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.
Abstract
Process-capture platforms promise to make the writing behind an assessed artefact visible, and vendors increasingly market them as a fairness measure rather than a detection tool. Their acceptability to the students who must write within them, however, is largely untested. This exploratory qualitative study examines how students'expectations of one such platform, Turnitin Clarity, compared with their experience of using it. Seven students at a UK university, given no onboarding to the platform, took part in pre-use focus groups. Six then completed an unassessed 500-word writing task over five days, before all seven returned for a post-use focus group. Data was analysed using reflexive thematic analysis, with Expectation-Confirmation Theory as an orienting frame. The overall pattern was one of mixed confirmation. Participants'functional expectations were largely met, and the sense of being watched that they had anticipated persisted after use: for some it was offset by perceived fairness, while for others it heightened self-monitoring. The bounded AI assistant divided them: its limits were welcomed for marking out acceptable use, but some felt it weakened their ownership of the work and worried it would flatten what they produced. Across both phases, participants weighed the costs of observation against perceived gains in fairness and asked for transparency to run in both directions. Several described already writing defensively in anticipation of accusations of AI misuse. Acceptance of process technologies was reported as being conditional on practice time, two-way transparency, and explicit data governance. Participants also questioned whether a single linear document can represent a writing process they described as messy and multimodal. Across these accounts, process capture did not sit outside the writing it recorded but reorganised the practice it set out to observe.
Since the release of OpenAI’s ChatGPT in November 2022, Generative AI (GenAI) has been rapidly integrated into applications capable of producing texts, images, and sounds that simulate human output. While students generally view this technology positively, writing scholars voice increasing concerns, particularly regard...
Jin-Rong Li, Kathleen O'Reilly· The Open/Technology in Educa...· 0 citations
This research study focuses on the pedagogical importance and student perspectives of the AI-driven “Write & Improve” web app in developing English writing skills. Using a mixed-methods research design, the study followed 24 students from the 12th grade at Mandakh Lyceum high school during a five-week experimental peri...
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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.
An exploratory study of computing students' perceptions, knowledge, and experiences with OSS at the University of Hawai'i at Manoa provides a nuanced understanding of how curriculum structure, faculty encouragement, and competing academic demands shape OSS participation.
Ítalo Santos, Briana M. Lee, Derek Garcia et al.· 0 citations
The rapid diffusion of Generative Artificial Intelligence (GenAI) tools such as ChatGPT into higher education has unsettled long standing assumptions about the validity, reliability, and authenticity of conventional assessment methods. Existing research has predominantly examined perceptions, ethical concerns, and tech...
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