Adopt a clear pedagogical approach focused on critical thinking and fact-checking strategies when integrating LLMs into curricula¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The paper recommends that educational systems pair LLM use with a pedagogical approach centered on critical thinking and fact checking. It states that "a clear pedagogical approach with a strong focus on critical thinking and strategies for fact checking are required to integrate and take full advantage of large language models in learning settings and teaching curricula." Concrete moves include using models to generate hypotheses and explore perspectives rather than answers, and encouraging learners to question and corroborate generated content against authoritative sources.

Design Implications¶

Context¶

Requirements¶

• A clear strategy within educational systems and a clear pedagogical approach with strong focus on critical thinking and fact-checking strategies.

Constraints¶

• The paper warns that effortlessly generated information could negatively impact critical thinking and problem-solving skills if learners rely too heavily on the model.

Target Learners¶

• students across primary, secondary, tertiary and professional education

Target Learning Goals¶

• critical thinking
• fact checking and corroboration of model output
• independent investigation and problem solving

Related Strategies¶

• Adopt ethical safeguards and pedagogically grounded frameworks when deploying GenAI assessment tools
• Scaffolded AI integration with teacher training and reflective tasks to reduce over-reliance

Examples¶

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Key Sources¶

• Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., & Kasneci, G. (2023). ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. https://doi.org/10.1016/j.lindif.2023.102274