AI-driven Feedback and Its Impact on Student Motivation in Online Learning - Putri Larasati, Sectio; Dina Sukma; Firman; Yeni Karneli; Miftahul Fikri; Muhammad Asyraf Che Amat; Ridho Rismi (G-Couns: Jurnal Bimbingan dan Konseling, 2026)
The rise of Artificial Intelligence (AI) in online learning has reshaped education, with AI-driven feedback as a key innovation. This paper systematically reviews its role in enhancing student motivation through the lens of Self-Determination Theory (SDT). Using a PRISMA-based Systematic Literature Review (SLR), 20 journal articles were selected from Scopus and Web of Science. VOSviewer supported bibliometric and thematic analyses, mapping keyword co-occurrence and research trends. Results show that AI-driven feedback enhances competence through timely, specific guidance; promotes autonomy through adaptive personalization; and fosters relatedness through interactive features and gamification. Challenges include affective satisfaction, ethical concerns, data privacy, and balancing teacher technology roles. AI-driven feedback can enhance intrinsic motivation in online learning when integrated with sound pedagogy and teacher support. Future research should explore long-term impacts and refine strategies for human AI balance. Keywords: AI-driven feedback, adaptive learning, student motivation, online learning