Integrating Semantic Web and AI in Informatics Education to Enhance Digital Information Evaluation Skills

Kurniawan, Sena
Sarah, Yuni Siti

Journal of Sustainable Innovation Engineering
Vol. 1 No. 2 (2025): July

The ability to critically evaluate digital information is a vital skill for students in an era of information overload and misinformation. This study aims to examine the effectiveness of integrating Semantic Web and Artificial Intelligence (AI) technologies in Informatics learning to enhance high school students' information evaluation skills. A quasi-experimental method was employed using a pretest-posttest control group design with two 11th-grade classes (30 students each). The intervention utilized Google Knowledge Graph and ChatGPT, with evaluations conducted via practical tests, digital literacy rubrics, and student perception questionnaires. Results revealed a statistically significant improvement in the experimental group’s evaluation scores (p < 0.01), particularly in accuracy and analytical depth. Students responded positively to semantic tools, although some reported difficulties understanding complex AI-generated content. The study concludes that Semantic Web and AI integration can serve as an effective pedagogical strategy in Informatics learning, provided there is adequate infrastructure and active teacher support as facilitators.