Enhancing Students' Computational Thinking through IoT Stater Kits: A Quasi Experimental Study Using a Pretest-Posttest Control Group Design
Enhancing Students' Computational Thinking through IoT Stater Kits: A Quasi Experimental Study Using a Pretest-Posttest Control Group Design

Summary/Abstract: This study aims to evaluate the effectiveness of integrating the IoT Starter Kit (SKIOT) into Project-Based Learning (PBL) in order to improve the Computational Thinking (CT) skills of vocational high school students. A quasi-experimental pretest-posttest control-group design was used, involving 30 eleventh-graders. The CT instrument, which includes abstraction, decomposition, algorithmic thinking, evaluation, and generalization, has been validated and demonstrates high reliability. Data were analyzed using normality tests, homogeneity tests, and N-gain analysis. The findings revealed that the experimental group achieved high N-gain (0.7), while the control group achieved moderate N-gain (0.5). These results show that SKIOT-supported PBL is more effective than conventional instruction in improving students’ CT competencies in vocational education.

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