Students' top two concerns about educational LLM use are output quality (fabricated or misleading content, 53 mentions) and the verification burden (34 mentions)¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2030: baselines and conditions change

Subclaims¶

q2 i? In the questionnaire, the most frequently cited problematic aspect of LLM use was incorrect, fabricated or misleading output (53 responses), followed by the constant need to cross-check outputs (34 responses). → Kudina 2025

Evidence¶

Kudina 2025¶

Kudina, O. (2025). Using AI in engineering education: a balancing act, driven by clear purpose. Draft version, to appear in The Routledge Handbook of the Philosophy of Engineering, 2nd ed. https://arxiv.org/abs/2606.16626 doi:10.48550/arxiv.2606.16626

q2 · i? · associational · r1

Questionnaire analysis of problematic aspects, summarized in Table 3 with counts: quality of output (53), verification burden (34), ethical concerns (19), impairing learning (18). Students reported that LLMs "produce incorrect, fabricated, or misleading information with confidence" and that checking is time-consuming.

"The summary of problematic aspects of students’ use of LLMs in education, as presented in Table 3, identifies questioning the quality of output and the need for constant evaluation as the top two concerns."

Discussion¶

Related Claims¶

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