An Ethical Evaluation of Artificial Intelligence in Higher Education : A User-Experience Approach - Steinbartová, Kamila (2023)
As artificial intelligence (AI) technology becomes increasingly prevalent in higher education, there is a growing need to address the ethical implications of its use. This master's thesis takes a user-experience approach to evaluate the ethical implications of artificial intelligence in education (AIED), which encompasses a variety of AI-powered applications used in teaching and learning. The study employs a mixed-methods approach, combining qualitative and quantitative research techniques, to gain a comprehensive understanding of the student experience with AIED. A literature review and a pilot test including 10 semi-structured interviews identified the 13 most commonly used categories of AIED among university students, including grammar and spelling correctors, machine translators, paraphrasing tools, and language learning applications. The online survey conducted among 301 university students discovered that the majority of university students (77%) use AIED applications on a regular basis, highlighting the widespread use and present relevance of AIED in today’s higher education. Additionally, based on the results of the survey, the average adherence level of AIED to Aiken and Epstein's ten ethical principles was found to be 59%. Principle 1, which stresses the importance of designing AIED to encourage user motivation and prevent demoralization, exhibited the highest adherence rate of 69%. By contrast, principle 2, which focuses on promoting collaborative learning and human interaction through AIED, showed the lowest adherence rate of 44%. The respondents’ area of origin was found to have a significant impact, with Eastern European respondents reporting higher adherence means than those from North America.