Student attitudes towards the use of Generative AI in a Foundation Level English for Academic Purposes course and the impact of in-class interventions on these attitudes.
The impact of Generative AI on Higher Education is still very uncertain. The speed that this technology is developing and the potentially both positive and negative impacts of this on student learning are still evolving. Therefore, how we as Higher Education educators adapt to this change is an area of importance. The Russel Group Principles say that “Universities will support students … to become AI-literate” and that “Universities will adapt teaching and assessment to incorporate the ethical use of generative AI and support equal access”. The issue is how best to do this when there is very little way in the way of precedent for the best way forward. This research is therefore assessing an approach taken in a Foundation Level English for Academic Purposes (EAP) course. Its objective is to research student attitudes and ideas about how to use generative AI in an academic setting and then assess to what extent these opinions change as the students have more input on using generative AI across Terms 1 and 2.
The potential survey group are students studying on the EAP course in this year’s King’s International Foundations Programme (KIF). There are 345 students on this course and it is expected that there will be reasonably high participation (the first survey had 191 responses). The average age of these students is 18 and they are from a wide range of nationalities with the two largest groups being Chinese and Saudi Arabian. All the students on the EAP course have English as a second language. The KIF is a high stakes gatekeeper course, where students need to get overall marks of 65% or 70% and a minimum score in English for Academic Purposes of 65% to progress to Undergraduate studies at King’s.
This year on the EAP course, there is specific input on the use of generative AI throughout term 1 and 2. For example, students have already looked at its use for paraphrasing, critiquing samples of AI generated paraphrases. This research aims to assess the efficacy of these interventions through the use of a longitudinal survey with three data gathering points and student focus groups based on the findings from the survey. It is envisaged that students will also co-analyse the data, as it will used as a basis for teaching materials on the topic of analysing and discussing data.
The hypothesis behind this is that the interventions in classes on AI use will have an impact on student attitudes towards AI use for academic purposes, including students who see it as a tool to “cheat” and those who have negative attitudes towards it and do not want to use it. The findings will then be used to help plan next year’s iteration of the course and hopefully allow for the creation of generalisable teaching techniques with data to support their efficacy.