Maker Lab Assignment: Semi-structured_Experiments
Before the Maker Lab students begin the open inquiry phases, they first learn and practice some important skills, supported by small assignments.
This assignment is a "structured", or "guided" inquiry, where students know ahead of time the result they should find, but have agency in their experimental design, within some prescribed limits. By assigning all teams different methods for addressing a single research question (currently: estimating the acceleration due to gravity), they are encouraged to reflect upon how experimental design and equipment limits the certainty of empirical findings.
This assignment requires teams of four students (organized into two pairs, each performing the experiment separately, but analyzing data and reporting on conclusions together). In two weeks (wherein students' course workload is 10 hours per week), the teams must set up experiments, controlling sensors with self-programmed Arduinos, collect and analyze experimental data, and create a pre-recorded video presentation to be viewed in class and aimed at their peers, followed by a Q&A.
Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality.
Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324
Contents:
- partial experimental instructions (for students) in Jupyter Notebook: Semi-structured_Experiments.ipynb (and .pdf )
- grading form for pre-recorded video presentation (both .docx and .pdf )
Licence: Creative Commons Attribution Non Commercial Share Alike 4.0 International
Keywords: science communication, research skills, uncertainty analysis, Jupyter Notebook, data analysis, Python programming, maker education, science lab education, challenge-based learning, inquiry-based learning, nature of science, experimental design
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