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Session:
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PER: Examining Content Understanding and Reasoning
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Paper Type:
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Contributed
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Title:
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Educational Data Mining: Results from in Vivo Experiments to Teach Different Physics Topics
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Meeting:
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2014 Summer Meeting: Minneapolis, Minnesota |
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Location:
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N/A |
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Date:
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Time:
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2:50PM
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Author:
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DANIEL SANCHEZ-GUZMAN
CICATA - Legaria, Instituto Politécnico Nacional
+525557296000X67733, dsanchezgzm@gmail.com
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Co-Author(s):
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ALEJANDRO BALLESTEROS-ROMAN
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Abstract:
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Educational Data Mining (EDM) uses different algorithms for analyze response and behavior in the teaching-learning process, these algorithms let researches to analyze and classify students' behavior or state of knowledge from different concepts; most of these algorithms have not been tested in Physics Education Research, this work presents the results obtained from applying three algorithms used by EDM for teaching different physics concepts applied to in-vivo experiments. These algorithms are: decision tree, rule induction, and fuzzy rule induction. The in-vivo experiments correspond to different active learning methodologies derived from research master degree thesis in the Physics Education Research Department from the Applied Science and Advance Technology Research Center of the National Polytechnic Institute in Mexico.
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Footnotes:
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None
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Presentation:
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Guzmán-Presentation-AAPT-SM-2014-30-07-2014.pdf
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