Guide students on when conversational AI supports learning versus when it replaces checking, evaluation, and independent judgment¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The review's practical implication for education is that the concern is unexamined delegation rather than AI use itself. It states: "Students need guidance on when conversational AI supports learning and when it begins to replace checking, evaluation, and independent judgment." This positions educational intervention at the point of delegation calibration rather than prohibition of use, consistent with the review's distinction between calibrated reliance and over-reliance.

Design Implications¶

Context¶

Requirements¶

• Educators must be able to distinguish calibrated reliance from over-reliance (delegation without adequate scrutiny)

Constraints¶

• The reviewed evidence does not establish a direction of effect between AI delegation and academic strain, so guidance rests on concurrent-association evidence

Target Learners¶

• Students in higher-education settings, the most common samples in the reviewed corpus

Target Learning Goals¶

• Maintaining independent judgment, checking, and evaluation when using conversational AI for academic tasks

Affordances¶

• Trust Reliance Attachment Dependence Construct Boundaries

Related Strategies¶

• Post-instrumental assessment: certify the learner's accountable relation to AI-mediated work via a design sequence of naming the capacity, classifying AI use, and requiring evidence at the point of judgment
• Dimensions of Critical Evaluation

Examples¶

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Key Sources¶

• Yan D (2026). A critical narrative synthesis of psychological correlates, measurement, and reported findings on conversational AI engagement and dependence-related constructs. Front. Psychol. 17:1827795. https://doi.org/10.3389/fpsyg.2026.1827795