Integrating Semiconductor Theory and Computational Practice Through Google Colab-Based Simulation of Diode Characteristics
DOI:
10.29303/jpft.v12i2.12554Published:
2026-10-19Downloads
Abstract
Teaching the effects of temperature on diode characteristics remains challenging, particularly in laboratory activities that require specialized equipment with considerable acquisition and maintenance costs. This study aims to integrate semiconductor theory and computational practice through the development and implementation of Google Colab-based simulations of diode characteristics. The study employed an Educational Design Research (EDR) approach combined with a quasi-experimental non-equivalent control group design. It was conducted at SMA Negeri 6 Yogyakarta, involving 63 twelfth-grade students from two science classes (XII MIPA 2 and XII MIPA 3). The simulation model was evaluated against experimental data, yielding an average Mean Absolute Percentage Error (MAPE) of 2.705% and a Root Mean Square Error (RMSE) of 0.88 mA, indicating relatively small discrepancies between the simulated and experimental results. Regarding learning outcomes, the experimental group demonstrated an increase in mean scores from 46.82 to 84.76, while the control group improved from 45.97 to 67.92. The normalized gain (N-gain) was 0.71 (high category) for the experimental group and 0.41 (medium category) for the control group. These findings suggest that Google Colab-based simulations can support improvements in students' conceptual understanding and computational thinking skills. The developed simulation therefore offers an alternative approach to integrating theoretical and computational learning in semiconductor physics.
Keywords:
Integration of Semiconductor Computational Practice Diode Characteristics SimulationReferences
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