Artificial Intelligence (AI)

Still rebounding from the impact of the global pandemic, the higher education sector is being challenged even further by the next wave of Artificial Intelligence (AI) technologies. These technologies have the power to generate in a matter of seconds, quality text, images, music and coding responses to questions or prompts entered into an online chat box. Currently, one of the most accessible and popular text generators is OpenAI's ChatGPT which was released in November 2022. Early evaluation indicates that the quality of the responses exceed standard pass rates for comparable university assessments. Even if academic protocols mandate that text cited from AI sources should be acknowledged and referenced as any other source material, the speed, accessibility and high quality of the AI material justifies a rethink of the purpose of higher education and a redesign of curriculum, pedagogy and assessment. An initial suggestion being promoted in the sector is that learning outcomes and assessments should move away from a focus on content memorisation and recall, to development of higher order thinking skills such as critical analysis, evaluation, resilience, creativity, problem solving, appraising and mastery of verbal communication and computer literacy. This preliminary paper examines some of the literature to date, which discusses potential risks and threats, as well as the opportunities to enhance learning, embedded in this new wave of emerging AI technologies in higher education.

Increasingly, Artificial Intelligence (AI) is having an impact on distance-based higher education, where it is revealing multiple ethical issues. However, to date, there has been limited research addressing the perspectives of key stakeholders about these developments. The study presented in this paper sought to address this gap by investigating the perspectives of three key groups of stakeholders in distance-based higher education: students, teachers, and institutions. Empirical data collected in two workshops and a survey helped identify what concerns these stakeholders had about the ethics of AI in distance-based higher education. A theoretical framework for the ethics of AI in education was used to analyse that data and helped identify what was missing. In this exploratory study, there was no attempt to prioritise issues as more, or less, important. Instead, the value of the study reported in this paper derives from: (1) the breadth and detail of the issues that have been identified; and (2) their categorisation in a unifying framework. Together these provide a foundation for future research and may also usefully inform future institutional implementation and practice.

With the rapid societal emergence of generative artificial intelligence chatbots, calls for responsible use of generative AI permeate public voices among faculty, administration, and Centers for Teaching and Learning. The Diffusion of Innovation Theory seeks to explain how technologies like generative AI large language models are being adopted. Higher education is faced with addressing AI in instruction as generative AI chatbot usage gains popularity. Further, instructors seek to understand how generative AI can and is currently utilized in teaching and learning. In this study, 25 graduate education learners discussed their current use and perceptions of AI chatbots. Most of these learners indicated they had utilized AI chatbots to support their personal and professional lives. Most learners indicated that they did not utilize generative AI for academic writing assignments but used it for other pursuits. Implications for teaching and learning include discussing with learners how, when, and if generative AI can be utilized in the classroom.

Generative AI has drawn significant attention from stakeholders in higher education. As it introduces new opportunities for personalized learning and tutoring support, it simultaneously poses challenges to academic integrity and leads to ethical issues. Consequently, governing responsible AI usage within higher education institutions (HEIs) becomes increasingly important. Leading universities have already published guidelines on Generative AI, with most attempting to embrace this technology responsibly. This study provides a new perspective by focusing on strategies for responsible AI governance as demonstrated in these guidelines. Through a case study of 14 prestigious universities in the United States, we identified the multi-unit governance of AI, the role-specific governance of AI, and the academic characteristics of AI governance from their AI guidelines. The strengths and potential limitations of these strategies and characteristics are discussed. The findings offer practical implications for guiding responsible AI usage in HEIs and beyond.