# Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators

arXiv: https://arxiv.org/abs/2604.01114 · HTML: https://mlsanity.com/paper/2604.01114/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 39 references that are in the map.
- First posted on arXiv 1 Apr 2026.

## Builds on (most cited first, 11 of 11)

- [Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making](https://mlsanity.com/paper/2001.02114/) (2020)
- [Expanding Explainability: Towards Social Transparency in AI systems](https://mlsanity.com/paper/2101.04719/) (2021)
- [Explanations Can Reduce Overreliance on AI Systems During Decision-Making](https://mlsanity.com/paper/2212.06823/) (2022)
- [MAILS -- Meta AI Literacy Scale: Development and Testing of an AI Literacy Questionnaire Based on Well-Founded Competency Models and Psychological Change- and Meta-Competencies](https://mlsanity.com/paper/2302.09319/) (2023)
- [Challenges and Opportunities of Moderating Usage of Large Language Models in Education](https://mlsanity.com/paper/2312.14969/) (2023)
- [Student Perspectives on the Benefits and Risks of AI in Education](https://mlsanity.com/paper/2505.02198/) (2025)
- [A Survey of LLM-Based Applications in Programming Education: Balancing Automation and Human Oversight](https://mlsanity.com/paper/2510.03719/) (2025)
- [Students' Reliance on AI in Higher Education: Identifying Contributing Factors](https://mlsanity.com/paper/2506.13845/) (2025)
- [Plan More, Debug Less: Applying Metacognitive Theory to AI-Assisted Programming Education](https://mlsanity.com/paper/2509.03171/) (2025)
- [Understanding Human-AI Trust in Education](https://mlsanity.com/paper/2506.09160/) (2025)
- [What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI](https://mlsanity.com/paper/2602.20547/) (2026)

## Built on by (most cited first, 3 of 3)

- [Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education](https://mlsanity.com/paper/2605.12988/) (2026)
- [Perceived Importance of Cognitive Skills Among Computing Students in the Era of AI](https://mlsanity.com/paper/2604.10730/) (2026)
- [Cognitive Skills in the Age of AI: Computing Students and Experts Perceptions](https://mlsanity.com/paper/2609.31272/) (2026)

## Abstract (arXiv)

As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning tasks, either by requesting help or through integrated tools. Trust in AI can influence how students interpret and use that output, including whether they evaluate it critically or exhibit overreliance. We investigate how students' trust relates to their appropriate reliance on an AI assistant during programming problem-solving tasks, and whether this relationship differs by learner characteristics. With 432 undergraduate participants, students' completed Python output-prediction problems while receiving recommendations and explanations from an AI chatbot, including accurate and intentionally misleading suggestions. We operationalize reliance behaviorally as the extent to which students' responses reflected appropriate use of the AI assistant's suggestions, accepting them when they were correct and rejecting them when they were incorrect. Pre- and post-task surveys assessed trust in the assistant, AI literacy, need for cognition, programming self-efficacy, and programming literacy. Results showed a non-linear relationship in which higher trust was associated with lower appropriate reliance, suggesting weaker discrimination between correct and incorrect recommendations. This relationship was significantly moderated by students' AI literacy and need for cognition. These findings highlight the need for future work on instructional and system supports that encourage more reflective evaluation of AI assistance during problem-solving.