Study cognition with methods that allow real-world AI use, including longitudinal designs tracking self-regulation formation¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that developmental research move beyond lab tasks forbidding external aid, since such conditions "does not reflect the manner in which cognition will be applied in the real world." It calls for methods in which participants use intelligent systems as they do in real-world settings, and for longitudinal work: "Future studies are required to investigate the dynamics of cognitive processes in the presence of AI, and how they evolve as time goes by."

Design Implications¶

Context¶

Requirements¶

• Research paradigms permitting naturalistic human–AI interaction rather than simplified experimental tasks

Constraints¶

• Lab performance where external aid is forbidden may not reflect real-world cognition; without such research it is hard to tell whether performance changes reflect ability differences or task-structure differences

Target Learners¶

• children
• adolescents
• adults

Target Learning Goals¶

• understanding self-regulation development under AI co-regulation

Affordances¶

• Human Ai Co Regulation Framework

Related Strategies¶

• Study effort regulation in real-world, personally relevant contexts over longer timeframes, including via ecological momentary assessment

Examples¶

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Key Sources¶

• S P, Joseph J, Jose M, S M A, N R and Joseph J (2026) Artificial intelligence as a cognitive partner: a developmental framework for human–AI co-regulation in learning. Front. Dev. Psychol. 4:1835258. https://doi.org/10.3389/fdpys.2026.1835258