The Digital Paradox in Schools: Navigating The Intersection between Artificial Intelligence and Academic Performance - Friyanda, Nurul Fahri; Dartim, Dartim (Proceeding ISETH (International Summit on Science, Technology, and Humanity), 2025)
The acceleration of the digitalization of education and the introduction of artificial intelligence (AI) into the classroom have created a "digital paradox": technologies designed to improve the quality of learning can simultaneously have opposite impacts, such as decreased motivation, weakened deep understanding, threats to academic integrity, and inequality in learning outcomes. This study aims to map and synthesize empirical evidence on the relationship between the use of AI/digital education and academic performance, as well as identify the conditions that make its impact stronger or weaker. The method used is a PRISMA-based Systematic Literature Review (SLR) with Scopus as a single database. The search uses structured Boolean strings in the range of 2021–2025, open access journal articles, Social Sciences/Arts and Humanities, and English. From the initial 562 articles, it was filtered down to 38, and through relevance screening based on title–abstract–content verification reading, 9 studies that met the inclusion criteria were obtained. Narrative synthesis shows evidence that the impact of AI on academic performance is contextual and not always consistent: some studies highlight benefits (learning support, personalization, early warning, acceleration of assessment), while others emphasize affective trade offs (interest/motivation), risks of cognitive "shortcut" behavior, and validity-fairness issues in digital assessments. These findings confirm that the impact of AI is more determined by task–AI fit, AI literacy and ethics, assessment design that assesses thought processes, and equity-sensitive school governance.