How students use translation and AI tools
At a glance
Student: Abhinav C G
Role: Research Intern
Host: School of Chemistry, University of Edinburgh
Methods and tools: R, data visualisation, chi-square tests, regression, focus group and thematic analysis
The project
Abhinav C G investigated how taught students in the Schools of Chemistry and Biology use translation and language-support software, including generative AI. The project considered how these tools may shape students’ academic experiences, language development and sense of belonging within their learning communities.
The research approach
The project used a mixed-methods design. Abhinav C G analysed survey data in R, using visualisation to explore patterns and chi-square tests and regression to examine relationships in the data. He complemented this quantitative work with a focus group and thematic analysis.
Why the work mattered
Bringing the quantitative and qualitative evidence together made it possible to examine both broad patterns of tool use and the experiences behind them. The project addressed a rapidly developing issue for universities: how students use emerging technologies and what that may mean for learning and participation.
Skills developed
- Cleaning, visualising and analysing survey data in R
- Applying chi-square tests and regression
- Designing and analysing a focus group
- Combining quantitative and qualitative evidence
- Communicating findings across disciplinary boundaries
Connect with Abhinav C G on LinkedIn.