight ><br />
<br />
== Bezier curve ==<br />
<br />
Animated bezier curve with two points: <br />
<br />
[[File:Bez2.svg|thumb]]<br />
<br />
https://github.com/markkuleino/manim/blob/main/FLL_CC0_bezier.py<br />
<br />
See tutorial on Bezier Curves https://pomax.github.io/bezierinfo/ and the interactive tutorial https://www.jasondavies.com/animated-bezier/<br />
<br />
== Heat engine ==<br />
<br />
<gallery><br />
CarnotCycle.gif|Carnot cycle. Remove bg.<br />
Ottocycle.gif|Otto cycle. Remove bg.<br />
DieselCycle.gif|Diesel cycle. Remove bg.<br />
</gallery><br />
<br />
<br />
*[[File:Carnot.zip]]<br />
*[[File:otto.zip]]<br />
*[[File:diesel.zip]]<br />
<br />
== Paths ==<br />
<br />
<br />
https://github.com/Elteoremadebeethoven/AnimationsWithManim/blob/master/English/extra/faqs/paths.md<br />
* Show Points<br />
* Path as corners<br />
* Path smoothly<br />
* Bezier points of a path<br />
* Change path style<br />
<br />
<br />
== Lines ==<br />
<br />
https://github.com/markkuleino/manim/blob/main/FLL_CC2_m13b.py<br />
<br />
== Camera ==<br />
<br />
Animate camera movement while animating sine wave (plane wave).<br />
<br />
<syntaxhighlight lang="python"><br />
surface = always_redraw(<br />
lambda: Surface(<br />
lambda u, v: np.array([ u, v, np.sin(u - phase.get_value()) ]),<br />
u_range=[-50, 50],<br />
v_range=[-5, 5],<br />
resolution=(15, 15),<br />
fill_opacity=0.8,<br />
#checkerboard_colors=[ BLUE_D, BLUE_E, ],<br />
).set_fill_by_value(<br />
axes=axes,<br />
colors=[ (BLUE_E, -1), (BLUE, 0), (YELLOW, 1), ]<br />
)<br />
)<br />
<br />
phi, theta, focal_distance, gamma, zoom = self.camera.get_value_trackers()<br />
<br />
#1. Zoom away<br />
self.play(<br />
zoom.animate.set_value(0.5),<br />
phase.animate.set_value(8 * np.pi),<br />
run_time=10,<br />
rate_func=linear,<br />
)<br />
</syntaxhighlight ><br />
<br />
The camera parameters<br />
*phi Vertical angle (elevation)<br />
*theta Horizontal angle (azimuth/orbit angle)<br />
*focal_distance Perspective strength<br />
*gamma Roll (rotation around viewing axis)<br />
*zoom Zoom factor<br />
<br />
== Plane wave ==<br />
<br />
<syntaxhighlight lang="python"><br />
from manim import *<br />
from manim import smooth<br />
import numpy as np<br />
<br />
class PlaneWave3D(ThreeDScene):<br />
def construct(self):<br />
axes = ThreeDAxes( x_range=[-5, 5, 1], y_range=[-5, 5, 1], z_range=[-2, 2, 1],)<br />
<br />
self.set_camera_orientation(<br />
phi=65 * DEGREES,<br />
theta=-45 * DEGREES,<br />
zoom=2,<br />
)<br />
phase = ValueTracker(0)<br />
x_pos = ValueTracker(20) # start at x=10 (right)<br />
<br />
surface = always_redraw(<br />
lambda: Surface(<br />
lambda u, v: np.array([ u, v, 1*np.sin(u - phase.get_value()) ]),<br />
u_range=[-50, 50],<br />
v_range=[-5, 15],<br />
resolution=(50, 50),<br />
fill_opacity=1.0,<br />
#checkerboard_colors=[ BLUE_D, BLUE_E, ],<br />
).set_fill_by_value(<br />
axes=axes,<br />
colors=[ (BLUE_E, -1), (BLUE, 0), (YELLOW, 1), ]<br />
)<br />
)<br />
<br />
gap = 0.02<br />
antenna = always_redraw(<br />
lambda: VGroup(<br />
Line(<br />
start=[x_pos.get_value(), 0, -1], # bottom of screen<br />
end=[x_pos.get_value(), 0, -gap], # top of screen<br />
color=YELLOW,<br />
stroke_width=8<br />
),<br />
Line(<br />
start=[x_pos.get_value(), 0, gap], # bottom of screen<br />
end=[x_pos.get_value(), 0, 1], # top of screen<br />
color=YELLOW,<br />
stroke_width=8<br />
),<br />
<br />
))<br />
<br />
amplitude = 0.5<br />
antenna_sine = always_redraw(<br />
lambda: VGroup(<br />
VMobject().set_points_smoothly([<br />
np.array([<br />
x_pos.get_value() + amplitude*np.sin( np.pi*<br />
(z-gap)/(2-gap)*np.cos(phase.get_value())),<br />
0, # fixed y<br />
z<br />
])<br />
for z in np.linspace(gap, 1, 50)<br />
]),<br />
VMobject().set_points_smoothly([<br />
np.array([<br />
x_pos.get_value() - amplitude*np.sin( np.pi + np.pi*<br />
(z-gap)/(2-gap)*np.cos(phase.get_value())),<br />
0, # fixed y<br />
z<br />
])<br />
for z in np.linspace(-gap, -1, 50)<br />
]),<br />
<br />
))<br />
#self.play(Create(axes))<br />
self.play(Create(surface))<br />
<br />
#self.begin_ambient_camera_rotation( rate=0.15, about='theta')<br />
#self.begin_ambient_camera_rotation( rate=0.15, about='phi')<br />
#self.begin_ambient_camera_rotation( rate=0.15, about='gamma')<br />
#self.play(<br />
# phase.animate.set_value(8 * np.pi), run_time=10, rate_func=linear,<br />
#)<br />
#self.stop_ambient_camera_rotation( about='theta')<br />
#self.stop_ambient_camera_rotation( about='pi')<br />
#self.stop_ambient_camera_rotation( about='gamma')<br />
#self.wait()<br />
<br />
<br />
phi, theta, focal_distance, gamma, zoom = self.camera.get_value_trackers()<br />
<br />
#2. Slow down<br />
current = phase.get_value()<br />
self.play(<br />
zoom.animate.set_value(0.5),<br />
theta.animate.set_value(-10*DEGREES),<br />
phase.animate.set_value(current + 20),<br />
run_time=4,<br />
#rate_func=lambda t: 1 - (1-t)**2,<br />
rate_func = linear<br />
)<br />
#2. Ramp the<br />
cruise_speed = 2.0 # phase units per second<br />
phase.add_updater(<br />
lambda m, dt: m.increment_value(cruise_speed * dt)<br />
)<br />
self.wait(10)<br />
phase.clear_updaters()<br />
<br />
#3 Add the antenna<br />
#Add the sinewave<br />
self.add(antenna)<br />
current = phase.get_value()<br />
self.play(<br />
phase.animate.set_value(current+20),<br />
theta.animate.set_value(-90*DEGREES),<br />
phi.animate.set_value(90*DEGREES),<br />
x_pos.animate.set_value(0), # move to x=-10 (left)<br />
run_time=10,<br />
rate_func=linear,<br />
)<br />
<br />
<br />
self.add(antenna_sine)<br />
self.play(<br />
zoom.animate.set_value(3),<br />
phase.animate.set_value(current+40),<br />
run_time=10,<br />
rate_func=linear,<br />
)<br />
</syntaxhighlight></div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16574SHAREE Conference 20272026-07-09T07:06:11Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
''Not openly available''. Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books. https://www.media.mit.edu/publications/mindstorms/ <br />
<br />
NOT FREE. Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press. https://direct.mit.edu/books/book/3134/Lifelong-KindergartenCultivating-Creativity<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16573SHAREE Conference 20272026-07-09T07:05:08Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
''Not openly available''. Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books. https://www.media.mit.edu/publications/mindstorms/ <br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press. https://direct.mit.edu/books/book/3134/Lifelong-KindergartenCultivating-Creativity<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16572SHAREE Conference 20272026-07-09T07:01:04Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
''Not openly available''. Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books. https://www.media.mit.edu/publications/mindstorms/ <br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16571SHAREE Conference 20272026-07-08T07:40:18Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
''Not openly available''. Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Martinez, S. L., & Stager, G. (2019). *Invent to Learn: Making, Tinkering, and Engineering in the Classroom* (2nd ed.). Constructing Modern Knowledge Press.<br />
https://inventtolearn.com/<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books.<br />
https://mitpress.mit.edu/9780465046744/mindstorms/<br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16570SHAREE Conference 20272026-07-08T07:39:14Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
''Not openly available''. Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Martinez, S. L., & Stager, G. (2019). *Invent to Learn: Making, Tinkering, and Engineering in the Classroom* (2nd ed.). Constructing Modern Knowledge Press.<br />
https://inventtolearn.com/<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books.<br />
https://mitpress.mit.edu/9780465046744/mindstorms/<br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16569SHAREE Conference 20272026-07-08T07:38:47Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11. ''Not openly available''. <br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Martinez, S. L., & Stager, G. (2019). *Invent to Learn: Making, Tinkering, and Engineering in the Classroom* (2nd ed.). Constructing Modern Knowledge Press.<br />
https://inventtolearn.com/<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books.<br />
https://mitpress.mit.edu/9780465046744/mindstorms/<br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16568SHAREE Conference 20272026-07-08T07:05:06Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34). https://www.terecop.eu/TRTWR-RIE2014/files/00_WFr1/00_WFr1_04.pdf <br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11.<br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Martinez, S. L., & Stager, G. (2019). *Invent to Learn: Making, Tinkering, and Engineering in the Classroom* (2nd ed.). Constructing Modern Knowledge Press.<br />
https://inventtolearn.com/<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books.<br />
https://mitpress.mit.edu/9780465046744/mindstorms/<br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=SHAREE_Conference_2027&diff=16567SHAREE Conference 20272026-07-08T07:01:10Z<p>Mol: /* References (with DOI or stable links) */</p>
<hr />
<div>== Introduction ==<br />
<br />
== STEAM Week ==<br />
<br />
== Simple and Cheap Arduino-Based Teaching Environment in STEAM ==<br />
<br />
=== Submitted Abstract ===<br />
<br />
Abstract length (max 200 words, approximately 1700 characters including spaces)<br />
<br />
'''Purpose''' The study presents an affordable, internally developed open source Arduino-based ICT teaching platform designed to improve hands-on learning in programming and STEAM education. By integrating sensors and peripherals into a fixed, portable environment, the platform simplifies classroom use, reduces teacher intervention, and supports interdisciplinary learning.<br />
<br />
'''Design/methodology''' The platform was developed iteratively based on feedback from pupils and teachers. It incorporates sensors, LEDs, displays, and environmental monitoring to support practical activities across programming, mathematics, physics, and home economics. AI-assisted programming tools were included to support learning.<br />
<br />
'''Findings''' The platform was evaluated over two academic years during ICT lessons at the Finnish school of Tallinn, Estonia. Pupils successfully created functional projects, often with AI support, despite limited understanding of programming fundamentals. The platform increased engagement, encouraged creativity, and simplified classroom organization.<br />
<br />
'''Research limitations''' The study involved a small sample from a single school with strong teacher support, limiting generalizability. Quantitative analysis was constrained, and AI-assisted programming made it difficult to distinguish programming knowledge from AI-supported task completion.<br />
<br />
'''Implications''' The platform promotes project-based and interdisciplinary learning, supports scientific data collection, and enhances student motivation through interactive feedback, making it a versatile tool for STEAM education.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== Original ===<br />
<br />
<br />
'''Purpose''' The purpose of implementing and testing affordable and versatile Arduino-based teaching environments is to enhance educational experiences. This approach addresses specific challenges faced in teaching micro controllers, such as the lack of fixed positions for sensors on the table. The movement of the sensors can disrupt the functionality of the system.<br />
The system is designed to minimize the teacher intervention, as essential components are already integrated, making it easier for students to engage with the technology. This approach facilitates straightforward storage and encourages creativity, as the readily available peripherals intrigue students and spark their imagination.<br />
The multi oriented nature of this system allows educators to incorporate it into a wide array of subjects, including mathematics, programming, physics, or arts. By providing a hands-on learning experience, the environment fosters critical thinking and problem-solving skills.<br />
<br />
'''Design/methodology''' The design of the platform is informed by ideas and suggestions provided by pupils, including questions such as how a machine can determine whether it is moving, how to use visual indicators (such as LED strips, or OLED screens), sound, or text-based feedback, and whether it can sense environmental conditions such as temperature or air quality. These features can be readily incorporated into subjects such as Home Economics, Physics, or Mathematics, providing practical and interdisciplinary learning opportunities.<br />
The study design was developed based on feedback from both students and teachers, and is still under continuous development. Although certain challenges remain, pupils have demonstrated the ability to produce exceptionally high-quality outcomes with the support of AI-assisted tools. Nonetheless, the resources for teachers are being updated and will include both text-based and video content.<br />
<br />
'''Findings''' The system was evaluated over a two-year period during ICT lessons in a school setting at the Finnish school of Tallinn, Estonia. The learning activities during the classes were designed to introduce fundamental programming concepts, including loops, conditionals, and variables. The findings indicate that, with the support of AI-assisted tools, pupils are often able to create the desired program behavior even without first mastering these underlying programming principles. While this may reduce the emphasis on traditional coding skills, it can support learners who might otherwise struggle with programming and can accelerate the development of new ideas and creative solutions. In addition, the platform contributes to more efficient classroom management by simplifying the organization, monitoring, and implementation of learning activities.<br />
<br />
'''Research limitations''' Some limitations should be considered when interpreting the findings. The sample size is relatively small and limited to a single school, reducing the generalizability of the results. In addition, participants were predominantly interested in engineering and computing, which may not reflect the wider student population.<br />
The study was conducted in a small-school environment where teacher provides substantial individual support. Such conditions may differ from those in larger educational settings. Furthermore, the platform currently supports a limited range of peripherals and sensors, selected primarily based on student interest.<br />
Quantitative analysis was restricted by the small sample size and the exploratory nature of the research. The AI-assisted programming tools also makes it difficult to separate programming knowledge from AI-supported task completion. Although the study spanned two academic years, the research and development remains ongoing.<br />
<br />
'''Implications''' The findings suggest several implications for educational practice. First, hands-on and project-based activities appear to increase pupil engagement and interest in STEAM-related subjects, including electronics, programming, and engineering. The platform enables learners to explore real-world phenomena, such as gradual changes in temperature and other environmental variables, supporting the development of scientific reasoning and data literacy.<br />
In addition, the use of LED lighting and other interactive components provides immediate visual feedback, which can enhance motivation and understanding of computational concepts. The integration of sensors and measurement tools also allows the platform to function as a scientific data-collection system, creating opportunities for interdisciplinary learning across subjects such as physics, technology, and home economics. These features may help connect abstract concepts to practical applications and encourage creative experimentation.<br />
<br />
'''Keywords'''<br />
STEAM, MICROPROCESSOR, ARDUINO, TINKERING, MAKERSPACE, MEASURING TEMPERATURE<br />
<br />
=== The paper ===<br />
<br />
'''Pedagogical Foundations and the Historical Development of STEAM, Makerspaces, and Open Hardware in Education'''<br />
<br />
The integration of science, technology, engineering, arts, and mathematics (STEAM) into education reflects a broader shift toward interdisciplinary, inquiry-based, and project-oriented learning. Rooted in constructivist and constructionist educational theories, STEAM emphasizes active knowledge creation through experimentation, collaboration, and creative problem-solving rather than passive acquisition of information. The inclusion of makerspaces, open-source electronics platforms such as Arduino, programmable robotics (including LEGO systems), and community-driven "hacker" initiatives has significantly expanded opportunities for authentic learning in school subjects ranging from physics and chemistry to home economics and culinary education.<br />
<br />
The educational philosophy underlying modern STEAM can be traced to the work of John Dewey, who argued that meaningful learning emerges through experience and reflection. Later, Seymour Papert extended these ideas through constructionism, proposing that learners develop deeper understanding by creating tangible artifacts that are personally meaningful. These theoretical perspectives have become central to contemporary makerspaces, where students design, prototype, test, and refine physical and digital projects while integrating scientific reasoning with engineering design (Papert, 1980).<br />
<br />
The term STEM was popularized during the early 2000s to strengthen education in science and engineering, particularly in response to workforce demands and technological innovation. Subsequently, the addition of the Arts transformed STEM into STEAM, recognizing that creativity, design thinking, communication, and aesthetics are essential components of innovation (Yakman, 2008). Today, STEAM education seeks not only to develop disciplinary knowledge but also to foster critical thinking, collaboration, creativity, and digital literacy—competencies frequently described as essential twenty-first-century skills (Henriksen, 2017).<br />
<br />
A significant practical manifestation of STEAM pedagogy is the makerspace. Makerspaces are collaborative learning environments equipped with digital fabrication tools, electronics, programmable devices, and traditional craft materials that encourage experimentation and iterative design. Rather than following predetermined laboratory procedures, learners formulate problems, construct prototypes, evaluate outcomes, and improve their solutions. Research demonstrates that makerspaces promote learner autonomy, motivation, and interdisciplinary understanding while supporting inclusive participation across diverse learner groups (Sheridan et al., 2014; Martin, 2015).<br />
<br />
Among the most influential educational technologies within makerspaces is the Arduino platform. Introduced in 2005 as an open-source microcontroller ecosystem, Arduino was developed to make embedded electronics and physical computing accessible to artists, designers, educators, and novice programmers. Its combination of low cost, open-source hardware and software, extensive documentation, and a large international user community has led to widespread adoption across engineering, STEM, and interdisciplinary educational settings (El-Abd, 2017, Tselegkaridis, 2024). Its affordability, extensive documentation, and large global community have made it one of the most widely adopted educational platforms for teaching programming, electronics, data acquisition, and automation. Students can construct weather stations, environmental monitoring systems, smart home prototypes, or laboratory instruments using inexpensive sensors that measure temperature, humidity, light intensity, pressure, pH, electrical conductivity, or motion.<br />
<br />
Similarly, LEGO educational systems, particularly LEGO Education and LEGO Mindstorms (and their successors), have played a major role in introducing engineering concepts to learners through programmable robotics. These systems enable students to investigate mechanical design, control systems, mathematics, and computational thinking while maintaining a playful and highly motivating learning environment. Numerous studies have shown that robotics activities support problem-solving abilities, teamwork, and conceptual understanding in STEM subjects (Eguchi, 2014).<br />
<br />
The growing availability of low-cost sensors and open-source hardware has also encouraged educational practices inspired by the hacker and maker movements. In this context, the term "hacker" refers not to illegal computer activities but to a culture of curiosity, creativity, open knowledge sharing, and technological exploration. Hackerspaces and Fab Labs emphasize learning through experimentation, reverse engineering, collaborative problem-solving, and open-source development. Educational adaptations of these principles encourage students to understand how technologies function internally rather than merely consuming finished products (Blikstein, 2013).<br />
<br />
''These approaches have proven particularly valuable in school physics and chemistry laboratories. Arduino-based data logging allows students to perform real-time measurements of physical phenomena such as acceleration, force, magnetic fields, electrical circuits, heat transfer, and oscillatory motion. In chemistry education, digital sensors can continuously monitor variables including temperature, pH, dissolved oxygen, conductivity, gas concentration, or reaction kinetics, enabling more precise quantitative investigations than traditional manual methods. Automated data collection also allows greater emphasis on experimental design, data interpretation, uncertainty analysis, and scientific reasoning.''<br />
<br />
Interestingly, STEAM principles have increasingly been incorporated into home economics education, where cooking provides an authentic interdisciplinary context for scientific inquiry. Food preparation naturally involves concepts from chemistry, physics, biology, mathematics, engineering, and nutrition. Arduino-compatible digital thermometers, load cells for precision weighing, humidity sensors, infrared temperature sensors, and timers enable students to investigate processes such as protein denaturation, starch gelatinization, caramelization, fermentation, heat transfer, energy efficiency, and moisture loss during cooking. Students may compare different heating methods, optimize baking conditions, or collect quantitative data to evaluate recipes scientifically. Such investigations transform cooking from a procedural activity into an evidence-based design challenge that integrates measurement, experimentation, and reflection while simultaneously developing practical life skills.<br />
<br />
Overall, the convergence of STEAM pedagogy, makerspaces, open-source electronics, programmable robotics, and hacker-inspired learning communities represents an important evolution in contemporary education. These approaches encourage learners to become active investigators, designers, and creators who connect theoretical knowledge with practical applications across multiple disciplines. By integrating precise digital measurements into physics, chemistry, and home economics, educators can provide authentic learning experiences that strengthen scientific literacy, technological competence, creativity, and lifelong problem-solving skills.<br />
<br />
=== References (with DOI or stable links) ===<br />
<br />
<br />
El-Abd, M. (2017). A Review of Embedded Systems Education in the Arduino Age: Lessons Learned and Future Directions. International Journal of Engineering Pedagogy, 7(2), 79–93. https://doi.org/10.3991/ijep.v7i2.6845<br />
<br />
Tselegkaridis, S., Sapounidis, T., & Papakostas, D. (2024). Learning Circuits and Coding with Arduino Board in Higher Education Using Tangible and Graphical User Interfaces. Information, 15(5), 245. https://doi.org/10.3390/info15050245<br />
<br />
Blikstein, P. (2013). Digital fabrication and "making" in education: The democratization of invention. In J. Walter-Herrmann & C. Büching (Eds.), *FabLabs: Of Machines, Makers and Inventors* (pp. 1–21). Transcript Verlag. https://inventingtolearn.org/wp-content/uploads/2023/10/Blikstein-2013-Digital-fabrication-and-%E2%80%98making-in-education-The-democratization-of-invention5.pdf<br />
https://www.researchgate.net/publication/281495128_Digital_Fabrication_and_'Making'_in_Education_The_The_Democratization_of_Invention<br />
<br />
Dewey, J. (1938). *Experience and Education*. New York: Macmillan. https://archive.org/details/ExperienceAndEducation/page/n13/mode/2up or original photocopy <br />
https://archive.org/details/experienceeducat00dewe<br />
<br />
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. In *Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics* (pp. 27–34).<br />
https://doi.org/10.1007/978-3-319-16369-7_3<br />
<br />
Henriksen, D. (2017). Creating STEAM with design thinking: Beyond STEM and arts integration. *The STEAM Journal, 3*(1), Article 11.<br />
https://doi.org/10.5642/steam.20170301.11<br />
<br />
Honey, M., & Kanter, D. E. (Eds.). (2013). *Design, Make, Play: Growing the Next Generation of STEM Innovators*. Routledge.<br />
https://doi.org/10.4324/9780203108352<br />
<br />
Martin, L. (2015). The promise of the maker movement for education. *Journal of Pre-College Engineering Education Research, 5*(1), 30–39.<br />
https://doi.org/10.7771/2157-9288.1099<br />
<br />
Martinez, S. L., & Stager, G. (2019). *Invent to Learn: Making, Tinkering, and Engineering in the Classroom* (2nd ed.). Constructing Modern Knowledge Press.<br />
https://inventtolearn.com/<br />
<br />
Papert, S. (1980). *Mindstorms: Children, Computers, and Powerful Ideas*. Basic Books.<br />
https://mitpress.mit.edu/9780465046744/mindstorms/<br />
<br />
Resnick, M. (2017). *Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play*. MIT Press.<br />
https://doi.org/10.7551/mitpress/11001.001.0001<br />
<br />
Sheridan, K., Halverson, E. R., Litts, B. K., Brahms, L., Jacobs-Priebe, L., & Owens, T. (2014). Learning in the making: A comparative case study of three makerspaces. *Harvard Educational Review, 84*(4), 505–531.<br />
https://doi.org/10.17763/haer.84.4.brr34733723j648u<br />
<br />
Yakman, G. (2008). STEAM education: An overview of creating a model of integrative education. In *Proceedings of the Pupils' Attitudes Towards Technology (PATT-19) Conference*.<br />
https://www.academia.edu/8113832/STEAM_Education_An_Overview_of_Creating_a_Model_of_Integrative_Education</div>Molhttps://wiki.luntti.net/index.php?title=Create_references_and_citations_database_in_Linux&diff=16566Create references and citations database in Linux2026-07-07T14:44:21Z<p>Mol: /* Introduction */</p>
<hr />
<div>== Introduction ==<br />
<br />
# Zotero + Better Notes<br />
# Obsidian + Zotero Integration<br />
# Logseq<br />
# Connected Papers<br />
# ResearchRabbit<br />
# Litmaps<br />
# JabRef (markdown)<br />
<br />
Myös<br />
#Neo4j<br />
#Memgraph<br />
#Kùzu<br />
<br />
#Zettlr<br />
<br />
#GROBID<br />
<br />
== Zotero & Better Notes ==</div>Molhttps://wiki.luntti.net/index.php?title=Pedagogy&diff=16565Pedagogy2026-07-07T14:39:43Z<p>Mol: /* Some famous propaganda */</p>
<hr />
<div>== Introduction ==<br />
<br />
Some interesting theories about learning.<br />
<br />
See also https://www.allourideas.org/trendiez/results?all=true<br />
<br />
== Theories ==<br />
<br />
* Collaborative learning<br />
* Compulsory learning<br />
* Computational-based learning<br />
* Discovery Learning<br />
* Distance learning<br />
* Inquiry-based learning<br />
* Narrative scenarios<br />
* Problem solving<br />
* Project-based learning<br />
* Scenario-based learning<br />
* Socioscientific Issues-Based Instruction https://serc.carleton.edu/sp/library/issues/what.html<br />
<br />
Roshenshine's Principles, 17 afn 10 in the UNESCO publications? Greg Ashman?<br />
<br />
== Some famous people ==<br />
<br />
* Arving Gupta<br />
* Sugata Mitra <br />
* Papiert<br />
* [https://www.importanceofplay.eu/wp-content/uploads/2019/11/Dr-David-Whitebread-The-importance-of-play-final.pdf Dr David Whitebread]<br />
<br />
== Some famous propaganda ==<br />
<br />
17 Principles of Effective Instruction <br />
The following list of 17 principles emerges from the research discussed in the main article. It overlaps with, and offers slightly more detail than, the 10 principles used to organize that article. <br />
# Begin a lesson with a short review of previous learning. <br />
# Present new material in small steps with student practice after each step. <br />
# Limit the amount of material students receive at one time. <br />
# Give clear and detailed instructions and explanations. <br />
# Ask a large number of questions and check for understanding. <br />
# Provide a high level of active practice for all students. <br />
# Guide students as they begin to practice. <br />
# Think aloud and model steps. <br />
# Provide models of worked-out problems. <br />
# Ask students to explain what they have learned. <br />
# Check the responses of all students. <br />
# Provide systematic feedback and corrections. <br />
# Use more time to provide explanations. <br />
# Provide many examples. <br />
# Reteach material when necessary. <br />
# Prepare students for independent practice. <br />
# Monitor students when they begin independent practice. —B.R.</div>Molhttps://wiki.luntti.net/index.php?title=Pedagogy&diff=16564Pedagogy2026-07-07T12:56:32Z<p>Mol: /* Some famous people */</p>
<hr />
<div>== Introduction ==<br />
<br />
Some interesting theories about learning.<br />
<br />
See also https://www.allourideas.org/trendiez/results?all=true<br />
<br />
== Theories ==<br />
<br />
* Collaborative learning<br />
* Compulsory learning<br />
* Computational-based learning<br />
* Discovery Learning<br />
* Distance learning<br />
* Inquiry-based learning<br />
* Narrative scenarios<br />
* Problem solving<br />
* Project-based learning<br />
* Scenario-based learning<br />
* Socioscientific Issues-Based Instruction https://serc.carleton.edu/sp/library/issues/what.html<br />
<br />
Roshenshine's Principles, 17 afn 10 in the UNESCO publications? Greg Ashman?<br />
<br />
== Some famous people ==<br />
<br />
* Arving Gupta<br />
* Sugata Mitra <br />
* Papiert<br />
* [https://www.importanceofplay.eu/wp-content/uploads/2019/11/Dr-David-Whitebread-The-importance-of-play-final.pdf Dr David Whitebread]<br />
<br />
== Some famous propaganda ==<br />
<br />
17 Principles of Effective Instruction <br />
The following list of 17 principles emerges from the research discussed in the main article. It overlaps with, and offers slightly more detail than, the 10 principles used to organize that article. • Begin a lesson with a short review of previous learning. • Present new material in small steps with student practice after each step. • Limit the amount of material students receive at one time. • Give clear and detailed instructions and explanations. • Ask a large number of questions and check for understanding. • Provide a high level of active practice for all students. • Guide students as they begin to practice. • Think aloud and model steps. • Provide models of worked-out problems. • Ask students to explain what they have learned. • Check the responses of all students. • Provide systematic feedback and corrections. • Use more time to provide explanations. • Provide many examples. • Reteach material when necessary. • Prepare students for independent practice. • Monitor students when they begin independent practice. —B.R.</div>Molhttps://wiki.luntti.net/index.php?title=DIY_drum_machine_sequencer_with_samples&diff=16563DIY drum machine sequencer with samples2026-07-07T12:44:00Z<p>Mol: /* Introduction */</p>
<hr />
<div>== Introduction ==<br />
''May the music passing through this device somehow help to bring just a little more peace to this troubled world''<br />
<br />
<gallery><br />
Teensy1.jpg<br />
Teensy2.jpg<br />
Teensy audioboard2.jpg<br />
Teensy audioboard1.jpg<br />
Teensy audioboardInstalled.jpg<br />
Teensy groovebox1.jpg<br />
</gallery><br />
<br />
Teensy based drum machine/ sequencer (groovebox?) with high quality samples<br />
<br />
The knobs:<br />
* Bpm<br />
* Play/ record<br />
* Free rhythm / on beat<br />
* Track number selection<br />
* Length: 8 / 16 beats<br />
* number showing current step<br />
* Drums; shown below.<br />
* Display? showing the situation<br />
<br />
Use potentiometer as Rotary selector switch.<br />
<br />
The drums included (see https://en.wikipedia.org/wiki/List_of_percussion_instruments)<br />
# Bass Drum https://samplefocus.com/samples/bass-drum-hit?search_id=199954966<br />
# Bongo Drum<br />
# Cajon Drum<br />
# Castanets<br />
# Conga Drums<br />
# Cowbell https://samplefocus.com/samples/cowbell-f92f5f7b-5be6-44b7-bd5c-055dab612e55?search_id=199955024<br />
# Cymbals https://samplefocus.com/samples/bright-soft-crash?search_id=199954863<br />
# Djembe Drum<br />
# Gongs<br />
# Hi-hat<br />
# Maracas<br />
# Snare Drum https://samplefocus.com/samples/snare-drum-phonk-hit<br />
# Steelpan https://samplefocus.com/samples/steel-pan-drum-15?search_id=199954909<br />
# Tambourine<br />
# Triangle<br />
# Woodblock<br />
<br />
== Material == <br />
=== ===<br />
<br />
=== ===<br />
<br />
<gallery><br />
Teensy groovebox.png|The plan. Note that also the svg version is available.<br />
</gallery><br />
<br />
* 0.91" OLED Display module 128x32 px. I2C (SSD1306 driver). 36 x 12.5 (mm). '''Too small for my eyes'''.<br />
* Teensy 4.1 - No ethernet<br />
** 55 digital input/output pins, 35 PWM output pins<br />
** 18 analog input pins<br />
** 8 serial, 3 SPI, 3 I2C ports<br />
** 3 CAN Bus (1 with CAN FD)<br />
** Output 3.3V 250mA out <br />
** Vin 3.6 V to 5.5V<br />
* Audio Adapter board for Teensy 4.0 (Rev D) https://www.pjrc.com/store/teensy3_audio.html<br />
* 8 x Mini LED Arcade buttons 24 mm. (The parallel ~1K resistors are built in. Power the LED from a microcontroller pin or direct from 5V (eg a USB) with 10mA draw. With 3.3V power, 2mA per button.) See arcade button wiring guide https://himuragames.com/led-arcade-buttons-wiring-guide/ Thus 250mA/2mA gives many. <br />
* 3 x Illuminated Latching push button 16 mm<br />
<br />
=== Wiring ===<br />
<br />
Wiring the arcade buttons.<br />
* use the internal pullup resistor, connect one side of the button to GND and the other side to a pin on the Teensy. Use pinMode(pin, INPUT_PULLUP); to enable the internal pullup resistor (an internal pull up resistor [~47kΩ] is enabled, to keep the signal HIGH by default.)<br />
* Use Debouncing library: The high speed of the Teensy 4.1 makes it very sensitive to mechanical switch bounce. Use a library like Bounce2 for reliable button input.<br />
<br />
Simple test program. Should use <code>Bounce(pin, time);</code> function.<br />
<syntaxhighlight lang="C"><br />
const int buttonPin1 = 32; // the number of the pushbutton pin<br />
const int buttonPin2 = 31; // the number of the pushbutton pin<br />
const int buttonPin3 = 30; // the number of the pushbutton pin<br />
const int buttonPin4 = 29; // the number of the pushbutton pin<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
<br />
pinMode(buttonPin1, INPUT_PULLUP);<br />
pinMode(buttonPin2, INPUT_PULLUP);<br />
pinMode(buttonPin3, INPUT_PULLUP);<br />
pinMode(buttonPin4, INPUT_PULLUP);<br />
}<br />
<br />
void loop() {<br />
if ( digitalRead(buttonPin1) == LOW ){<br />
Serial.println("1");<br />
}<br />
if ( digitalRead(buttonPin2) == LOW ){<br />
Serial.println("2");<br />
}<br />
if ( digitalRead(buttonPin3) == LOW ){<br />
Serial.println("3");<br />
}<br />
if ( digitalRead(buttonPin4) == LOW ){<br />
Serial.println("4");<br />
}<br />
}<br />
</syntaxhighlight><br />
<br />
Potentiometer<br />
* Potentiometer + Pin to 3.3V<br />
* Potentiometer - Pin to GND<br />
* Potentiometer Data Pin<br />
<br />
OLED Display module <br />
* I2C (Normally a 4.7K pullup resistor is connected between each signal and power, but the weak internal pullup resistors may be sufficient for short wires to a single device.)<br />
** SDA (18, Wire1 17, or 25)<br />
** SCL (19, Wire1 16, or 24)<br />
<br />
Audio Board, I2C<br />
* SDA 18<br />
* SCL 19<br />
<br />
=== Teensy Pins ===<br />
<br />
Teensy 4.1 has a total of 55 input/output signal pins, from which 42 are easily accessible when used with a solderless breadboard. In teensy 4.1, 35 PWM pin support and 18 analog pins are present.<br />
<br />
The pins 23 - 32 and 33 - 42 are easily available.<br />
* The 23 is 3.3V output. The potentiometer's other end should be there.<br />
* Pins A0 - A17 (24, 25, 26, 27 and 38, 39, 40, 41) are analog input pins. See https://www.etechnophiles.com/teensy-4-1-pinout/<br />
<br />
== Teensy 4 Audio Library and Audio Board ==<br />
<br />
=== Audio Board ===<br />
https://www.pjrc.com/store/teensy3_audio.html<br />
<br />
Audio Board is based on the SGTL5000 chip which in addition to ADC/DAC and amplifiers also offers some basic DSP functionality. The Adapter board has line input and output, mic input, and headphone output. Connect to Teensy using very short wires because of high-frequency master clock input (MCLK).<br />
<br />
Audio Board connects to Teensy using 7 signals. The I2C pins SDA and SCL are used to control the chip and adjust parameters. Audio data uses I2S signals. DIN and DOUT and 3 clocks (LRCLK 44.1 kHZ, BCLK 1.41 or 2.82 MHZ and MCLK 11.29 MHz. <br />
<br />
{| class="wikitable"<br />
! Signal<br />
! Rev D, D2 (Teensy 4.x)<br />
! Required For<br />
! Function<br />
|-<br />
| MCLK<br />
| 23 (MCLK1)<br />
| Audio<br />
| Audio Master Clock, 11.29 MHz<br />
|-<br />
| BCLK<br />
| 21 (BCLK1)<br />
| Audio<br />
| Audio Bit Clock, 1.41 or 2.82 MHz<br />
|-<br />
| LRCLK<br />
| 20 (LRCLK1)<br />
| Audio<br />
| Audio Left/Right Clock, 44.1 kHz<br />
|-<br />
| DIN<br />
| 7 (OUT1A)<br />
| Audio Output<br />
| Audio Data from Teensy to Audio Shield. Goes to both headphone jack and Line-Out pins.<br />
|-<br />
| DOUT<br />
| 8 (IN1)<br />
| Audio Input<br />
| Audio Data from Audio Shield to Teensy. Comes from either Microphone or Line-In pins.<br />
|-<br />
| SCL<br />
| 19<br />
| Audio Config<br />
| Control Clock (I2C)<br />
|-<br />
| SDA<br />
| 18<br />
| Audio Config<br />
| Control Data (I2C)<br />
|-<br />
| SCK<br />
| 13<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) Clock<br />
|-<br />
| MISO<br />
| 12<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) from SD/MEM to Teensy<br />
|-<br />
| MOSI<br />
| 11<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) from Teensy to SD/MEM<br />
|-<br />
| SDCS<br />
| 10<br />
| Optional Data SD Card<br />
| Chip Select (SPI) for SD Card<br />
|-<br />
| MEMCS<br />
| 6<br />
| Optional Data MEM Chip<br />
| Chip Select (SPI) for Memory Chip<br />
|-<br />
| Vol<br />
| 15 / A1<br />
| Optional Knob<br />
| Volume Thumbwheel (analog signal)<br />
|}<br />
<br />
=== Play a sine wave ===<br />
<br />
Test 1, almost from https://gist.github.com/mwicat/4c129fe835d58258688974d5e02ffb75<br />
<syntaxhighlight lang="C"><br />
#include <Audio.h><br />
<br />
AudioSynthWaveformSine sineWave; // Create a sine wave object<br />
AudioOutputAnalog output; // Create an analog output object<br />
AudioConnection patchCord(sineWave, output);<br />
<br />
void setup() {<br />
AudioMemory(8); // Allocate memory for audio processing<br />
sineWave.frequency(440); // Set frequency to 440 Hz (A4)<br />
sineWave.amplitude(0.5); // Set amplitude<br />
}<br />
<br />
void loop() {<br />
// The sine wave will continuously play<br />
}<br />
</syntaxhighlight><br />
<br />
Test2 Sine/Square Wave Generator: https://github.com/jameskeaveney/Teensy-SineWaveGenerator/blob/master/SineGen.ino<br />
<br />
=== Teensy 4 Signal Generator ===<br />
<br />
DDS (Direct Digital Synthesis) For teensy 3.5 https://github.com/EmaMaker/SignalGenerator-Teensy/blob/master/README.md<br />
<br />
Harmonic distortion https://kennypeng.com/2020/11/23/teensy_harmonic_distortion.html https://github.com/colonelwatch/teensy-harmonic-distortion<br />
<br />
Teensy Dynamic Sound Effects Processor https://cdn.hackaday.io/files/1638357009516640/Final%20Project_Complete.pdf<br />
<br />
=== Hackaday tutorial ===<br />
The tutorial: https://hackaday.io/project/8292-microcontroller-audio-workshop-had-supercon-2015 and the pdf file from https://raw.githubusercontent.com/PaulStoffregen/AudioWorkshop2015/master/workshop.pdf<br />
<br />
Playing a file from SD card.<br />
File → Examples → Audio → Tutorial → Part_1_03_Playing_Music. Also available below (slightly modified version) and at https://github.com/PaulStoffregen/Audio/blob/master/examples/WavFilePlayer/WavFilePlayer.ino<br />
* Insert the Micro SD card from the card reader and into the Teensy Audio Shield before you upload the program. The music files are stored on this MicroSD card.<br />
<br />
Three different audio outputs<br />
* AudioOutputI2S audioOutput;<br />
* AudioOutputSPDIF audioOutput;<br />
* AudioOutputAnalog audioOutput;<br />
See the memory function at MemoryAndCpuUsage example<br />
<br />
The <code>patchCord1(playWav1, 0, audioOutput, 0);</code> connects the left output channel (channel 0) of the WAV file player (playWav1) to the left input channel (channel 0) of the audio output (audioOutput).<br />
<br />
<syntaxhighlight lang="C"><br />
#include <Audio.h><br />
#include <Wire.h><br />
#include <SPI.h><br />
#include <SD.h><br />
#include <SerialFlash.h><br />
<br />
AudioPlaySdWav playWav1;<br />
AudioOutputI2S audioOutput;<br />
<br />
AudioConnection patchCord1(playWav1, 0, audioOutput, 0);<br />
AudioConnection patchCord2(playWav1, 1, audioOutput, 1);<br />
AudioControlSGTL5000 sgtl5000_1;<br />
<br />
// Use these with the Teensy Audio Shield<br />
#define SDCARD_CS_PIN 10<br />
#define SDCARD_MOSI_PIN 7 // Teensy 4 ignores this, uses pin 11<br />
#define SDCARD_SCK_PIN 14 // Teensy 4 ignores this, uses pin 13<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
AudioMemory(8);<br />
<br />
sgtl5000_1.enable();<br />
sgtl5000_1.volume(0.5);<br />
<br />
SPI.setMOSI(SDCARD_MOSI_PIN);<br />
SPI.setSCK(SDCARD_SCK_PIN);<br />
if (!(SD.begin(SDCARD_CS_PIN))) {<br />
// stop here, but print a message repetitively<br />
while (1) {<br />
Serial.println("Unable to access the SD card");<br />
delay(500);<br />
}<br />
}<br />
}<br />
<br />
void playFile(const char *filename){<br />
Serial.print("Playing file: ");<br />
Serial.println(filename);<br />
<br />
playWav1.play(filename);<br />
<br />
delay(25); // A brief delay for the library read WAV info<br />
<br />
// Simply wait for the file to finish playing.<br />
while (playWav1.isPlaying()) {<br />
}<br />
}<br />
<br />
<br />
void loop() {<br />
playFile("SDTEST1.WAV"); // filenames are always uppercase 8.3 format<br />
delay(500);<br />
playFile("SDTEST2.WAV");<br />
delay(500);<br />
playFile("SDTEST3.WAV");<br />
delay(500);<br />
playFile("SDTEST4.WAV");<br />
delay(1500);<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
<br />
Blink LED while Playing Music.<br />
File → Examples → Audio → Tutorial → Part_1_04_Blink_While_Playing<br />
<br />
Use eg <br />
<syntaxhighlight lang="C"><br />
elapsedMillis blinkTime;<br />
. . .<br />
if (blinkTime < 250) {<br />
digitalWrite(LED_PIN, LOW);<br />
} else if (blinkTime < 500) {<br />
digitalWrite(LED_PIN, HIGH);<br />
} else {<br />
blinkTime = 0; // start blink cycle over again<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
Do More While Playing Music. <br />
File → Examples → Audio → Tutorial → Part_1_05_Do_More_While_Playing<br />
* The potentiometer controls the volume immediately, regardless of status of the LED. <br />
* The pushbuttons are read using the Bounce library<br />
<br />
=== The GUI ===<br />
<br />
Audio system design GUI https://www.pjrc.com/teensy/gui/ (page 9)<br />
From the main Arduino folder, navigate to these folders hardware / teensy / avr / libraries / Audio / gui. Inside the gui folder, open index.html<br />
<br />
== References ==<br />
<br />
<br />
Teensy / Arduino/ ESP32 based drum machine/ sequencer with high quality samples. Use MIDI to transfer data from sequencer to synth. / Groovebox.<br />
References:<br />
<br />
DIY Arduino Drum Synth + FREE SAMPLES! https://www.youtube.com/watch?v=xo-iN3tfE6o<br />
* Simple, good starting point!<br />
* https://github.com/NickCulbertson/Arduino-Audio-Projects<br />
<br />
https://www.instructables.com/MIDI-Drum-Machine/<br />
<br />
ARDUINO 8 STEP KEYBOARD SEQUENCER FOR SYNTHESIZERS https://www.youtube.com/watch?v=9oGlCfwCoCw<br />
* https://www.lookmumnocomputer.com/projects/#/sequencer-keyboard<br />
* CV patch cables (also called mini-jack patch cables, modular patch cables or Eurorack cables)<br />
<br />
Drum trigger sequencer. How To Make Your Own Drum Sequencer DIY The BIG BUTTON https://www.youtube.com/watch?v=6ArDGcUqiWM<br />
<br />
<br />
<br />
https://diyelectromusic.com/2021/06/23/arduino-mozzi-sample-drum-sequencer/<br />
* <br />
<br />
Doof machine <br />
<br />
https://github.com/gavD/arduino-drum-machine<br />
<br />
<br />
Mozzi https://sensorium.github.io/Mozzi/gallery/<br />
<br />
<br />
The Bastl Microgranny https://www.instructables.com/Microgranny-Sampler-Completely-Home-built-not-a-Ki/<br />
<br />
SnapBeat https://www.hackster.io/hiro-akihabara/snapbeat-the-simple-lo-fi-sampler-5a3222<br />
<br />
https://www.youtube.com/watch?v=U5Q8chfMglE<br />
<br />
https://www.youtube.com/watch?v=YeKsXck8LDY<br />
<br />
NI404 https://www.synthtopia.com/content/2024/01/21/the-ni404-is-an-open-source-diy-hardware-sampler-sequencer/<br />
* TOERN new version https://toern.live/<br />
<br />
MOTHSYNTH https://www.mothsynth.com/<br />
<br />
Samplotron https://hackaday.io/project/205253/components<br />
<br />
Pushpin https://pushpin.kinga.dev/<br />
<br />
Cosmic Loop https://github.com/kreiff/Cosmic_Loop<br />
<br />
OpnBeat https://hackaday.io/project/190273-opnbeat-diy-lo-fi-sampler-with-isd1700-series<br />
<br />
Launchpad https://github.com/pabolojo/DIY-Launchpad<br />
<br />
Yorick https://bristol-communal-modular.github.io/yorick/?utm_source=chatgpt.com<br />
<br />
== Button test ==<br />
<br />
<syntaxhighlight lang="C"><br />
<br />
//LEFT SIDE<br />
const int buttonPin1 = 41; // the number of the pushbutton pin<br />
const int buttonPin2 = 40; // the number of the pushbutton pin<br />
const int buttonPin3 = 39; // the number of the pushbutton pin<br />
const int buttonPin4 = 38; // the number of the pushbutton pin<br />
const int buttonPin5 = 37; // the number of the pushbutton pin<br />
const int buttonPin6 = 36; // the number of the pushbutton pin<br />
const int buttonPin7 = 35; // the number of the pushbutton pin<br />
const int buttonPin8 = 34; // the number of the pushbutton pin<br />
//last is empty<br />
<br />
//RIGHT SIDE<br />
const int potentiometer1 = 24; // ANALOG INPUT<br />
<br />
const int togglePin1 = 25; // the number of the pushbutton pin<br />
const int togglePin2 = 26; // the number of the pushbutton pin<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
<br />
pinMode(buttonPin1, INPUT_PULLUP);<br />
pinMode(buttonPin2, INPUT_PULLUP);<br />
pinMode(buttonPin3, INPUT_PULLUP);<br />
pinMode(buttonPin4, INPUT_PULLUP);<br />
pinMode(buttonPin5, INPUT_PULLUP);<br />
pinMode(buttonPin6, INPUT_PULLUP);<br />
pinMode(buttonPin7, INPUT_PULLUP);<br />
pinMode(buttonPin8, INPUT_PULLUP);<br />
<br />
pinMode(togglePin1, INPUT_PULLUP);<br />
pinMode(togglePin2, INPUT_PULLUP);<br />
<br />
<br />
}<br />
<br />
int val;<br />
<br />
void loop() {<br />
if ( digitalRead(buttonPin1) == LOW ){<br />
Serial.print("1, ");<br />
}<br />
if ( digitalRead(buttonPin2) == LOW ){<br />
Serial.print("2, ");<br />
}<br />
if ( digitalRead(buttonPin3) == LOW ){<br />
Serial.print("3, " );<br />
}<br />
if ( digitalRead(buttonPin4) == LOW ){<br />
Serial.print("4, " );<br />
}<br />
if ( digitalRead(buttonPin5) == LOW ){<br />
Serial.print("5, ");<br />
}<br />
if ( digitalRead(buttonPin6) == LOW ){<br />
Serial.print("6, ");<br />
}<br />
if ( digitalRead(buttonPin7) == LOW ){<br />
Serial.print("7, ");<br />
}<br />
if ( digitalRead(buttonPin8) == LOW ){<br />
Serial.print("8, ");<br />
}<br />
<br />
if ( digitalRead(togglePin1) == LOW ){<br />
Serial.print("t1, ");<br />
}<br />
if ( digitalRead(togglePin2) == LOW ){<br />
Serial.print("t2, ");<br />
}<br />
<br />
val = analogRead( potentiometer1 );<br />
Serial.println(val);<br />
<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
== 2 ==<br />
<br />
== References ==<br />
<br />
Teensy Best Practices: https://gist.github.com/somebox/d969f8a97e5a4362af5049ed554a9e69</div>Molhttps://wiki.luntti.net/index.php?title=DIY_drum_machine_sequencer_with_samples&diff=16562DIY drum machine sequencer with samples2026-07-07T12:39:55Z<p>Mol: /* Introduction */</p>
<hr />
<div>== Introduction ==<br />
<br />
<gallery><br />
Teensy1.jpg<br />
Teensy2.jpg<br />
Teensy audioboard2.jpg<br />
Teensy audioboard1.jpg<br />
Teensy audioboardInstalled.jpg<br />
Teensy groovebox1.jpg<br />
</gallery><br />
<br />
Teensy based drum machine/ sequencer (groovebox?) with high quality samples<br />
<br />
The knobs:<br />
* Bpm<br />
* Play/ record<br />
* Free rhythm / on beat<br />
* Track number selection<br />
* Length: 8 / 16 beats<br />
* number showing current step<br />
* Drums; shown below.<br />
* Display? showing the situation<br />
<br />
Use potentiometer as Rotary selector switch.<br />
<br />
The drums included (see https://en.wikipedia.org/wiki/List_of_percussion_instruments)<br />
# Bass Drum https://samplefocus.com/samples/bass-drum-hit?search_id=199954966<br />
# Bongo Drum<br />
# Cajon Drum<br />
# Castanets<br />
# Conga Drums<br />
# Cowbell https://samplefocus.com/samples/cowbell-f92f5f7b-5be6-44b7-bd5c-055dab612e55?search_id=199955024<br />
# Cymbals https://samplefocus.com/samples/bright-soft-crash?search_id=199954863<br />
# Djembe Drum<br />
# Gongs<br />
# Hi-hat<br />
# Maracas<br />
# Snare Drum https://samplefocus.com/samples/snare-drum-phonk-hit<br />
# Steelpan https://samplefocus.com/samples/steel-pan-drum-15?search_id=199954909<br />
# Tambourine<br />
# Triangle<br />
# Woodblock<br />
<br />
== Material == <br />
=== ===<br />
<br />
=== ===<br />
<br />
<gallery><br />
Teensy groovebox.png|The plan. Note that also the svg version is available.<br />
</gallery><br />
<br />
* 0.91" OLED Display module 128x32 px. I2C (SSD1306 driver). 36 x 12.5 (mm). '''Too small for my eyes'''.<br />
* Teensy 4.1 - No ethernet<br />
** 55 digital input/output pins, 35 PWM output pins<br />
** 18 analog input pins<br />
** 8 serial, 3 SPI, 3 I2C ports<br />
** 3 CAN Bus (1 with CAN FD)<br />
** Output 3.3V 250mA out <br />
** Vin 3.6 V to 5.5V<br />
* Audio Adapter board for Teensy 4.0 (Rev D) https://www.pjrc.com/store/teensy3_audio.html<br />
* 8 x Mini LED Arcade buttons 24 mm. (The parallel ~1K resistors are built in. Power the LED from a microcontroller pin or direct from 5V (eg a USB) with 10mA draw. With 3.3V power, 2mA per button.) See arcade button wiring guide https://himuragames.com/led-arcade-buttons-wiring-guide/ Thus 250mA/2mA gives many. <br />
* 3 x Illuminated Latching push button 16 mm<br />
<br />
=== Wiring ===<br />
<br />
Wiring the arcade buttons.<br />
* use the internal pullup resistor, connect one side of the button to GND and the other side to a pin on the Teensy. Use pinMode(pin, INPUT_PULLUP); to enable the internal pullup resistor (an internal pull up resistor [~47kΩ] is enabled, to keep the signal HIGH by default.)<br />
* Use Debouncing library: The high speed of the Teensy 4.1 makes it very sensitive to mechanical switch bounce. Use a library like Bounce2 for reliable button input.<br />
<br />
Simple test program. Should use <code>Bounce(pin, time);</code> function.<br />
<syntaxhighlight lang="C"><br />
const int buttonPin1 = 32; // the number of the pushbutton pin<br />
const int buttonPin2 = 31; // the number of the pushbutton pin<br />
const int buttonPin3 = 30; // the number of the pushbutton pin<br />
const int buttonPin4 = 29; // the number of the pushbutton pin<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
<br />
pinMode(buttonPin1, INPUT_PULLUP);<br />
pinMode(buttonPin2, INPUT_PULLUP);<br />
pinMode(buttonPin3, INPUT_PULLUP);<br />
pinMode(buttonPin4, INPUT_PULLUP);<br />
}<br />
<br />
void loop() {<br />
if ( digitalRead(buttonPin1) == LOW ){<br />
Serial.println("1");<br />
}<br />
if ( digitalRead(buttonPin2) == LOW ){<br />
Serial.println("2");<br />
}<br />
if ( digitalRead(buttonPin3) == LOW ){<br />
Serial.println("3");<br />
}<br />
if ( digitalRead(buttonPin4) == LOW ){<br />
Serial.println("4");<br />
}<br />
}<br />
</syntaxhighlight><br />
<br />
Potentiometer<br />
* Potentiometer + Pin to 3.3V<br />
* Potentiometer - Pin to GND<br />
* Potentiometer Data Pin<br />
<br />
OLED Display module <br />
* I2C (Normally a 4.7K pullup resistor is connected between each signal and power, but the weak internal pullup resistors may be sufficient for short wires to a single device.)<br />
** SDA (18, Wire1 17, or 25)<br />
** SCL (19, Wire1 16, or 24)<br />
<br />
Audio Board, I2C<br />
* SDA 18<br />
* SCL 19<br />
<br />
=== Teensy Pins ===<br />
<br />
Teensy 4.1 has a total of 55 input/output signal pins, from which 42 are easily accessible when used with a solderless breadboard. In teensy 4.1, 35 PWM pin support and 18 analog pins are present.<br />
<br />
The pins 23 - 32 and 33 - 42 are easily available.<br />
* The 23 is 3.3V output. The potentiometer's other end should be there.<br />
* Pins A0 - A17 (24, 25, 26, 27 and 38, 39, 40, 41) are analog input pins. See https://www.etechnophiles.com/teensy-4-1-pinout/<br />
<br />
== Teensy 4 Audio Library and Audio Board ==<br />
<br />
=== Audio Board ===<br />
https://www.pjrc.com/store/teensy3_audio.html<br />
<br />
Audio Board is based on the SGTL5000 chip which in addition to ADC/DAC and amplifiers also offers some basic DSP functionality. The Adapter board has line input and output, mic input, and headphone output. Connect to Teensy using very short wires because of high-frequency master clock input (MCLK).<br />
<br />
Audio Board connects to Teensy using 7 signals. The I2C pins SDA and SCL are used to control the chip and adjust parameters. Audio data uses I2S signals. DIN and DOUT and 3 clocks (LRCLK 44.1 kHZ, BCLK 1.41 or 2.82 MHZ and MCLK 11.29 MHz. <br />
<br />
{| class="wikitable"<br />
! Signal<br />
! Rev D, D2 (Teensy 4.x)<br />
! Required For<br />
! Function<br />
|-<br />
| MCLK<br />
| 23 (MCLK1)<br />
| Audio<br />
| Audio Master Clock, 11.29 MHz<br />
|-<br />
| BCLK<br />
| 21 (BCLK1)<br />
| Audio<br />
| Audio Bit Clock, 1.41 or 2.82 MHz<br />
|-<br />
| LRCLK<br />
| 20 (LRCLK1)<br />
| Audio<br />
| Audio Left/Right Clock, 44.1 kHz<br />
|-<br />
| DIN<br />
| 7 (OUT1A)<br />
| Audio Output<br />
| Audio Data from Teensy to Audio Shield. Goes to both headphone jack and Line-Out pins.<br />
|-<br />
| DOUT<br />
| 8 (IN1)<br />
| Audio Input<br />
| Audio Data from Audio Shield to Teensy. Comes from either Microphone or Line-In pins.<br />
|-<br />
| SCL<br />
| 19<br />
| Audio Config<br />
| Control Clock (I2C)<br />
|-<br />
| SDA<br />
| 18<br />
| Audio Config<br />
| Control Data (I2C)<br />
|-<br />
| SCK<br />
| 13<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) Clock<br />
|-<br />
| MISO<br />
| 12<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) from SD/MEM to Teensy<br />
|-<br />
| MOSI<br />
| 11<br />
| Optional Data SD or MEM<br />
| Data Storage (SPI) from Teensy to SD/MEM<br />
|-<br />
| SDCS<br />
| 10<br />
| Optional Data SD Card<br />
| Chip Select (SPI) for SD Card<br />
|-<br />
| MEMCS<br />
| 6<br />
| Optional Data MEM Chip<br />
| Chip Select (SPI) for Memory Chip<br />
|-<br />
| Vol<br />
| 15 / A1<br />
| Optional Knob<br />
| Volume Thumbwheel (analog signal)<br />
|}<br />
<br />
=== Play a sine wave ===<br />
<br />
Test 1, almost from https://gist.github.com/mwicat/4c129fe835d58258688974d5e02ffb75<br />
<syntaxhighlight lang="C"><br />
#include <Audio.h><br />
<br />
AudioSynthWaveformSine sineWave; // Create a sine wave object<br />
AudioOutputAnalog output; // Create an analog output object<br />
AudioConnection patchCord(sineWave, output);<br />
<br />
void setup() {<br />
AudioMemory(8); // Allocate memory for audio processing<br />
sineWave.frequency(440); // Set frequency to 440 Hz (A4)<br />
sineWave.amplitude(0.5); // Set amplitude<br />
}<br />
<br />
void loop() {<br />
// The sine wave will continuously play<br />
}<br />
</syntaxhighlight><br />
<br />
Test2 Sine/Square Wave Generator: https://github.com/jameskeaveney/Teensy-SineWaveGenerator/blob/master/SineGen.ino<br />
<br />
=== Teensy 4 Signal Generator ===<br />
<br />
DDS (Direct Digital Synthesis) For teensy 3.5 https://github.com/EmaMaker/SignalGenerator-Teensy/blob/master/README.md<br />
<br />
Harmonic distortion https://kennypeng.com/2020/11/23/teensy_harmonic_distortion.html https://github.com/colonelwatch/teensy-harmonic-distortion<br />
<br />
Teensy Dynamic Sound Effects Processor https://cdn.hackaday.io/files/1638357009516640/Final%20Project_Complete.pdf<br />
<br />
=== Hackaday tutorial ===<br />
The tutorial: https://hackaday.io/project/8292-microcontroller-audio-workshop-had-supercon-2015 and the pdf file from https://raw.githubusercontent.com/PaulStoffregen/AudioWorkshop2015/master/workshop.pdf<br />
<br />
Playing a file from SD card.<br />
File → Examples → Audio → Tutorial → Part_1_03_Playing_Music. Also available below (slightly modified version) and at https://github.com/PaulStoffregen/Audio/blob/master/examples/WavFilePlayer/WavFilePlayer.ino<br />
* Insert the Micro SD card from the card reader and into the Teensy Audio Shield before you upload the program. The music files are stored on this MicroSD card.<br />
<br />
Three different audio outputs<br />
* AudioOutputI2S audioOutput;<br />
* AudioOutputSPDIF audioOutput;<br />
* AudioOutputAnalog audioOutput;<br />
See the memory function at MemoryAndCpuUsage example<br />
<br />
The <code>patchCord1(playWav1, 0, audioOutput, 0);</code> connects the left output channel (channel 0) of the WAV file player (playWav1) to the left input channel (channel 0) of the audio output (audioOutput).<br />
<br />
<syntaxhighlight lang="C"><br />
#include <Audio.h><br />
#include <Wire.h><br />
#include <SPI.h><br />
#include <SD.h><br />
#include <SerialFlash.h><br />
<br />
AudioPlaySdWav playWav1;<br />
AudioOutputI2S audioOutput;<br />
<br />
AudioConnection patchCord1(playWav1, 0, audioOutput, 0);<br />
AudioConnection patchCord2(playWav1, 1, audioOutput, 1);<br />
AudioControlSGTL5000 sgtl5000_1;<br />
<br />
// Use these with the Teensy Audio Shield<br />
#define SDCARD_CS_PIN 10<br />
#define SDCARD_MOSI_PIN 7 // Teensy 4 ignores this, uses pin 11<br />
#define SDCARD_SCK_PIN 14 // Teensy 4 ignores this, uses pin 13<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
AudioMemory(8);<br />
<br />
sgtl5000_1.enable();<br />
sgtl5000_1.volume(0.5);<br />
<br />
SPI.setMOSI(SDCARD_MOSI_PIN);<br />
SPI.setSCK(SDCARD_SCK_PIN);<br />
if (!(SD.begin(SDCARD_CS_PIN))) {<br />
// stop here, but print a message repetitively<br />
while (1) {<br />
Serial.println("Unable to access the SD card");<br />
delay(500);<br />
}<br />
}<br />
}<br />
<br />
void playFile(const char *filename){<br />
Serial.print("Playing file: ");<br />
Serial.println(filename);<br />
<br />
playWav1.play(filename);<br />
<br />
delay(25); // A brief delay for the library read WAV info<br />
<br />
// Simply wait for the file to finish playing.<br />
while (playWav1.isPlaying()) {<br />
}<br />
}<br />
<br />
<br />
void loop() {<br />
playFile("SDTEST1.WAV"); // filenames are always uppercase 8.3 format<br />
delay(500);<br />
playFile("SDTEST2.WAV");<br />
delay(500);<br />
playFile("SDTEST3.WAV");<br />
delay(500);<br />
playFile("SDTEST4.WAV");<br />
delay(1500);<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
<br />
Blink LED while Playing Music.<br />
File → Examples → Audio → Tutorial → Part_1_04_Blink_While_Playing<br />
<br />
Use eg <br />
<syntaxhighlight lang="C"><br />
elapsedMillis blinkTime;<br />
. . .<br />
if (blinkTime < 250) {<br />
digitalWrite(LED_PIN, LOW);<br />
} else if (blinkTime < 500) {<br />
digitalWrite(LED_PIN, HIGH);<br />
} else {<br />
blinkTime = 0; // start blink cycle over again<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
Do More While Playing Music. <br />
File → Examples → Audio → Tutorial → Part_1_05_Do_More_While_Playing<br />
* The potentiometer controls the volume immediately, regardless of status of the LED. <br />
* The pushbuttons are read using the Bounce library<br />
<br />
=== The GUI ===<br />
<br />
Audio system design GUI https://www.pjrc.com/teensy/gui/ (page 9)<br />
From the main Arduino folder, navigate to these folders hardware / teensy / avr / libraries / Audio / gui. Inside the gui folder, open index.html<br />
<br />
== References ==<br />
<br />
<br />
Teensy / Arduino/ ESP32 based drum machine/ sequencer with high quality samples. Use MIDI to transfer data from sequencer to synth. / Groovebox.<br />
References:<br />
<br />
DIY Arduino Drum Synth + FREE SAMPLES! https://www.youtube.com/watch?v=xo-iN3tfE6o<br />
* Simple, good starting point!<br />
* https://github.com/NickCulbertson/Arduino-Audio-Projects<br />
<br />
https://www.instructables.com/MIDI-Drum-Machine/<br />
<br />
ARDUINO 8 STEP KEYBOARD SEQUENCER FOR SYNTHESIZERS https://www.youtube.com/watch?v=9oGlCfwCoCw<br />
* https://www.lookmumnocomputer.com/projects/#/sequencer-keyboard<br />
* CV patch cables (also called mini-jack patch cables, modular patch cables or Eurorack cables)<br />
<br />
Drum trigger sequencer. How To Make Your Own Drum Sequencer DIY The BIG BUTTON https://www.youtube.com/watch?v=6ArDGcUqiWM<br />
<br />
<br />
<br />
https://diyelectromusic.com/2021/06/23/arduino-mozzi-sample-drum-sequencer/<br />
* <br />
<br />
Doof machine <br />
<br />
https://github.com/gavD/arduino-drum-machine<br />
<br />
<br />
Mozzi https://sensorium.github.io/Mozzi/gallery/<br />
<br />
<br />
The Bastl Microgranny https://www.instructables.com/Microgranny-Sampler-Completely-Home-built-not-a-Ki/<br />
<br />
SnapBeat https://www.hackster.io/hiro-akihabara/snapbeat-the-simple-lo-fi-sampler-5a3222<br />
<br />
https://www.youtube.com/watch?v=U5Q8chfMglE<br />
<br />
https://www.youtube.com/watch?v=YeKsXck8LDY<br />
<br />
NI404 https://www.synthtopia.com/content/2024/01/21/the-ni404-is-an-open-source-diy-hardware-sampler-sequencer/<br />
* TOERN new version https://toern.live/<br />
<br />
MOTHSYNTH https://www.mothsynth.com/<br />
<br />
Samplotron https://hackaday.io/project/205253/components<br />
<br />
Pushpin https://pushpin.kinga.dev/<br />
<br />
Cosmic Loop https://github.com/kreiff/Cosmic_Loop<br />
<br />
OpnBeat https://hackaday.io/project/190273-opnbeat-diy-lo-fi-sampler-with-isd1700-series<br />
<br />
Launchpad https://github.com/pabolojo/DIY-Launchpad<br />
<br />
Yorick https://bristol-communal-modular.github.io/yorick/?utm_source=chatgpt.com<br />
<br />
== Button test ==<br />
<br />
<syntaxhighlight lang="C"><br />
<br />
//LEFT SIDE<br />
const int buttonPin1 = 41; // the number of the pushbutton pin<br />
const int buttonPin2 = 40; // the number of the pushbutton pin<br />
const int buttonPin3 = 39; // the number of the pushbutton pin<br />
const int buttonPin4 = 38; // the number of the pushbutton pin<br />
const int buttonPin5 = 37; // the number of the pushbutton pin<br />
const int buttonPin6 = 36; // the number of the pushbutton pin<br />
const int buttonPin7 = 35; // the number of the pushbutton pin<br />
const int buttonPin8 = 34; // the number of the pushbutton pin<br />
//last is empty<br />
<br />
//RIGHT SIDE<br />
const int potentiometer1 = 24; // ANALOG INPUT<br />
<br />
const int togglePin1 = 25; // the number of the pushbutton pin<br />
const int togglePin2 = 26; // the number of the pushbutton pin<br />
<br />
void setup() {<br />
Serial.begin(9600);<br />
<br />
pinMode(buttonPin1, INPUT_PULLUP);<br />
pinMode(buttonPin2, INPUT_PULLUP);<br />
pinMode(buttonPin3, INPUT_PULLUP);<br />
pinMode(buttonPin4, INPUT_PULLUP);<br />
pinMode(buttonPin5, INPUT_PULLUP);<br />
pinMode(buttonPin6, INPUT_PULLUP);<br />
pinMode(buttonPin7, INPUT_PULLUP);<br />
pinMode(buttonPin8, INPUT_PULLUP);<br />
<br />
pinMode(togglePin1, INPUT_PULLUP);<br />
pinMode(togglePin2, INPUT_PULLUP);<br />
<br />
<br />
}<br />
<br />
int val;<br />
<br />
void loop() {<br />
if ( digitalRead(buttonPin1) == LOW ){<br />
Serial.print("1, ");<br />
}<br />
if ( digitalRead(buttonPin2) == LOW ){<br />
Serial.print("2, ");<br />
}<br />
if ( digitalRead(buttonPin3) == LOW ){<br />
Serial.print("3, " );<br />
}<br />
if ( digitalRead(buttonPin4) == LOW ){<br />
Serial.print("4, " );<br />
}<br />
if ( digitalRead(buttonPin5) == LOW ){<br />
Serial.print("5, ");<br />
}<br />
if ( digitalRead(buttonPin6) == LOW ){<br />
Serial.print("6, ");<br />
}<br />
if ( digitalRead(buttonPin7) == LOW ){<br />
Serial.print("7, ");<br />
}<br />
if ( digitalRead(buttonPin8) == LOW ){<br />
Serial.print("8, ");<br />
}<br />
<br />
if ( digitalRead(togglePin1) == LOW ){<br />
Serial.print("t1, ");<br />
}<br />
if ( digitalRead(togglePin2) == LOW ){<br />
Serial.print("t2, ");<br />
}<br />
<br />
val = analogRead( potentiometer1 );<br />
Serial.println(val);<br />
<br />
}<br />
</syntaxhighlight><br />
<br />
<br />
== 2 ==<br />
<br />
== References ==<br />
<br />
Teensy Best Practices: https://gist.github.com/somebox/d969f8a97e5a4362af5049ed554a9e69</div>Molhttps://wiki.luntti.net/index.php?title=File:Teensy_groovebox1.jpg&diff=16561File:Teensy groovebox1.jpg2026-07-07T12:39:06Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=Pedagogy&diff=16560Pedagogy2026-07-07T12:37:03Z<p>Mol: /* Theories */</p>
<hr />
<div>== Introduction ==<br />
<br />
Some interesting theories about learning.<br />
<br />
See also https://www.allourideas.org/trendiez/results?all=true<br />
<br />
== Theories ==<br />
<br />
* Collaborative learning<br />
* Compulsory learning<br />
* Computational-based learning<br />
* Discovery Learning<br />
* Distance learning<br />
* Inquiry-based learning<br />
* Narrative scenarios<br />
* Problem solving<br />
* Project-based learning<br />
* Scenario-based learning<br />
* Socioscientific Issues-Based Instruction https://serc.carleton.edu/sp/library/issues/what.html<br />
<br />
Roshenshine's Principles, 17 afn 10 in the UNESCO publications? Greg Ashman?<br />
<br />
== Some famous people ==<br />
<br />
* Arving Gupta<br />
* Sugata Mitra <br />
* Papiert<br />
* [https://www.importanceofplay.eu/wp-content/uploads/2019/11/Dr-David-Whitebread-The-importance-of-play-final.pdf Dr David Whitebread]</div>Molhttps://wiki.luntti.net/index.php?title=DIY_Spot_Welding_machine_for_battery_packs&diff=16559DIY Spot Welding machine for battery packs2026-07-07T12:33:32Z<p>Mol: /* Kits */</p>
<hr />
<div>== Introduction ==<br />
<br />
NE555<br />
<br />
Transformer<br />
<br />
<br />
== Theory: NE555 based ==<br />
<br />
=== Idea ===<br />
<br />
The 555 timer circuit controls MOSFETs that deliver short, high-current pulses for welding nickel strips. The 555 shall work in monostable mode. <br />
<br />
The MOSFETs (IRLB4132 or IRF3205) handle the high welding current.<br />
<br />
<br />
=== Kits ===<br />
<br />
'''99 Gears 12V Spot Welder Kit'''<br />
* Problem: Blowing up. <br />
** Not enough amperes from the battery. If not enough current for the mosfets, those will blow.<br />
** Medium (20–40Ah) is the sweet spot<br />
** "The destruction of the MOSFETs is likely to be caused by DROP of the Gate Drive, if the the battery voltage drops. That is where the Cranking Amperes come to play. If the weld location resistance is very low, with near zero drop there, more of the drop happens inside the battery and in general before the point where the gate drive voltage is picked." <br />
** Nickel thickness of 0.1 - 0.2 mm: 120 - 180 Amps.<br />
* Problem: Welding takes a lot of practice.<br />
** Resistance is the key. Push just hard enough to get a contact, and not with perpendicular probes.<br />
* Number of mosfets: 2 or 4 (4 MOSFETs: Generally better, since the current is shared among more devices)? Also the markings on the mosfet. <br />
<br />
Connect battery → almost short circuit → let physics decide the current”. The current is roughly<br />
<br />
<math><br />
I = \frac{U}{ R_\text{internal} + R_\text{wires} + R_\text{contact}}<br />
</math><br />
<br />
Thus <br />
* Lower resistance: massive current spike<br />
* Higher resistance: weak weld<br />
* High CCA (cranking current): low internal resistance → higher weld current<br />
and bigger batteries usually have lower internal resistance.<br />
<br />
<br />
A big car battery has very low internal resistance (~milliohms) and can deliver 1000+ amps instantly. My welder's cheap electronics and limited current handling causes that current spike exceeds MOSFET limits and they fail explosively.<br />
<br />
The 12 V AGM motorcycle battery (18 Ah, 310 CCA) is much more likely to be too weak. It works reasonably well on 0.1 mm nickel, struggles on 0.15 mm nickel but may not reliably weld 0.2 mm nickel.<br />
<br />
=== References ===<br />
<br />
Some references related to 555 based<br />
<br />
https://hackaday.io/project/204777-diy-battery-spot-welder-build-your-own-power-pack/details<br />
<br />
https://www.instructables.com/DIY-Battery-Spot-Welder-Build-Your-Own-Power-Pack-/<br />
<br />
pcbway.com/project/shareproject/<br />
<br />
== Theory: Transformer based ==</div>Molhttps://wiki.luntti.net/index.php?title=DIY_Spot_Welding_machine_for_battery_packs&diff=16558DIY Spot Welding machine for battery packs2026-07-07T12:32:17Z<p>Mol: /* Kits */</p>
<hr />
<div>== Introduction ==<br />
<br />
NE555<br />
<br />
Transformer<br />
<br />
<br />
== Theory: NE555 based ==<br />
<br />
=== Idea ===<br />
<br />
The 555 timer circuit controls MOSFETs that deliver short, high-current pulses for welding nickel strips. The 555 shall work in monostable mode. <br />
<br />
The MOSFETs (IRLB4132 or IRF3205) handle the high welding current.<br />
<br />
<br />
=== Kits ===<br />
<br />
'''99 Gears 12V Spot Welder Kit'''<br />
* Problem: Blowing up. <br />
** Not enough amperes from the battery. If not enough current for the mosfets, those will blow.<br />
** Medium (20–40Ah) is the sweet spot<br />
** "The destruction of the MOSFETs is likely to be caused by DROP of the Gate Drive, if the the battery voltage drops. That is where the Cranking Amperes come to play. If the weld location resistance is very low, with near zero drop there, more of the drop happens inside the battery and in general before the point where the gate drive voltage is picked." <br />
** Nickel thickness of 0.1 - 0.2 mm: 120 - 180 Amps.<br />
* Problem: Welding takes a lot of practice.<br />
** Resistance is the key. Push just hard enough to get a contact, and not with perpendicular probes.<br />
* Number of mosfets: 2 or 4?<br />
<br />
Connect battery → almost short circuit → let physics decide the current”. The current is roughly<br />
<br />
<math><br />
I = \frac{U}{ R_\text{internal} + R_\text{wires} + R_\text{contact}}<br />
</math><br />
<br />
Thus <br />
* Lower resistance: massive current spike<br />
* Higher resistance: weak weld<br />
* High CCA (cranking current): low internal resistance → higher weld current<br />
and bigger batteries usually have lower internal resistance.<br />
<br />
<br />
A big car battery has very low internal resistance (~milliohms) and can deliver 1000+ amps instantly. My welder's cheap electronics and limited current handling causes that current spike exceeds MOSFET limits and they fail explosively.<br />
<br />
The 12 V AGM motorcycle battery (18 Ah, 310 CCA) is much more likely to be too weak. It works reasonably well on 0.1 mm nickel, struggles on 0.15 mm nickel but may not reliably weld 0.2 mm nickel.<br />
<br />
=== References ===<br />
<br />
Some references related to 555 based<br />
<br />
https://hackaday.io/project/204777-diy-battery-spot-welder-build-your-own-power-pack/details<br />
<br />
https://www.instructables.com/DIY-Battery-Spot-Welder-Build-Your-Own-Power-Pack-/<br />
<br />
pcbway.com/project/shareproject/<br />
<br />
== Theory: Transformer based ==</div>Molhttps://wiki.luntti.net/index.php?title=Create_references_and_citations_database_in_Linux&diff=16557Create references and citations database in Linux2026-07-06T16:33:41Z<p>Mol: /* Introduction */</p>
<hr />
<div>== Introduction ==<br />
<br />
# Zotero + Better Notes<br />
# Obsidian + Zotero Integration<br />
# Logseq<br />
# Connected Papers<br />
# ResearchRabbit<br />
# Litmaps<br />
# JabRef (markdown)<br />
<br />
Myös<br />
#Neo4j<br />
#Memgraph<br />
#Kùzu<br />
<br />
#Zettlr<br />
<br />
#GROBID</div>Molhttps://wiki.luntti.net/index.php?title=Create_references_and_citations_database_in_Linux&diff=16556Create references and citations database in Linux2026-07-06T16:33:08Z<p>Mol: Created page with "== Introduction == # Zotero + Better Notes # Obsidian + Zotero Integration # Logseq # Connected Papers # ResearchRabbit # Litmaps # JabRef (markdown) Myös #Neo4j #Memgraph #Kùzu #Zettlr"</p>
<hr />
<div>== Introduction ==<br />
<br />
# Zotero + Better Notes<br />
# Obsidian + Zotero Integration<br />
# Logseq<br />
# Connected Papers<br />
# ResearchRabbit<br />
# Litmaps<br />
# JabRef (markdown)<br />
<br />
Myös<br />
#Neo4j<br />
#Memgraph<br />
#Kùzu<br />
<br />
#Zettlr</div>Molhttps://wiki.luntti.net/index.php?title=File:Ukonkello3.jpg&diff=16555File:Ukonkello3.jpg2026-07-06T16:02:45Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=T-majan_kasvit&diff=16554T-majan kasvit2026-07-06T15:56:17Z<p>Mol: /* Johdanto */</p>
<hr />
<div>== Johdanto ==<br />
<br />
Huom! Erheitä luultavasti on. <br />
<br />
<gallery><br />
Peurankello1.jpg| Peurankello<br />
Peurankello2.jpg| Peurankello<br />
Peurankello3.jpg| Peurankello<br />
Kaunokainen1.jpg| Kaunokainen<br />
Kaunokainen2.jpg| Kaunokainen<br />
Kaunokainen3.jpg| Kaunokainen<br />
Kaunokainen4.jpg| Kaunokainen<br />
Pensasangervo1.jpg| Pensasangervo<br />
Pensasangervo2.jpg| Pensasangervo<br />
Pensasangervo3.jpg| Pensasangervo<br />
Pensasangervo4.jpg| Pensasangervo<br />
Pensasangervo5.jpg| Pensasangervo<br />
Pensasangervo6.jpg| Pensasangervo<br />
Nurmitädyke1.jpg| Nurmitädyke<br />
Nurmitädyke2.jpg| Nurmitädyke<br />
Nurmitädyke3.jpg| Nurmitädyke<br />
Nurmitädyke4.jpg| Nurmitädyke<br />
Nurmitädyke5.jpg| Nurmitädyke<br />
Harjaneilikka1.jpg| Harjaneilikka<br />
Harjaneilikka2.jpg| Harjaneilikka<br />
Harjaneilikka3.jpg| Harjaneilikka<br />
Harjaneilikka4.jpg| Harjaneilikka<br />
Harjaneilikka5.jpg| Harjaneilikka<br />
Varjolilja1.jpg| Varjolilja<br />
Varjolilja2.jpg| Varjolilja<br />
Varjolilja3.jpg| Varjolilja<br />
Varjolilja4.jpg| Varjolilja<br />
Mukulaleinikki1.jpg| Mukulaleinikki<br />
Mukulaleinikki2.jpg| Mukulaleinikki<br />
Mukulaleinikki3.jpg| Mukulaleinikki<br />
Mukulaleinikki4.jpg| Mukulaleinikki<br />
Mukulaleinikki5.jpg| Mukulaleinikki<br />
Mukulaleinikki6.jpg| Mukulaleinikki<br />
Piparjuuri1.jpg| Piparjuuri<br />
Piparjuuri2.jpg| Piparjuuri<br />
Piparjuuri3.jpg| Piparjuuri<br />
Piparjuuri4.jpg| Piparjuuri<br />
Ukonkello1.jpg| Ukonkello<br />
Ukonkello2.jpg| Ukonkello<br />
Ukonkello3.jpg| Ukonkello<br />
</gallery><br />
<br />
<br />
Joitain kasveja teemajalta. <br />
<br />
{| class="wikitable sortable"<br />
! Kasvi (tieteellinen nimi)<br />
! Luonnonvarainen / istutettu<br />
! Syötävyys / mauste / myrkyllisyys<br />
! Kasvupaikka<br />
! Kukinta<br />
! Leviäminen<br />
! Valo<br />
! Maaperä<br />
! Pölyttäjäystävällisyys<br />
! Korkeus<br />
|-<br />
| '''Peurankello''' (''Campanula glomerata'')<br />
| Luonnonvarainen, myös viljellään<br />
| Ei yleisessä ravintokäytössä, ei merkittävästi myrkyllinen<br />
| Niitty, keto, tienpientareet<br />
| Kesä–heinäkuu<br />
| Siemenet, lyhyt juurakko<br />
| Aurinko–puolivarjo<br />
| Kuiva–tuore, niukkaravinteinen<br />
| ★★★★★ Erinomainen mesikasvi mehiläisille ja kimalaisille<br />
| 20–60 cm<br />
|-<br />
| '''Kaunokainen''' (''Bellis perennis'')<br />
| Luonnonvarainen, myös viljelty<br />
| Kukat ja lehdet syötäviä<br />
| Nurmi, pihat, niityt<br />
| Touko–syyskuu<br />
| Siemenet<br />
| Aurinko–puolivarjo<br />
| Tuore, melko ravinteikas<br />
| ★★★★☆ Houkuttelee mehiläisiä ja kärpäsiä<br />
| 5–20 cm<br />
|-<br />
| '''Pensasangervo''' (''Spiraea'' spp.)<br />
| Istutettu<br />
| Ei ravintokäyttöä<br />
| Pensasistutukset, puistot<br />
| Kesä–heinäkuu<br />
| Juurivesat, pistokkaat<br />
| Aurinko–puolivarjo<br />
| Tuore, ravinteikas<br />
| ★★★★☆ Runsaasti mettä pölyttäjille<br />
| 1–2 m<br />
|-<br />
| '''Nurmitädyke''' (''Veronica chamaedrys'')<br />
| Luonnonvarainen<br />
| Ei yleistä ravintokäyttöä<br />
| Nurmet, niityt, metsänreunat<br />
| Touko–kesäkuu<br />
| Siemenet, rönsyt<br />
| Aurinko–puolivarjo<br />
| Tuore, melko ravinteikas<br />
| ★★★★☆ Tärkeä keväinen mesikasvi<br />
| 10–30 cm<br />
|-<br />
| '''Harjaneilikka''' (''Dianthus barbatus'')<br />
| Istutettu, joskus villiintyy<br />
| Kukkia voi käyttää koristeena, ei varsinainen ravintokasvi<br />
| Kukkapenkit, perennat<br />
| Kesä–heinäkuu<br />
| Siemenet<br />
| Aurinko<br />
| Läpäisevä, melko kuiva<br />
| ★★★★★ Perhosten ja mehiläisten suosikki<br />
| 30–60 cm<br />
|-<br />
| '''Varjolilja''' (''Lilium martagon'')<br />
| Luonnonvarainen Ahvenanmaalla, muualla yleensä istutettu<br />
| Sipuli syötävä kypsennettynä; erittäin myrkyllinen kissoille<br />
| Lehdot, puutarhat<br />
| Kesä–heinäkuu<br />
| Siemenet, sivusipulit<br />
| Puolivarjo–varjo<br />
| Tuore, runsasmultainen<br />
| ★★★★☆ Houkuttelee erityisesti perhosia<br />
| 60–120 cm<br />
|-<br />
| '''Mukulaleinikki''' (''Ficaria verna'')<br />
| Luonnonvarainen<br />
| Tuoreena lievästi myrkyllinen; ei ravinnoksi<br />
| Lehdot, puronvarret<br />
| Huhti–toukokuu<br />
| Mukulat, itusilmut<br />
| Puolivarjo–varjo<br />
| Kostea, ravinteikas<br />
| ★★★☆☆ Kevään varhainen siitepölylähde<br />
| 5–20 cm<br />
|-<br />
| '''Piparjuuri''' (''Armoracia rusticana'')<br />
| Viljelty, paikoin villiintynyt<br />
| Juuri syötävä, maustekasvi<br />
| Viljelymaa, pihat<br />
| Kesä–heinäkuu<br />
| Juuripalat<br />
| Aurinko–puolivarjo<br />
| Syvä, ravinteikas, tuore<br />
| ★★★☆☆ Kukat houkuttelevat pölyttäjiä<br />
| 50–100 cm<br />
|-<br />
| '''Ukonkello''' (''Campanula latifolia'')<br />
| Luonnonvarainen<br />
| Ei yleisessä ravintokäytössä<br />
| Lehdot, puronvarret<br />
| Heinä–elokuu<br />
| Siemenet<br />
| Puolivarjo<br />
| Tuore, runsasravinteinen<br />
| ★★★★★ Erinomainen kimalais- ja mehiläiskasvi<br />
| 60–120 cm<br />
|}</div>Molhttps://wiki.luntti.net/index.php?title=T-majan_kasvit&diff=16553T-majan kasvit2026-07-06T15:49:32Z<p>Mol: /* Johdanto */</p>
<hr />
<div>== Johdanto ==<br />
<br />
Huom! Erheitä luultavasti on. <br />
<br />
<gallery><br />
Peurankello1.jpg| Peurankello<br />
Peurankello2.jpg| Peurankello<br />
Peurankello3.jpg| Peurankello<br />
Kaunokainen1.jpg| Kaunokainen<br />
Kaunokainen2.jpg| Kaunokainen<br />
Kaunokainen3.jpg| Kaunokainen<br />
Kaunokainen4.jpg| Kaunokainen<br />
Pensasangervo1.jpg| Pensasangervo<br />
Pensasangervo2.jpg| Pensasangervo<br />
Pensasangervo3.jpg| Pensasangervo<br />
Pensasangervo4.jpg| Pensasangervo<br />
Pensasangervo5.jpg| Pensasangervo<br />
Pensasangervo6.jpg| Pensasangervo<br />
Nurmitädyke1.jpg| Nurmitädyke<br />
Nurmitädyke2.jpg| Nurmitädyke<br />
Nurmitädyke3.jpg| Nurmitädyke<br />
Nurmitädyke4.jpg| Nurmitädyke<br />
Nurmitädyke5.jpg| Nurmitädyke<br />
Harjaneilikka1.jpg| Harjaneilikka<br />
Harjaneilikka2.jpg| Harjaneilikka<br />
Harjaneilikka3.jpg| Harjaneilikka<br />
Harjaneilikka4.jpg| Harjaneilikka<br />
Harjaneilikka5.jpg| Harjaneilikka<br />
Varjolilja1.jpg| Varjolilja<br />
Varjolilja2.jpg| Varjolilja<br />
Varjolilja3.jpg| Varjolilja<br />
Varjolilja4.jpg| Varjolilja<br />
Mukulaleinikki1.jpg| Mukulaleinikki<br />
Mukulaleinikki2.jpg| Mukulaleinikki<br />
Mukulaleinikki3.jpg| Mukulaleinikki<br />
Mukulaleinikki4.jpg| Mukulaleinikki<br />
Mukulaleinikki5.jpg| Mukulaleinikki<br />
Mukulaleinikki6.jpg| Mukulaleinikki<br />
Piparjuuri1.jpg| Piparjuuri<br />
Piparjuuri2.jpg| Piparjuuri<br />
Piparjuuri3.jpg| Piparjuuri<br />
Piparjuuri4.jpg| Piparjuuri<br />
Ukonkello1.jpg| Ukonkello<br />
Ukonkello2.jpg| Ukonkello<br />
Ukonkello3.jpg| Ukonkello<br />
</gallery><br />
<br />
<br />
Joitain kasveja teemajalta. <br />
<br />
Peurankello, monivuotinen ruoho<br />
<br />
Kaunokainen<br />
<br />
Pensasangervo<br />
<br />
Nurmitädyke<br />
<br />
Harjaneilikka<br />
<br />
Varjolilja<br />
<br />
Mukulaleinikki<br />
<br />
Piparjuuri<br />
<br />
Ukonkello</div>Molhttps://wiki.luntti.net/index.php?title=File:Ukonkello2.jpg&diff=16552File:Ukonkello2.jpg2026-07-06T15:48:20Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Ukonkello1.jpg&diff=16551File:Ukonkello1.jpg2026-07-06T15:47:57Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Piparjuuri4.jpg&diff=16550File:Piparjuuri4.jpg2026-07-06T15:46:19Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Piparjuuri3.jpg&diff=16549File:Piparjuuri3.jpg2026-07-06T15:44:32Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Piparjuuri2.jpg&diff=16548File:Piparjuuri2.jpg2026-07-06T15:43:53Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Piparjuuri1.jpg&diff=16547File:Piparjuuri1.jpg2026-07-06T15:43:20Z<p>Mol: </p>
<hr />
<div></div>Molhttps://wiki.luntti.net/index.php?title=File:Mukulaleinikki2.jpg&diff=16546File:Mukulaleinikki2.jpg2026-07-06T15:42:44Z<p>Mol: </p>
<hr />
<div></div>Mol