Student chatbot queries were overwhelmingly task-oriented initial inquiries, dominated by definition requests and pasted assignment questions rather than iterative critique¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q2 i? Initial Inquiry behaviors comprised 70.3% of all queries, with Definition (42.1%) and Copy (24.3%) codes together constituting 66.4% of interactions. → Yuan-Hsuan Lee and Jiun-Yu Wu 2026 q2 i? Deeper iterative behaviors such as Doubt (3.4%) and Extend (3.8%) were considerably less frequent than Repeat and Check. → Yuan-Hsuan Lee and Jiun-Yu Wu 2026 (2)

Evidence¶

Yuan-Hsuan Lee and Jiun-Yu Wu 2026¶

Yuan-Hsuan Lee and Jiun-Yu Wu. (2026). Differential engagement with generative artificial intelligence in higher education: Gender, motivation, and achievement trajectories. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00615-8

q2 · i? · associational · r2

Inductive–deductive content analysis of all 2,819 chatbot entries (Cohen's kappa = .898) coded ten fine-grained behaviors in three macro-categories; the Initial Inquiry macro-category comprised 70.3% (n = 1,984) of queries, dominated by definition requests and pasted assignment problems.

"Within this category, two behaviors were highly dominant: Definition (Def) queries (42.1%, n = 1,189) and Copy behaviors (24.3%, n = 687). Collectively, these two codes constituted 66.4% of all student-chatbot interactions, establishing the tool's primary role as a resource for definitional knowledge and direct problem framing (fact seeking)."

Yuan-Hsuan Lee and Jiun-Yu Wu 2026 (2)¶

Yuan-Hsuan Lee and Jiun-Yu Wu. (2026). Differential engagement with generative artificial intelligence in higher education: Gender, motivation, and achievement trajectories. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00615-8

q2 · i? · associational · r2

Within the Follow-Up Inquiry macro-category (26.4%, n = 746), the most common behaviors were Repeat (11.6%, n = 326) and Check (7.7%, n = 217), while explicit critique of chatbot answers (Doubt) and extension (Extend) were rare; Other Inquiry was minimal at 3.3% (n = 92).

"Behaviors reflecting explicit self-correction or critique, such as Doubt (3.4%, n = 97) and Extend (3.8%, n = 106), were considerably less frequent."

Discussion¶

Related Claims¶

• Shallow, copy-pasting engagement occurred but was not the dominant mode of GenAI Tutor use, and was lowest during exam preparation — reports the opposite
• Growing Achievers used StatBot significantly more than Declining Performers, driven mainly by initiating new inquiries — related
• Telegram-based chatbot use declined after initial novelty, with platform friction cited as a barrier — related
• In Study 2, Question Autocompletion was widely adopted and the proportion of knowledge-based questions increased significantly across session stages — related
• Peer answering in the hybrid support system was fast where it occurred: 70.3% of peer-answered queries closed within one hour, against 1.9% of administrator-answered and 14.8% of script-closed queries — related
• Most unrestricted-mode interactions were direct answer retrieval: 52.9% of exercise interactions were copy-paste of the question, and participant answers were linguistically near-identical to chatbot text in 25.3% of cases — related
• First queries from Cold Start learners were overwhelmingly dependent (96.7%), contrasting with mostly guided first queries from Oriented (69.1%) and Struggling (71.4%) learners — related
• Explanatory inquiries, factual queries, and tutorial requests are the most frequent LLM learning tasks — related
• Students' GenAI prompts overwhelmingly exact-copy instructions and request information rather than review — possibly the same claim (merge candidate)
• Students rated the LLM-based assignments as useful, challenging, engaging, and enjoyable at both the first and fifth iterations, with no significant change across the semester — related
• Assessment/Evaluation was the most common use of AIEd in higher education, with automatic assessment in 26 studies — related
• Technologically oriented help requests comprised 11.5% of requests and declined steeply from the first to the last post-experiment activity
• Socratic + No Context produces the highest query volume and Direct + No Context the longest messages — related
• Students' inquiry sequences differ by session: most start with Assertion questions in Session 1 (prob = 0.48) but with Instrumental/Procedural questions in Session 2 (prob = 0.43) — related
• More than half of participants' ChatGPT queries sought knowledge or advice, with methodological knowledge and classroom management the largest prompt categories — related
• Learners engaged extensively with the chatbot, overwhelmingly communicating in Japanese rather than English — related
• Students dynamically switched between Socratic Inquiry and Transactional Delegation as deadlines approached and task novelty changed (the Strategic Dance) — related
• A small subset of question types accounts for the majority of student inquiries to AI, with Assertion the most frequent category in both CS2 sessions — related
• Guest-mode usage dominates lightweight help-seeking, raising an equity concern that students without metacognitive support stay at shallow answer lookup — related
• Students treated the genAI avatar as a sophisticated question base rather than a virtual patient, using predominantly closed-ended, efficiency-focused questioning — related