Abstract:

The proposed paper would present the main findings from a survey of teachers at higher education institutions across 9 European countries: UK, France, Belgium, Norway, Denmark, Germany, Austria, Italy and Serbia. The main aim of the survey is to discover innovative uses of Generative AI tools (GenAI) where the use of technology is enhancing teaching, learning and research among university educators. Moreover, we aim to discover what training creates empowerment and how those utilizing this technology think about and act upon ethical concerns. The survey is distributed online starting in March 2025 and it will be open until 9th May 2025. The survey is aimed at those teaching across these 9 universities at any level ranging from hourly-paid lecturers to tenured professors. The team managing and conducting this survey is interdisciplinary and international consisting of computer scientists, sociologists, educational scientists, AI governance experts, and university AI leads. This abstract is based on the analysis of the responses currently collected, which is 235 (as of 24th March 2025). The survey consists of a range of questions: those looking at the areas of use are multiple choice questions, questions asking about innovation are a combination of multiple choice and open-ended questions, those asking about ethics are multiple-choice questions, and in terms of training and critical AI literacy, we used Likert scale questions. In terms of analysis, we are using descriptive statistics and thematic coding. We defined GenAI broadly as a subset of AI that utilizes machine learning models to create new data rather than making a prediction about a specific dataset. A genAI system is one that learns to generate more objects that look like the data it was trained on. We were also interested in exploring personalisation of these tools and the creation of proprietary models. The proposed paper would present a selection of findings from this research. The first part would look at overarching results and break down the main findings in terms of how the following factors are influencing innovative use and perceived benefits of GenAI tools: area of expertise, targeted training attended, career stage, gender, and perceived trustworthiness. What we have found so far is that most of the innovative use of GenAI tools is when it comes to teaching rather than research, and from those who have expertise in AI or are working in collaboration with AI experts. Targeted training has limited influence with respondents claiming their expertise in AI having the determining effect. The second part of the presentation would focus on ethics in relation to the use of Generative AI tools by higher education teachers. One of the key findings from the survey is how narrowly ethics is defined among the respondents mainly in terms of privacy and data protection. Furthermore, there is little in terms of proactively seeking to make the use ethical – more than 90% of respondents say that there is reliance on the existing technology design to mitigate against ethical risks. The third part of the presentation would look at the links between critical AI literacy training and its effect on the use of GenAI tools. One of the key findings here is the absence of targeted literacy programmes for university educators. Here we link the data from these questions to the wider conclusions we make about the current and future uses of Generative AI tools among Higher education teachers.

Keywords:

Generative AI, education, ethics, critical AI literacy.