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.

This exploratory experimental study investigates the impact of motivational strategies based on the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS‐V) model on online learners' academic performance, motivation, volition, and course interest. The research was conducted over an 11‐week semester with 122 undergraduate online learners within two groups. One group received a traditional e‐course, while the other group was offered the course with extra motivational strategies derived from the ARCS‐V model. The results revealed that the group who used motivational strategies showed significantly higher gains in motivation, academic performance, and course interest scores. However, there were no significant differences between the groups regarding the volition. Furthermore, the motivation and interest variables were measured with Attention, Relevance, Confidence, and Satisfaction subscales of the ARCS‐V model. In terms of interest variable, there was only a statistically significant difference on the Attention subscale. Regarding motivation variable, the results also showed a statistically significant difference on the attention, confidence, and satisfaction subsections of the ARCS‐V model. The findings of the present study offer insights into ARCSV model‐based research by examining the effects of the model as a valid and reliable framework for online learning environments. The implications and directions for future research are then discussed.

In the 21st century, when the knowledge-based economy is steering improvement and development, STEM education has gained increasing momentum and importance. This study aims to identify the current trends in STEM education, and also explores and identifies research trends and patterns in articles published between 2014 and 2016 on STEM education through a systematic review study. The research findings indicate that interest in STEM education in scholarly venues has witnessed a marked increase since 2014, with researchers preferring mostly quantitative, conceptual/descriptive, qualitative, mixed and practice-based research methods. In contrast, no interest is currently being shown in data mining and analytical methodologies. The patterns being in STEM education are identified as follows: (1) the scope of the STEM education, (2) the need for a new curriculum for the STEM in higher education, (3) gender studies in STEM education and (4) the need for student-centred future studies on the effectiveness of STEM education. Keywords: STEM, research trends, systematic review, content analysis, text mining.

Blockchain is an online decentralized and distributed ledger technology that has the ability to keep and track records in a safe, verifiable, and transparent manner. More significantly, it has an infrastructure that is compatible with Web 3.0, which offers great potential for lifelong learning. This chapter explains the different modalities of learning (formal, non-formal, informal), blockchain technology, and its current use in educational processes. Based on the findings, the authors suggest that blockchain technology can be used to connect and interlink different educational experiences that occur in different educational modalities, enabling us to evaluate educational processes holistically and thus promote lifelong learning through the use of cutting-edge technologies.