Students’ reflective use of general-purpose LLMs rather than educational AI systems or tutoring agents is focused on, with a pilotable intervention and illustrative pilot evidence offering a pilotable intervention and illustrative pilot evidence.
This exploratory qualitative study examines how students' expectations of one process-capture platform, Turnitin Clarity, compared with their experience of using it are compared with their experience of using the platform.
J. Roe, M. University, British University Vietnam· 0 citations
Large language models (LLMs) raise new questions for instructors, among them how to integrate LLMs productively into coursework and what to evaluate in students'work when an LLM can produce much of it directly. LLM-guided homework assignments offer one answer. Instructors configure the LLM to guide students in ways tha...
E. Furfaro, Katherine Elizabeth Lovelace, Yu-Hang Zhang et al.· 0 citations
Structured practice merits refinement; teacher-facing analytics require evaluation for actionability; Structured practice merits refinement; teacher-facing analytics require evaluation for actionability.
This exploratory study examines graduate students’ perceptions of generative AI use in coursework and evaluates the feasibility of using large language models (LLMs) to support thematic coding of brief open-ended responses. Students (n = 20) enrolled in a systems analysis and design course completed a post-course surve...
Viktors J. Muiznieks, Billie S. Anderson, Tyler Price· Discover Education· 0 citations
Instructor practices in higher education for setting assignment-level expectations have been meaningfully shaped by the Transparency in Learning and Teaching (TILT) Framework (Winkelmes, 2023a, 2023b) which encourages the development of clear guidance for students around each assignment’s purpose, core tasks, and asses...
A. Wiss, Karen E. Singer-freeman, J. Pattershall-Geide et al.· Online Learning· 0 citations
A common concern is that using large language models (LLMs) lets students offload mathematical work that tasks are designed to elicit. Yet such claims often rest on outcomes (e.g., submitted solutions), rather than on evidence of students'work with LLMs. We followed 23 first-year linear algebra students as they solved...
Igor'Kontorovich, Miriam N. Wallach· 0 citations
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