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Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence

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arXiv:2605. 29041v1 Announce Type: new Abstract: This study reports findings from a cross-sectional survey (n = 72) of higher education practitioners examining beliefs, behaviors, and institutional conditions related to artificial intelligence (AI) integration in teaching and learning.

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Authors: David Gibson (Curtin University), M. Elizabeth Azukas (Georgia Institute of Technology), Gerald Knezek (University of North Texas)
Released: 2026-05-29 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, rect, alpha, eval, rate, implement, factor, lora. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2605.29041

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