Effectiveness of AI-driven personalized learning is context-dependent, with CS and Mathematics students showing contrasting engagement and performance trajectories¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? In introductory programming courses, CS students tended to develop more efficient learning strategies over time, while Mathematics students often displayed high engagement without corresponding achievement, with complex but inefficient work and greater susceptibility to learning avoidance. → Khalifeh 2026

Evidence¶

Khalifeh 2026¶

Khalifeh, F., Santiago, R., & Palau, R. (2026). Redefining personalized learning in the artificial intelligence era: an updated systematic review from 2019 to 2025. Smart Learning Environments. https://doi.org/10.1186/s40561-026-00440-6

q2 · i? · review · r2

The review reports, citing Gao et al. (2025), comparative analyses of CS and Mathematics students in introductory programming courses; the contrast is attributed to goal congruity, with CS students perceiving programming as central to their trajectories. The review attributes these findings to the cited study, which was not independently verified.

"CS students tend to develop more efficient learning strategies over time, showing reduced surface engagement alongside increased productivity and conceptual mastery."

Discussion¶

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