This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We also reviewed 12 data ethics frameworks drawn from different sectors. Finally, we reviewed an extensive and diverse body of literature about data practices, research ethics, data ethics and critical data literacy, in order to develop a transversal model that can be adopted across higher education. To promote and support ethical approaches to the collection and use of data, ethics training must go beyond securing informed consent to enable a critical understanding of the techno-centric environment and the intersecting hierarchies of power embedded in technology and data. By fostering ethics as a method, educators can enable research that protects vulnerable groups and empower communities.

Educational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions' scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and  appropriate investments.

In the wake of COVID-19, study conditions in Europe have changed dramatically. To limit contact between students and teachers, since March 2020 teaching has largely taken place digitally (remotely via digital means) and in private. Because the success of digital learning likely relies on many factors beyond good digital infrastructure conditions, this article focuses on which aspects, at both the teacher and the student levels, promote digital learning success. The large-scale student survey "Studying in Times of the Corona Pandemic" conducted at German universities and universities of applied sciences in the summer semester of 2020 offers data on how COVID-19 has affected several aspects of university studying in Germany. Here, we consider this data within the theoretical framework "theory of transactional distance" introduced by Moore (in: Moore (ed) Handbook of distance education, Routledge, 2018), according to which the success of digital teaching is influenced by dialogue, structure, and learner autonomy. Based on various regression analyses, our results show that several (digital) framework conditions must be created on both the teacher and student levels to achieve sufficient digital learning success. In this sense, our findings provide guidance on which aspects institutions of higher education should focus on when developing or updating their digitalization strategies. In accordance with collaborative learning approaches a key factor for learning success appears to be enabling peer-to-peer interactions. This finding supports our prediction that the possibility of engaging in interactive learning activities is crucial for students' learning experience, as it might reduce the perception of transactional distance and allow for social exchange. The strongest predictor of students' learning success turned out to be the (perceived) digital competencies of the teachers. This finding clearly emphasizes that teachers must be qualified to address the very specific challenges of teaching in digital contexts and indicates that universities may need to implement more teacher qualification programs.

Micro-credentials are gaining traction as viable vehicles for rapid upskilling of the workforce in the twenty-first century and potential pathways for gaining employment for some students. The primary purpose of the current systematic review was to understand the current conceptions and discourses of micro-credentials in higher education and to identify the opportunities and challenges in adopting micro-credentials in higher education. The review also aimed to develop a need-driven micro-credentials framework that demonstrates the value of micro-credentials to stakeholders, i.e., learners, higher education institutions, employers, and government agencies. Key findings revealed that there are various stakeholders' needs and expectations. The learner wants short, practical, and up-to-date courses for their chosen career path, education institutions emphasise accreditation for building trust, employers want clarity regarding the competencies gained through micro-credentials, and government bodies expect higher graduate employability with lower tuition fees. Key findings revealed that implementing micro-credentials can be disruptive in the higher education sector and present several challenges. However, these challenges are likely to be mitigated by increased collaboration among stakeholders. The review has revealed several outstanding research questions critical for the success of micro-credentials as significant pathways to supplement traditional degree programmes. The research presented in the article has implications for policy development to guide the implementation of micro-credentials in the higher education sector.

As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI prediction models focus on the development and optimization of the accuracy of AI algorithms rather than applying AI models to provide student with in-time and continuous feedback and improve the students' learning quality. To fill this gap, this research integrated an AI performance prediction model with learning analytics approaches with a goal to improve student learning effects in a collaborative learning context. Quasi-experimental research was conducted in an online engineering course to examine the differences of students' collaborative learning effect with and without the support of the integrated approach. Results showed that the integrated approach increased student engagement, improved collaborative learning performances, and strengthen student satisfactions about learning. This research made contributions to proposing an integrated approach of AI models and learning analytics (LA) feedback and providing paradigmatic implications for future development of AI-driven learning analytics.

Little is known about how to develop frameworks for using AI to support learning in English Literature within higher education. This paper presents research that developed a framework for employing AI in the study of the fourteenth-century English poet Geoffrey Chaucer. Studying Chaucer presents challenges for modern readers, as it requires an understanding of his literary style, spoken Middle English, and the cultural and social context of the late medieval period. The research investigated how AI tools, such as ChatGPT and Amazon Polly, could support the study of Chaucer. It found that while AI can assist with students' initial familiarisation with Chaucer's poetry, it lacks the depth and rigour necessary for more advanced study. As a result, students and lecturers still rely on traditional resources, including authoritative print-based and digital scholarly editions. Consequently, the research developed a framework for studying Chaucer's poetry that integrates the guided use of AI through active learning with additional supporting resources, such as digital scholarly editions.

Higher education institutions may adopt various approaches to the pedagogic principles and methods used in teaching sustainable development in business and marketing courses. These methods can include the utilisation of digital technologies and online communication to facilitate distance learning and fast access to relevant information. Changes towards the digitalisation of the learning environment especially gained popularity during the Covid-19 pandemic. In the post-pandemic period, digitalisation continues to facilitate the learning and teaching processes. However, the implementation of digital technologies, besides technological expertise, requires appropriate theoretical frameworks for understanding how learning is developed. This study explores connectivism theory applied to the pedagogic practices of knowledge dissemination concerning sustainable development in the fields of business and marketing. Connectivism embraces knowledge as a network where the learner, with the help of digital technologies, develops mental connections between pieces of information during interaction with various information sources. This qualitative research empirically explores the principles of connectivism embedded in the learning and teaching of a university course conducted online. The research findings indicate that connectivism may be a suitable conceptual framework that motivates learners to develop knowledge through digital enablers, discussions and social networking and to make connections to sustainability concepts. The principles of connectivism may help instructors to develop a learning environment where learners add understandings to their previous knowledge on sustainability through online interactions and by accessing digital knowledge sources. This study makes several interdisciplinary contributions by deepening the insights into digital pedagogic methods and approaches for the facilitation of learning, which may be of interest to academic and other pedagogic practitioners.

This study explores a student-centered teaching method in postgraduate courses. Teacher-centered classroom teaching cannot fully stimulate learning initiative and enthusiasm of students. Student-centered means that students actively learn and construct knowledge by participating in teaching activities. This study presents a student-centered online-offline hybrid teaching method, which adopts student-centered case-based teaching and online-offline case discussion in the postgraduate courses of computer science. The latest engineering cases are integrated into teaching and a case library is constructed. Taking the digital image processing course as an example, student-centered teaching allows students to choose what to learn and how to learn. Case-based teaching makes students better understand the application of theory of knowledge. It can introduce multiple perspectives, promote understanding and reflection on problems, and help students develop higher-level thinking, analysis, and synthesis skills. This study explores online-offline case discussion method in the student-centered teaching and proposes the principles of case design of postgraduate courses. Revised Bloom's taxonomy is used for teaching assessment. The actual teaching effect shows that student-centered case-based teaching and online-offline case discussion have achieved better teaching effect.

Research has shown that learners' stress and mental distress are linked to poorer academic outcomes. A better understanding of stress and mental distress experiences during study could foster more nuanced course and intervention design which additionally teaches learners how to navigate through to protect their academic performance. The current study draws on data collected via validated self-reported questionnaires completed by final year undergraduate students (n = 318) at a large distance education university. We examined how common features of stress, depression and anxiety link to each other using a network analysis of reported symptoms. The results included findings demonstrating the symptoms with the greatest relative importance to the network. Specifically, these included the stress symptom 'I found it difficult to relax' and the depression symptom 'I was unable to become enthusiastic about anything'. The findings could help institutions design interventions that directly correspond to common features of students' stress and distress experiences.

This article reports on a study analysing changes in the use of digital technologies and working from home during the COVID-19 crisis and the impact of these changes on the wellbeing of five female university lecturers from Australia and Sweden. Applying collaborative autoethnographical methods, this study employed Weick's sensemaking framework to explore how the academics made sense of these sudden changes. The Positive emotion, Engagement, Relationships, Meaning, and Accomplishment (PERMA) wellbeing framework was also employed to explore the effect of these changes on the academics' wellbeing. Findings from the reflective narratives show that after the initial experiences of stress, each university lecturer was able to adapt and navigate the online teaching environment during the pandemic. However, the time constraints in preparing and adapting to online teaching, and working from home, were experienced by some of the university lecturers as highly stressful and isolating which impacted their sense of wellbeing. Even so, working from home was recognized as a positive experience, providing time for research, hobbies, and time with family. This study addresses a gap in current knowledge by examining the impact of the sudden transition to online teaching and learning had on academic wellbeing as conceptualised through the PERMA framework. In addition, by applying Weick's sensemaking framework, this study provides a unique perspective around how academics made sense of the sudden switch to online teaching and learning during COVID-19.

This research addresses an identified need to further understand digital literacies (DL) and whether undergraduate students view DL as being important in their lives and in their learning. Using a cross-sectional survey sent to a stratified random sample of 2500 undergraduates representative of the overall student population at a medium-sized Canadian undergraduate university (survey response rate of 19.8%,  = 496), we explored the relationships between social media and digital literacies, particularly in different disciplinary contexts. We also explored the ways in which students report using social media in their university learning, showing that students value social media for collaboration, discussion, information finding and sharing, and practise activities related to their learning. Additionally, we examined the importance students place on DL, and how they perceive and rate their own abilities with digital literacies across three domains: procedural and technical, cognitive, and sociocultural. Findings illustrate an observable gap between the high importance that students place on digital literacies (including DL for social media) in their learning and their lives and the lack of coverage students reported receiving about these topics in their undergraduate education. Based on the study's findings, we discuss the specific ways that those in the higher education community can address this gap by engaging with and fostering development of digital literacies within specific disciplinary and professional contexts, and in interdisciplinary or transdisciplinary learning settings across the curriculum.

Professional development (PD) is a key element for enhancing the quality of academic teaching. An increasing number of PD activities have moved to blended and online formats, especially since the COVID-19 pandemic. Due to the desire, potential, and need for collaboration among educators to learn from innovative and best practices, several institutions have started to pool their resources and expertise together and have started to implement cross-institutional and cross-national online professional development (OPD). The questions of what type of a (cross-)institutional OPD educators might prefer, and whether educators learn effectively from (and with) peers in such cross-cultural context have not been adequately explored empirically. In this case-study across three European countries, we explored the lived experiences of 86 educators as a result of a cross-institutional OPD. Using a mixed methods design approach our pre-post findings indicated that, on average, participants made substantial gains in knowledge. In addition, several cultural differences were evident in the expectations and lived experiences in ODP, as well as the intention to transfer what had been learned into one's own practice of action. This study indicates that while substantial economic and pedagogical affordances are provided with cross-institutional OPD, cultural differences in context might impact the extent to which educators implement lessons learned from OPD.

In recent decades, higher education institutions around the world have come to depend on complex digital infrastructures. In addition to registration, financial, and other operations platforms, digital classroom tools with built-in learning analytics capacities underpin many course delivery options. Taken together, these intersecting digital systems collect vast amounts of data from students, staff, and faculty. Educators' work environments-and knowledge about their work environments-have been shifted by this rise in pervasive datafication. In this paper, we overview the ways faculty in a variety of institutional status positions and geographic locales understand this shift and make sense of the datafied infrastructures of their institutions. We present findings from a comparative case study (CCS) of university educators in six countries, examining participants' knowledge, practices, experiences, and perspectives in relation to datafication, while tracing patterns across contexts. We draw on individual, systemic, and historical axes of comparison to demonstrate that in spite of structural barriers to educator data literacy, professionals teaching in higher education do have strong and informed ethical and pedagogical perspectives on datafication that warrant greater attention. Our study suggests a distinction between the understandings educators have of data processes, or technical specifics of datafication on campuses, and their understanding of big picture data paradigms and ethical implications. Educators were found to be far more knowledgeable and comfortable in paradigm discussions than they were in process ones, partly due to structural barriers that limit their involvement at the process level.

Flexible learning addresses students' needs for more flexibility and autonomy in shaping their learning process, and is often realised through online technologies in a blended learning design. While higher education institutions are increasingly considering replacing classroom time and offering more blended learning, current research is limited regarding its effectiveness and modifying design factors. This study analysed a flexible study programme with 133 courses in a blended learning design in different disciplines over more than 4 years with a mixed-methods approach. In the analysed flexible study programme, classroom instruction time was reduced by 51% and replaced with an online learning environment in a blended learning format ( students = 278). Student achievement was compared to the conventional study format ( students = 1068). The estimated summary effect size for the 133 blended learning courses analysed was close to, but not significantly different from, zero ( = - 0.0562,  = 0.3684). Although overall effectiveness was equivalent to the conventional study format, considerable variance in the effect sizes between the courses was observed. Based on the relative effect sizes of the courses and data from detailed analyses and surveys, heterogeneity can be explained by differences in the implementation quality of the educational design factors. Our results indicate that when implementing flexible study programmes in a blended learning design, particular attention should be paid to the following educational design principles: adequate course structure and guidance for students, activating learning tasks, stimulating interaction and social presence of teachers, and timely feedback on learning process and outcomes.

The influence of personality traits on educational outcomes has been widely recognized and studied. Research has explored its effects on factors such as student satisfaction, academic anxiety, and dishonesty, particularly during the COVID-19 pandemic. However, there has been a lack of studies comparing the learning behaviors and performance of students with different personality traits during the pre, during, and post-COVID-19 lockdown periods. This study fills this gap by analyzing the differences in academic metrics, such as class grades and assignment submissions, among students with varying personality traits during different lockdown periods. Our research, based on a dataset of 282 graduate students in the USA, identified correlations and patterns between lockdown periods, personality traits, and academic metrics. For example, the class grades and the rate of late submissions were affected by different lockdown periods. Students with lower degree in extraversion and agreeableness made less attempts in assignment submissions. These findings can assist educators in identifying impacted students and developing effective teaching strategies at early stage in future incidents.

This paper aims to evaluate and discuss the digital competence of academics at universities, to identify challenges and define recommendations for policy. This study was conducted through collaboration between the Joint Research Centre (JRC) of the European Commission and Metared of the Universia Foundation, surveying 30,407 participants who present the perceptions of their own digital competence levels. These self-reflections took place in universities in seven countries, namely Argentina, Brazil, Colombia, Chile, Peru, Mexico and Portugal, and used the Check-In tool, which consists of 22 questions based on the European Framework for the Digital Competence of Educators-or 'DigCompEdu' framework. A descriptive statistical analysis was performed, followed by a qualitative evaluation. Almost 70% of the academics have an average intermediate level of competence when the data is aggregated, with results varying in each DigCompEdu area according to the specific question asked. There is no significant difference between young and senior academics, as well as between men and women. The results present a discussion of whether the age and gender of educators and their work environment have an impact on their digital competence level, and at the same time highlights the areas in which educators perceive themselves to be most and least competent. It shows how the amount of institutional support that is offered affects the academics' perceptions of their level of digital competence. On the basis of the results, recommendations are presented for higher-education institutions, with the aim of supporting the professional development of their academics.

As a consequence of the COVID-19 pandemic, most courses at a large technical university were adapted so that students had a free choice of whether to attend lectures on-site or online; in addition, in many courses, lecture recordings were available. At the subsequent exam session, over 17,000 student-survey responses were collected regarding attendance choices, learning behavior, interest in the course, perception of the exam, and recommendations to future students. A total of 27 learner attributes and their relationships were investigated. In addition, conditional attributes and free-response statements were analyzed, and the students' exam grades were retrieved to gauge their performance. We found only minute differences with respect to exam performance, but the analysis indicates distinctly different preferences and constraints in taking advantage of learning opportunities. We also found some indications that performance differences might be larger for interactive-engagement courses. The results of the analysis may be key to answering why at many universities, faculty report that live-lecture attendance has decreased more strongly than expected with the availability of new, virtual attendance modes.

In this study we measured the effect of COIL on intercultural competence development using a quasi-experimental design. Our sample consisted of 108 undergraduate students from two universities, one located in the Netherlands (NL) and one in the United States (US). Students' self-reported intercultural competence was measured using a pre-post survey which included the Cultural Intelligence Scale (CQS) and Multicultural Personality Questionnaire (MPQ). Qualitative data were collected to complement our quantitative findings and to give a deeper insight into the student experience. The data showed a significantly bigger increase in intercultural competence for the US experimental group compared to the US control group, supporting our hypothesis that COIL develops intercultural competence. This difference was not observed for the NL students, possibly due to the NL control group being exposed to other international input during the course.

In recent years, COVID-19 policy measures massively affected university teaching. Seeking an effective and viable way to transform their lecture material into asynchronous online settings, many lecturers relied on prerecorded video lectures. Whereas researchers in fact recommend implementing prompts to ensure students process those video lectures sufficiently, open questions about the types of prompts and role of students' engagement remain. We thus conducted an online field experiment with teacher students at a German university ( = 124; 73 female, 49 male). According to the randomly assigned experimental conditions, the online video lecture on topic was supplemented by (A) notes prompts ( = 31), (B) principle-based self-explanation prompts ( = 36), (C) elaboration-based self-explanation prompts ( = 29), and (D) both principle- and elaboration-based self-explanation prompts ( = 28). We found that the lecture fostered learning outcomes about its content regardless of the type of prompt. The type of prompt did induce different types of self-explanations, but had no significant effect on learning outcomes. What indeed positively and significantly affected learning outcomes were the students' self-explanation quality and their persistence (i.e., actual participation in a delayed posttest). Finally, the self-reported number of perceived interruptions negatively affected learning outcomes. Our findings thus provide ecologically valid empirical support for how fruitful it is for students to engage themselves in self-explaining and to avoid interruptions when learning from asynchronous online video lectures.

Digital games are considered relevant in higher education due to their ability to foster authentic, active and experiential learning opportunities that are of importance in engineering education. However, as a relatively new pedagogical tool, there is the need to understand the perceptions of engineering students as well as to identify factors that influence their adoption of games for learning. So far, only a few studies have investigated the perceptions of higher education students towards learning games and even fewer for engineering students. To bridge this research gap, the current study utilises a mixed-method research design to identify factors that influence the adoption of digital learning games by engineering students as well as their overall perceptions of the use of games for engineering education. Results from the analysed quantitative and qualitative data suggest that engineering students value fun and engagement as well as relevance to the curriculum as factors that would influence their intentions to use digital games for engineering education. Students also showed openness to the use of digital games for learning, but resistance to their use for assessment. These findings have implications for the design of games and classroom deployment of games, as these provide insights to game designers and educators on the factors to consider in the design and classroom deployment of games, respectively.

In the evolving realm of medical education, where artificial intelligence (AI) technologies play an increasingly pivotal role, embedding AI ethics within educational frameworks has become crucial. This scoping review explores the breadth of literature concerning ethical considerations for teaching with AI in medical education settings. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, the team analyzed 82 peer-reviewed English-language articles published between 2018 and October 2023, sourced from PubMed, Embase, and Web of Science. The review presents insights into the geographic distribution of studies, publication trends, article types, common keywords, areas of focus, and ethical considerations. Ethical considerations are framed around the core principles of autonomy, beneficence, non-maleficence, justice, and transparency. Emerging themes and notable gaps are identified, offering suggested directions for future research. Review articles were found to be the most common study type, and "artificial intelligence" and "education" were the most frequently recurring keywords in the articles. The articles primarily focused on (a) incorporating AI in medical education, (b) AI ethical principles in medical education, and (c) ChatGPT in healthcare education. Ethical concerns raised in the articles centered on privacy, bias, informed consent, and algorithmic transparency, with many offering implications for curriculum development. These findings underscore the significance of integrating AI tools as instructional aids to enhance medical education, improve student learning experiences, and address the ethical challenges associated with their use in instructional settings. Future research opportunities include refining standardized competencies for AI in medical education, developing evidence-based curricula, and conducting longitudinal studies to assess AI's long-term impact on learning outcomes.