Pengaruh Artificial Intelligence terhadap Motivasi Belajar Mahasiswa: Analisis Data Sekunder

Abstract

This study analyzes the influence of Artificial Intelligence (AI) on students’ learning motivation, focusing on both its transformative potential and its challenges. Using secondary data from national and international journals published between 2024–2025, this research examines how AI affects intrinsic motivation, student engagement, and the development of self-efficacy. The analysis applies Keller’s ARCS model—Attention, Relevance, Confidence, and Satisfaction—as a primary framework, complemented by the Self-Determination Theory (SDT), to evaluate motivational factors influenced by AI. Findings reveal that over 80% of students have used AI tools in their studies, leading to higher engagement, self-confidence (competence), and learning satisfaction. AI’s personalization features particularly strengthen the needs for autonomy and competence in learning. However, over-reliance on AI may reduce critical-thinking ability and result in surface learning, thereby threatening intrinsic motivation. Thus, AI should be integrated ethically and strategically to enhance, not replace, human-driven learning motivation and metacognitive skills.