Riko Oktiyalten
Faculty of Language and Arts, Universitas Negeri Padang, Padang, Indonesia

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Integration of Artificial Intelligence in Problem-based Learning Models: Its Impact on Explanatory Writing Skills and the Interaction with Reading Interest Riko Oktiyalten; Abdurahman Abdurahman
Jurnal Edutech Undiksha Vol. 13 No. 2 (2025): December
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jeu.v13i2.102231

Abstract

The research questions in this study cover three aspects, namely whether the Artificial Intelligence-based Problem-based Learning model affects students' explanatory writing skills, whether reading interest also influences these skills, and whether there is an interaction between the two. Accordingly, this study aims to analyse the effect of AI-based Problem-based Learning on explanatory writing skills, evaluate the effect of reading interest, and examine the possibility of interaction between the two. The background of this study is based on the importance of explanatory writing skills as part of 21st-century literacy and the potential of AI in supporting adaptive and contextual learning. The research method used an experiment with a 2x2 factorial design involving 60 eighth-grade students. The experimental group received AI-based Problem-based Learning, while the control group followed the conventional model. The instruments used were an explanatory writing test and a reading interest questionnaire. The results of the analysis showed that the AI-based Problem-based Learning model had a significant effect on improving explanatory writing skills (tcount 7.537 > ttable 1.672; Sig. 0.000 < 0.05). Reading interest also had an effect, but no significant interaction was found (p = 0.573 > 0.05). Thus, the effectiveness of AI-based PBL applies regardless of reading interest levels.