The Effectiveness of Deep Learning Assisted by PhET Simulation on Students’ Probabilistic Reasoning Skills
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Abstract
This study aims to test the effectiveness of deep learning assisted by PhET simulation on students' probabilistic reasoning skills. This research design uses a one-group pretest-posttest design. This study took population of mathematics education students who took the probability theory course in the 2025/2026 academic year. The instrument in this study is a probabilistic reasoning test. Data were analyzed using a paired samples t-test, and Cohens' d effect size. The result of the paired samples t-test (t = -3.53; p = 0.002) show that the pretest and posttest have a significant difference. The effect size value of -0.680 is in the medium category, which shows that deep learning assisted by PhET simulation has a considerable impact on probabilistic reasoning skills. The results show that deep learning is able to encourage students to explore, reflect, and construct probability concepts.
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