Responsible AI Adoption In Virtual Learning Environments: A Qualitative Pilot Study Using Generative Tools

Sumpter, John (2026) Responsible AI Adoption In Virtual Learning Environments: A Qualitative Pilot Study Using Generative Tools. In: EduLearn26, 29th June - 1st July 2026, Spain. (Submitted)

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Abstract / Summary

The rapid diffusion of artificial intelligence in higher education offers opportunities to enhance learning
design while raising significant ethical and academic integrity questions. To explore how generative AI
can be implemented responsibly within virtual learning environments (VLEs), this qualitative pilot study
investigates the use of generative tools to support development of code‑based learning components in
Canvas (VLE). Drawing on reflective practice accounts, semi‑structured discussions and iterative design
documents from members of a digital learning team, the study examines how AI assistance influences
professional agency, trust, accountability and pedagogical control when co‑creating digital learning
artefacts. Participants experimented with AI‑driven code generation and content design to automate
elements of instructional development and improve workflow efficiency. Throughout the pilot, the team
followed institutional AI policies and ethical frameworks, embedding transparency and disclosure
statements into AI‑assisted artefacts and monitoring the impact on academic integrity. Analysis reveals
that generative AI can act as an augmentative partner in digital learning when clear ethical guidelines
are in place. Participants reported gains in efficiency and creativity, but emphasised the need for human
oversight, rigorous validation of AI‑generated output, and transparent communication with students and
stakeholders. The study concludes that responsible integration of AI requires shared professional norms,
institutional support for AI literacy and governance, and ongoing evaluation of how AI tools affect equity,
academic standards and pedagogical values. These insights offer practical guidance for universities
seeking to leverage AI within VLE ecosystems while sustaining integrity, equity and responsible
innovation.

Item Type:	Conference or Workshop Item (Lecture)
Uncontrolled Keywords:	AI, technology, education, instructional design, ethics, responsible AI, VLE, learning design.
Subjects:	Computing & Data Science
Department:	Professional and Academic Services
Depositing User:	John Sumpter
Date Deposited:	07 Jul 2026 13:57
Last Modified:	07 Jul 2026 13:57
URI:	https://repository.falmouth.ac.uk/id/eprint/6535

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