Activity: Academic Talks or Presentations › Oral presentation › Research
Understanding the impact of the Learning Development service on students and staff is crucial in determining whether we make a difference. Quantitative surveys give an overview of staff and student opinion, but they may not give us the full picture. In-depth qualitative interviews give the opportunity to hear student and staff points of view on the service we provide. At the University of Northampton, in-depth interviews were conducted with students and staff to explore their usage of and opinions on Learning Development to help develop our understanding and improve and grow our service. The students included users and non-users of Learning Development. A problem with in-depth interviews is that they take considerable time to analyse due to the manual process of reading through transcripts and are based on the researcher self-determining the thematic review. Therefore, it was decided to perform a computer analysis using text analytic software, enabling the qualitative analysis to be undertaken in a time-efficient and objective manner. In theory, this software, with its automated analytical process, should provide insights by finding positive and negative associations within text, key phrases, language, themes and patterns. The paper will compare the analyses of the qualitative research data completed using three different methods with varying degrees of automation: the more traditional method of NVivo which is researcher-led tool; WMatrix a semi-automated computer-based text mining method; and Leximancer, a wholly automated text mining software package. The analytical approaches and ease of use will be considered alongside whether they produce results that are consistent; interpretable by the researcher by producing key themes; and useful in understanding the Learning Development service.
This research will inform future qualitative analysis practice, which will be directly relevant to other delegates.