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Christina Areizaga Barbieri; Brianna L. Devlin – Journal of Computer Assisted Learning, 2024
Background: Providing students with worked out problem solutions is a beneficial instructional technique in STEM disciplines, and studying examples that have been worked out incorrectly may be especially helpful for reducing misconceptions in students with low prior content knowledge. However, past results are inconclusive and the effects of…
Descriptors: STEM Education, Misconceptions, Fractions, Error Patterns
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Papadopoulos, Pantelis M.; Natsis, Antonis; Obwegeser, Nikolaus; Weinberger, Armin – Journal of Computer Assisted Learning, 2019
The aim of the present study (n = 113) was to examine how (objective and subjective) information on peers' preparation, confidence, and past performance can support students in answering correctly in audience response systems (aka clickers). The result analysis shows that in the "challenging" questions, in which answers diverged,…
Descriptors: Feedback (Response), Audience Response Systems, Self Esteem, Student Attitudes
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Niedderer, H.; And Others – Journal of Computer Assisted Learning, 1991
Described is how an iconic model building software can be used to help students gain a deeper qualitative conceptual understanding of physics concepts. The program, STELLA, links research about misconceptions and new teaching strategies with the use of modern information technology tools. (31 references) (KR)
Descriptors: Computer Assisted Instruction, Concept Formation, Learning Strategies, Misconceptions
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Brna, P. – Journal of Computer Assisted Learning, 1991
A methodology for confronting students with the inconsistencies entailed by their own beliefs is outlined. This methodology is illustrated using the dynamics domain of physics and a computer modeling program, DYNALAB. (KR)
Descriptors: Case Studies, Cognitive Development, Computer Assisted Instruction, Concept Formation
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Li, S. C.; Law, N.; Lui, K. F. A. – Journal of Computer Assisted Learning, 2006
While simulations have widely been used to facilitate conceptual change in learning science, results indicate that significant disparity or gap between students' prior conceptions and scientific conceptions still exists. To bridge the gap, we argue that the applications of computer simulation in science education should be broadened to enable…
Descriptors: Computer Simulation, Science Education, Concept Formation, Models