Address debilitating technology anxiety through supportive low-stakes introductory experiences while preserving the critical stance that accompanies it¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends against undifferentiated anxiety reduction: because residual anxiety was positively associated with critical appraisal and ethical judgement dimensions of AI literacy, removing apprehension wholesale may also remove the disposition to scrutinise AI outputs. It proposes addressing only debilitating anxiety "through supportive and low-stakes introductory experiences" and framing caution as a component of competent AI use rather than an obstacle to it.

Design Implications¶

Context¶

Requirements¶

• Introductory AI experiences must be supportive and low-stakes so that debilitating anxiety is addressed without eliminating critical vigilance

Constraints¶

• The authors state these implications are generated by cross-sectional correlational data and none has been tested experimentally; causal inference requires intervention designs

Target Learners¶

• undergraduate university students in humanities and social sciences

Target Learning Goals¶

• critical evaluation of AI outputs
• ethical competence with AI
• responsible AI use

Related Strategies¶

• Universities combine responsible AI use guidelines, accessible technical support, AI literacy training, and assessment-embedded critical evaluation activities to address AI learning anxiety
• Explicate, Validate, and Address Negative Emotions
• Target calibrated trust and anxiety alongside AI literacy instruction when supporting existing generative AI users

Examples¶

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Key Sources¶

• Chow Tak Sang, To Ken, Lam Bess Yin Hung, Lau Kung Wong. (2026). A Multidimensional Analysis of AI Literacy Determinants: External Resources, Digital Skills, and Psychological Profile Among University Students. Behavioral Sciences. https://doi.org/10.3390/bs16081448