This study intends to explore the current trends in the field of distance education research 331 articles was reviewed. Mainly content analysis was employed to be able to analyze the current research. Also, a social network analysis (SNA) was used to interpret the interrelationship between keywords indicated in these articles. Themes were developed and the content of the articles in the selected journals were coded according to categories derived from earlier studies.The results were interpreted using descriptive analysis (frequencies) and social network analysis. The reporting of the results were organized into the following categories: research areas, theoretical and conceptual frameworks, variables, methods, models, strategies, data collection and analysis methods, and the participants. The study also identified the most commonly used keywords, and the most frequently cited authors and studies in distance education. The findings obtained in this study may be useful in the exploration of potential research areas and identification of neglected areas in the field of distance education.

Student authentication and authorship checking systems are intended to help teachers address cheating and plagiarism. This study set out to investigate higher education teachers' perceptions of the prevalence and types of cheating in their courses with a focus on the possible changes that might come about as a result of an increased use of eassessment, ways of addressing cheating, and how the use of student authentication and authorship checking systems might impact on assessment practice. This study was carried out within the context of the project TeSLA (an Adaptive Trust-based e-assessment System for Learning) which is developing a system intended for integration within an institution's Virtual Learning Environment (VLE) offering a variety of instruments to assure student authentication and authorship checking. Data was collected at two universities that were trialling the TeSLA system, one in Turkey, where the main modes of teaching are face-toface teaching and distance education, and one in Bulgaria, where the main modes of teaching are face-to-face teaching and blended learning. The study used questionnaires and interviews, building on existing TeSLA project evaluation activities and extending these to explore the specific areas we wished to examine in more depth. In three of the four contexts cheating was seen by teachers as a serious and growing problem, the exception was the distance education context where the teachers believed that the existing procedures were effective in controlling cheating. Most teachers in all four contexts expected cheating to become a greater problem with increased use of eassessment. Student authentication was not seen as a major problem in any of the contexts, as this was felt to be well controlled through face-to-face proctored assessments, though the problem of assuring effective authentication was seen by many teachers as a barrier to increased use of e-assessment. Authorship checking was seen as a major issue in all contexts, as copying and pasting from the web, ghost writing and plagiarism were all reported as widely prevalent, and authorship checking was seen as becoming even more important with increased use of e-assessment. Teachers identified a third category of cheating behaviours, which was the accessing of information from other students, from written materials, and from the internet during assessments. Teachers identified a number of approaches to addressing the problem of cheating: education, technology, assessment design, sanctions, policy, and surveillance. Whilst technology was not seen as the most important approach to prevention, student authentication and authorship checking systems were seen as relevant in terms of reducing reliance on face-to-face proctored examinations, and in improving the quality of assessment through supporting the employment of a wider range of assessment methods. The development of authorship checking based on computational linguistic (Continued on next page)

Artificial intelligence (AI) has penetrated every layer of our lives, and education is not immune to the effects of AI. In this regard, this study examines AI studies in education in half a century (1970–2020) through a systematic review approach and benefits from social network analysis and text-mining approaches. Accordingly, the research identifies three research clusters (1) artificial intelligence, (2) pedagogical, and (3) technological issues, and suggests five broad research themes which are (1) adaptive learning and personalization of education through AI-based practices, (2) deep learning and machine Learning algorithms for online learning processes, (3) Educational human-AI interaction, (4) educational use of AI-generated data, and (5) AI in higher education. The study also highlights that ethics in AI studies is an ignored research area.