Personalized learning functions as a collaborative human–AI model in which teachers and AI systems play complementary roles¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? Teachers lead design, implementation, and evaluation by interpreting learner data, aligning system recommendations with curricular goals, providing socio-emotional support, and intervening when automated pathways conflict with learner needs. → Khalifeh 2026 q2 i? AI systems contribute through learner modeling, real-time adaptation, and continuous analytics, generating learner profiles, predicting performance, personalizing content, and monitoring engagement. → 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's Research Question 7 synthesis across included studies. It concludes personalized learning is most effective when AI provides adaptive precision while teachers ensure pedagogical coherence, ethical oversight, and human involvement, with the two functioning as interdependent partners.

"Findings across studies indicate that personalized learning functions as a collaborative human–AI model in which teachers and AI systems play complementary roles."

Discussion¶

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