Over the past two decades, educational leadership has increasingly been identified as a key factor in facilitating and enabling academic development. Nevertheless, the body of literature on the subject remains limited and reflects considerable ambiguity regarding how the relationship between educational leadership and academic development should be understood. For this special issue, we invited contributions that could advance our understanding of educational leadership from the perspective of academic developers. In this editorial, we present four distinct relational orientations between educational leadership and academic development. We argue that these configurations can serve a dual purpose: clarifying what forms of educational leadership are under discussion, and identifying areas in which further empirical and theoretical research are needed.

Informed consent (IC) is a fundamental cornerstone in medical ethics, medical research and also medical education research.1 When we say IC in the specific context of qualitative research interviews, we are not only invoking a procedural step in research ethics but also referring to a deeper social and relational agreement between researchers and participants. This agreement between researcher and researcher participants is currently being renegotiated due to the push for data sharing in health professions education journals, as well as other research contexts. As scientific research increasingly embraces transparency and accessibility, the ‘Open Science’ movement advocates for making research data freely available.2 This shift towards openness highlights the need for researchers to navigate and reflect on the balance between ethical obligations and the benefits of widespread data sharing and accordingly reconsider what it means to ask for IC from participants in a scientific study.

Resilience becomes increasingly critical in today’s higher education environment, which faces numerous challenges and disruptions. Academic developers are in a unique position to assist in facilitating resilience at individual, departmental, and institutional levels. Based on a valuable collection of work in the current issue of the International Journal for Academic Development, this editorial synthesises how resilience is defined, promoted, and sustained through various theoretical lenses and approaches. Put together, these contributions highlight the importance of relationship and capacity building, ethical partnership, proper reward and recognition, and more importantly, a critical examination of many of the assumptions underlying the current structures and systems.

Artificial intelligence (AI) chatbots trained on large language models are an example of generative AI which brings promises and threats to the higher education sector. In this study, we examine the emerging research area of AI chatbots in higher education (HE), focusing specifically on empirical studies conducted since the release of ChatGPT. Our review includes 23 research articles published between December 2022 and December 2023 exploring the use of AI chatbots in HE settings. We take a three-pronged approach to the empirical data. We first examine the state of the emerging field of AI chatbots in HE. Second, we identify the theories of learning used in the empirical studies on AI chatbots in HE. Third, we scrutinise the discourses of AI in HE framing the latest empirical work on AI chatbots. Our findings contribute to a better understanding of the eclectic state of the nascent research area of AI chatbots in HE, the lack of common conceptual groundings about human learning, and the presence of both dystopian and utopian discourses about the future role of AI chatbots in HE.

The integration of generative artificial intelligence (GAI) chatbots in higher education has introduced both opportunities and challenges for students’ academic practices. To date, most qualitative research has examined the implications of this phenomenon for teaching practices and the experiences of teachers. This explorative study investigates how students use GAI chatbots in their studies and how they evaluate AI generated text, particularly in relation to academic integrity, reliability, and ethical norms. Using a qualitative research approach, we conducted semi-structured interviews with higher education students to a) examine students’ experiences of using GAI chatbots in their academic studies, and b) to explore how students perceive the ethical impact of using chatbots on their studies. The findings reveal that while students use GAI chatbots to support writing, idea generation, and language improvement, they also face challenges related to plagiarism concerns, the reliability of AI-generated content, and the lack of clear institutional guidelines on responsible AI use. Additionally, the study highlights how students develop individual strategies to navigate these challenges, including seeking validation from educators and critically assessing AI-generated outputs. The findings emphasize the need for clearer academic policies and ethical frameworks to support students in making informed and responsible decisions about the use of GAI chatbots in higher education.

 Emerging AI technologies are changing teachers’ assessment practices and posing higher education institutions with novel ethical dilemmas. While frameworks and guidelines promise to align technology with moral and human values, the dilemma of how AI may impact existing valuing practices is often overlooked. To examine this gap, we conducted an interview study with university teachers from different disciplines at a university in Sweden. Following a semi-structured study design, we explored university teachers’ anticipations of AI in assessment and examined how emerging AI technologies may reconfigure the fit between values, challenges, and activities situated in everyday assessment contexts. Our findings suggest that anticipated AI, including automation and AI-mediated communication and grading, may amplify and reduce teachers’ possibilities to align activities with professional, pedagogical, and relational values and solve current challenges. In light of the study’s findings, the paper discusses potential ethical issues in the anticipated shifts from human to automated assessment and possible new and reinforced challenges brought by AI for education. 

The emergence of generative artificial intelligence (GAI) has given rise to diverse narratives about its transformative potential in higher education. Despite widespread speculation about how GAI might change teaching and learning, there is a significant gap in understanding how GAI artefacts are perceived in educational practices, particularly from the perspective of university teachers. This study investigates how GAI mediates teachers’ practices and reconfigures professional roles. Drawing on post-phenomenology and technological mediation theory, we focus on university teachers’ experiences and perceptions of GAI in higher education. Twenty-four university teachers participated in workshops involving assessment exercises with GAI-generated outputs, followed by focus group interviews discussing the challenges and opportunities posed by GAI. Findings reveal that GAI prompts teachers to reassess established practices, particularly in relation to assessment, while confronting ethical concerns regarding fairness, trust, and quality. Teachers described their initial engagement with GAI as transformative yet challenging, as they navigated uncertainties about their roles while prioritising students’ learning and development. By capturing teachers’ voices during this pivotal period, the study contributes to the growing body of research on AI's role in higher education and provides a nuanced understanding of its impact on teaching and learning.

The rise of videoconference lectures has sparked concerns about their potential negative impact on college and university student engagement. In this study, we review prior research on engagement, focusing on its behavioral and cognitive dimensions, which we investigate empirically using a novel methodology. Our analysis centers on active-learning approaches in large-group teaching settings. Contrary to concerns about potential harm, our findings reveal no evidence supporting the alleged detrimental effects. On the contrary, our results indicate that neither behavioral engagement nor course cognitive engagement is higher for in-class students, and levels of engagement may even be greater with virtual live lectures. If taken at face value, these findings carry significant pedagogical and policy implications.

While student privacy is frequently a topic of concern in studies about data-powered technologies in higher education, we still know little about handling student privacy in online proctoring systems (OPS). To better understand the challenges associated with student privacy in higher educational practice, we conducted an interview study examining various stakeholders’ understandings of privacy in OPS. We interviewed ten stakeholders–including teachers, students, and administration staff, such as the head of the department, the head of the IT department, and examination administrators–directly involved in the procurement and use of an online examination platform with proctoring features, in one of the largest universities in Scandinavia, to investigate stakeholders’ privacy perceptions, privacy concerns, privacy awareness, and perceived responsibility regarding the privacy practices of OPS. The findings show the participants perceive privacy in OPS as a seclusive and anonymous state of being, a way to control information, and an individual right. The results also point to stakeholders’ concerns regarding collecting sensitive information about the students, the possibility of information misuse, and improper access to students’ personal information. Furthermore, the study’s results identify trade-offs between the stakeholders’ concerns for privacy and the benefits of using OPS for examinations in higher education. This study underscores the need for higher education institutions to involve students and educators in procuring and deploying OPS and develop strategies for cultivating privacy awareness and responsible privacy practices. Finally, implications for developing responsible digital practices in higher education are discussed.

Emerging AI technologies are changing teachers’ assessment practices and posing higher education institutions with novel ethical dilemmas. While frameworks and guidelines promise to align technology with moral and human values, the dilemma of how AI may impact existing valuing practices is often overlooked. To examine this gap, we conducted an interview study with university teachers from different disciplines at a university in Sweden. Following a semi-structured study design, we explored university teachers’ anticipations of AI in assessment and examined how emerging AI technologies may reconfigure the fit between values, challenges, and activities situated in everyday assessment contexts. Our findings suggest that anticipated AI, including automation and AI-mediated communication and grading, may amplify and reduce teachers’ possibilities to align activities with professional, pedagogical, and relational values and solve current challenges. In light of the study’s findings, the paper discusses potential ethical issues in the anticipated shifts from human to automated assessment and possible new and reinforced challenges brought by AI for education.