info:eu-repo/semantics/article
Exploring Undergraduate Students' Computational Modeling Abilities and Conceptual Understanding of Electric Circuits
Fecha
2018-08-01Registro en:
00189359
15579638
WOS;000440784100006
SCOPUS;2-s2.0-85045726787
10.1109/TE.2018.2822245
Autor
Ortega-Alvarez J.D.
Sanchez W.
Magana A.J.
Institución
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.
Materias
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Large-scale IoT network offloading to cloud and fog computing : A fluid limit model
Belcredi, Gonzalo; Aspirot, Laura; Monzón, Pablo; Belzarena, Pablo (IEEE, 2021)This paper models a large-scale Internet of Things (IoT) network as a stochastic system that offloads computing towards Fog and Cloud via a shared access medium. The analysis of this large IoT system by stochastic methods ... -
Da modelagem de plantas a dinamica de multidões : um modelo de animação comportamental bio-inspirado
Bicho, Alessandro de Lima -
Molecular modeling databases: A new way in the search of protein targets for drug development
da Silveira, Nelson José Freitas; Bonalumi, Carlos Eduardo; Arcuri, Helen Andrade; de Azevedo Jr., Walter Filgueira