Embedding Generative AI as a digital capability into a year-long skills program.

The arrival of Generative Artificial Intelligence (GenAI) into higher education has significantly transformed assessment practices and pedagogical approaches. Large Language Models (LLMs) powered by GenAI present unprecedented opportunities for personalised learning journeys. However, the emergence of GenAI in higher education raises concerns regarding academic integrity and the development of essential cognitive and creative skills among students. Critics worry about the potential decline in academic standards and the perpetuation of biases inherent in the training sets used for LLMs. Addressing these concerns requires clear frameworks and continual evaluation and updating of assessment practices to leverage GenAI's capabilities while preserving academic integrity. Here, we evaluated the integration of GenAI into a year-long MSc program to enhance student understanding and confidence in using GenAI. Approaching GenAI as a digital competency, its use was integrated into core skills modules across two semesters, focusing on ethical considerations, prompt engineering, and tool usage. The assessment tasks were redesigned to incorporate GenAI, which takes a process-based assessment approach. Students' perceptions were evaluated alongside skills audits, and they reported increased confidence in using GenAI. Thematic analysis of one-to-one interviews revealed a cyclical relationship between students' usage of GenAI, experience, ethical considerations, and learning adaptation.

Authors

Institutions

Publication Details

Journal
Journal of University Teaching and Learning Practice
Published
2025-06-17
DOI
https://doi.org/10.53761/fh6q4v89
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Embedding Generative AI as a digital capability into a year-long skills program.

Melissa Lacey, David P. Smith, Chioma Angela Okonkwo, Charlotte Boyd et al.
1 citations
Journal of University Teaching and Learning Practice
Online Learning and Analytics
1.69
article

Embedding Generative AI as a digital capability into a year-long skills program.

Melissa Lacey, David P. Smith, Chioma Angela Okonkwo, Charlotte Boyd, Nigel Francis, Dami Sokoya, Skye Moore
article en
1 citations

Abstract

The arrival of Generative Artificial Intelligence (GenAI) into higher education has significantly transformed assessment practices and pedagogical approaches. Large Language Models (LLMs) powered by GenAI present unprecedented opportunities for personalised learning journeys. However, the emergence of GenAI in higher education raises concerns regarding academic integrity and the development of essential cognitive and creative skills among students. Critics worry about the potential decline in academic standards and the perpetuation of biases inherent in the training sets used for LLMs. Addressing these concerns requires clear frameworks and continual evaluation and updating of assessment practices to leverage GenAI's capabilities while preserving academic integrity. Here, we evaluated the integration of GenAI into a year-long MSc program to enhance student understanding and confidence in using GenAI. Approaching GenAI as a digital competency, its use was integrated into core skills modules across two semesters, focusing on ethical considerations, prompt engineering, and tool usage. The assessment tasks were redesigned to incorporate GenAI, which takes a process-based assessment approach. Students' perceptions were evaluated alongside skills audits, and they reported increased confidence in using GenAI. Thematic analysis of one-to-one interviews revealed a cyclical relationship between students' usage of GenAI, experience, ethical considerations, and learning adaptation.

Journal of University Teaching and Learning PracticeVol. 22(4)
Sheffield Hallam University (GB), Cardiff University (GB)
Sheffield Hallam University
Openalex Percentile: Top 12%
Online Learning and Analytics
1.69
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Embedding Generative AI as a digital capability into a year-long skills program. — Melissa Lacey, David P. Smith, et al. · Journal of University Teaching and Learning Practice (2025) | TGRS Research Map | TGRS