Beyond Access: Guided LLM Scaffolding for Independent Learning in Undergraduate Statistics
Large language models (LLMs) are increasingly entering students' learning practices, but their educational value may depend on whether they are used to support reasoning or to complete tasks without engaging in the underlying reasoning. This study examines guided LLM use in an undergraduate Probability and Statistics course, focusing on the distinction between assigned LLM access and the quality of students' actual interaction with the model. In a four-week quasi-experimental summer program, students were organized into three balanced conditions: no LLM access, unrestricted LLM access, and guided LLM access. The guided condition used the same LLM platform as the unrestricted condition, bu...
| Authors | Mohammad Amanlou, Yasaman Amou-Jafari, Fereshte Bagheri et al. |
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| Primary category | cs.CY |
| Published | 31 May 2026 |
| Last updated at source | 17 August 2026 |
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