arXiv:2604.01114v3 Announce Type: replace-cross Abstract: 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 characteristi
The proliferation of generative AI in educational settings necessitates understanding student interaction and reliance to guide responsible integration. This paper reflects growing concerns and research into the pedagogical implications of widespread AI adoption.
Understanding how students trust and rely on AI is crucial for designing effective educational tools and policies, preventing overreliance, and fostering critical thinking in an AI-augmented learning environment. This directly impacts future workforce capabilities and ethical AI development.
The focus shifts from merely deploying AI in education to strategically understanding and moderating how students engage with and interpret AI outputs. It highlights the need for AI literacy programs alongside AI tools.
- · Educational technologists
- · AI literacy program developers
- · Responsible AI developers
- · Students with high AI literacy
- · Educational institutions ignoring AI literacy
- · Students exhibiting uncritical overreliance
- · Developers of unmoderated AI educational tools
Educational curricula will likely evolve to include explicit AI literacy training and critical evaluation skills.
New assessment methodologies will emerge to differentiate between AI-assisted and human-generated work, and to gauge appropriate AI interaction.
Long-term societal impacts could include a generation of workers with varied critical thinking skills depending on their AI education, potentially exacerbating digital divides.
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Read at arXiv cs.AI