Pengaruh Artificial Intelligence sebagai Tutor Virtual terhadap Motivasi dan Student Engagement Siswa: Tinjauan Systematic Literature Review

Salwa Martasya, Santy Aulia

Abstract


The rapid adoption of artificial intelligence (AI) and generative AI (GenAI) in higher education underscores the need for a synthesis of empirical evidence to support evidence-based implementation. This study aims to analyze the characteristics, effectiveness, and factors influencing the application of AI on student learning, motivation, and engagement. The study employed a Systematic Literature Review (SLR) method on four articles retrieved from Scopus, Web of Science, and ScienceDirect, using the following criteria: publications from 2016 to 2026, a focus on AI in higher education, and the presentation of empirical evidence or methodological synthesis. The results of the review indicate that AI consistently improves students’ academic performance, motivation, and cognitive, emotional, and agentic engagement. However, its effectiveness is influenced by the field of study, learning strategies, and the type of AI platform used. Therefore, the implementation of AI requires the support of a clear pedagogical and ethical framework, accompanied by AI governance policies, the promotion of AI literacy, and adaptive learning design so that the benefits of AI can be sustainably optimized.

Keywords


Artificial Intelligence (AI); Higher Education; Motivation to Learn; Student Engagement; Systematic Literature Review.

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References


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