Computational Physics Education through AI-Assisted Media: Improving Pascal Programming Skills for Sixth-Semester Physics Education Students at PMIPA FKIP UNRAM
DOI:
10.29303/jcar.v6i2.8225Published:
2024-05-30Downloads
Abstract
This study investigates the integration of AI-assisted media to enhance Pascal programming skills among sixth-semester Physics Education students at PMIPA FKIP UNRAM within the domain of computational physics education. Utilizing a classroom action research methodology over two cycles, the intervention employed AI-powered programming assistants and interactive platforms to enhance students' comprehension and application of Pascal programming. Initial findings from Cycle 1 highlighted ongoing challenges despite technological integration, with a mean score of 61.13 (SD=6.67). However, refinements in AI-assisted feedback and practice activities during Cycle 2 resulted in a significant improvement in mean scores to 78.06 (SD=7.6), accompanied by a substantial normalized gain (mean=0.4423, SD=0.1265). Detailed median analyses from Mood’s Median Test for Cycle 2 further underscored improvements across various score ranges, with an overall median of 60.0 indicating enhanced student performance. These results underscore the transformative potential of AI-assisted educational interventions in advancing Pascal programming skills and enriching computational physics education at PMIPA FKIP UNRAM.
Keywords:
AI-Assisted Media, Classroom Action Research, Computational Physics Education, Pascal Programming Skills, PMIPA FKIP UNRAM.References
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