Exploring Undergraduate Students' Computational Modeling Abilities and Conceptual Understanding of Electric Circuits
Por:
Ortega-Alvarez J.D., Sanchez W., Magana A.J.
Publicada:
1 ago 2018
Ahead of Print:
1 ene 2018
Resumen:
Contribution: This paper adds to existing literature on teaching basic concepts of electricity using computer-based instruction; findings suggest that students can develop an accurate understanding of electric circuits when they generate multiple and complementary representations that build toward computational models. Background: Several studies have explored the efficacy of computer-based, multi-representational teaching of electric circuits for novice learners. Existing research has found that instructional use of computational models that move from abstract to concrete representations can foster students' comprehension of electric circuit concepts, but other features of effective instruction using computational models need further investigation. Research Questions: 1) Is there a correlation between students' representational fluency and their ability to reason qualitatively on electric circuits? and 2) Is the quality of student-generated computational representations correlated to their conceptual understanding of electric circuits? Methodology: The study comprised two cases in which 51 sophomore-engineering students completed a voluntary assignment designed to assess their representational fluency and conceptual understanding of electric circuits. Qualitative insights from the first case informed the design of a scoring rubric that served as both the assessment and the data collection instrument. Findings: The results suggest that a multi-representational approach aimed at the construction of computational models can foster conceptual understanding of electric circuits. The number and quality of students' representations showed a positive correlation with their conceptual understanding. In particular, the quality of the computational representations was found to be highly, and significantly, correlated with the correctness of students' answers to qualitative reasoning questions. © 1963-2012 IEEE.
Filiaciones:
Ortega-Alvarez J.D.:
Process Engineering Department, Universidad EAFIT, Medellí
Sanchez W.:
Polytechnic Institute, Purdue University, West Lafayette, IN 47906 USA
Magana A.J.:
Polytechnic Institute, Purdue University, West Lafayette, IN 47906 USA
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