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Social media platforms offer many educational possibilities, but they also create challenges associated with their business models. One increasingly relevant challenge, especially in the context of teacher education and schools, is personal data privacy. When considering social media and data privacy in education, taking into account culture-specific aspects in different countries, such as legal frameworks, user attitudes, and cultural values, is uncommon. This cross-sectional study explores the perceptions of pre-service teachers (N= 225) from universities in four countries (Germany, New Zealand, Spain, and the USA) concerning educational and professional social media use, as well as data privacy awareness and practices. Data were collected via a survey and analyzed through descriptive and inferential statistics. Results indicate that along with common belief in social media’s educational potential, data privacy concerns were present, knowledge related to data privacy was lacking, and differences existed between participants from the different universities. We discuss these results in relation to legal frameworks, user attitudes, and cultural values concerning social media data privacy, and consider implications for research, practice, and policy.

This paper presents a multiple case study on the use of digital storytelling to support the development of reflection and digital skills in professional education. Students from two universities, one group studying health and social care, the other training to be teachers, were asked to produce two artefacts, at the beginning and end of their respective modules, in which they reflected on the aspects of professional and personal learning. The artefacts, some of which were produced in groups, others by individual students, were analysed for recurring themes, levels of reflection and digital competence, particularly in the use of open educational resources. Findings from the analysis support the use of digital storytelling methods to develop a range of key skills pertinent to professional education in general but concluded that the deeper levels of reflection may be most evident in individual artefacts produced in the later stages of professional education. The study provides some important insights for teaching and learning in professional education as it suggests that digital storytelling provides a highly engaging way of introducing both reflective and open educational practices.

By the end of 2020, over 16,300 Massive Open Online Courses (MOOCs) from 950 universities worldwide had enrolled over 180 million students. Interest in MOOCs has been matched by significant research on the topic, including a considerable number of reviews. This study uses Machine Learning techniques and human expert supervision to generate a comprehensive systematic literature mapping review that overcomes some limitations of the traditional ones and provides a broader overview of the content and main topics studied in the specialized literature devoted to MOOCs. The sample consisted of 6320 publications automatically classified within six research topics, denominated by human experts: institutional approach, pedagogical approach, evaluation, analytics, participation, and educational resources. The content analysis of the topics identified was conducted using visual network analysis, which supported the identification of different thematic sub-clusters and endorsed the classification. Results from the review show that the lowest production of MOOC papers is within the topics of the pedagogical approach and educational resources. In contrast, participation and evaluation are the most frequent ones. In addition, the most cited papers are on the topics of analytics and resources, being the pedagogical approach and the institutional approach the less cited. This highlights the need for more MOOC research from a pedagogical perspective and calls upon the presence of educators.

Due to the Covid-19 pandemic that spread globally in 2020, higher education courses were subsequently offered in fully remote, online formats. A plethora of primary studies began investigating a range of topics exploring teaching and learning in higher education, particularly during the initial semester. In order to provide an overview and initial understanding of this emerging research field, a systematic mapping review was conducted that collates and describes the characteristics of 282 primary empirical studies. Findings reveal that research was carried out mostly descriptively and cross-sectionally, focusing predominantly on undergraduate students and their perceptions of teaching and learning during the pandemic. Studies originate from a broad range of countries, are overwhelmingly published open access, and largely focused on the fields of Health & Welfareand Natural Sciences, Mathematics & Statistics. Educational technology used for emergency remote teaching are most often synchronous collaborative tools, used in combination with text-based tools. The findings are discussed against pre-pandemic research on educational technology use in higher education teaching and learning, and perspectives for further research are provided.

According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.