The Effect of Interactive Computer Animation and Simulation on Students’ Achievement and Motivation in Learning Electrochemistry

Abstract

Electrochemistry is difficult to learn due to its abstract concepts involving macroscopic, microscopic, and symbolic representation levels. Studies have shown that students can visualize and improve their understanding of chemistry by using interactive computer animation and simulation. This study reports the effect of interactive computer animation and simulation module named “Interactive Electrolysis of Aqueous Solution” (IEAS) developed to aid students in learning electrolysis. A pre and post-test control quasi-experimental design was carried out to investigate the effects of the IEAS on students’ achievement and motivation in electrochemistry topics. This study involved 62 16-years-old male students from two different secondary schools. Pre and post electrochemistry achievement tests (EAT) and pre and post- Instructional Material Motivation Surveys (IMMS) were used. For EAT, using one-way ANOVA, it shows that there was a significant difference in the post-test mean score in this study on the understanding of the electrolysis concept between students in the treatment and control groups [F (1, 60) = 5.15, p <0.05]. The qualitative results also provided evidence that the students in the treatment group had a better conceptual understanding than the control group, especially at the microscopic representation level. For the IMMS test, there was a significant difference between the treatment and control groups in terms of the mean score of the post motivation IMMS test where p <0.05 in chemistry learning [F (1,59) = 266.89, p <0.05]. Thus, it can be concluded that IEAS has an impact on enhancing the students’ understanding of the electrolysis concept, and the students are more motivated to learn electrochemistry.

Effect of Using Physics Education Technology (PhET) Simulation Media to Enhance Students’ Motivation and Problem-Solving Skills in Learning Physics

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Music aesthetic teaching and emotional visualization under emotional teaching theory and deep learning

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