Online learning activities provide opportunities to enhance learners’ engagement and active learning. However, designing effective online learning activities for adults is a critical issue. This study tackles challenges faced in adult online learning, such as limited information literacy, low engagement levels, an emphasis on knowledge transmission rather than skill development, and difficulties in reconstructing learning communities. By employing the classical Activity Theory, the study synthesized the published research from Web of Science (WoS) and CNKI to propose a model for designing adult online learning activities. This model outlines specific steps for the design process, implementing the Open University Integration Platform (OUIP) and adhering to principles of activity theory. The most noticeable finding to extract from this study is that instructional design should consider the diverse needs of adult learners with well-organized and balanced activities to enhance their learning experience, driven by robust learning theories and human cognition principles.

This Full-Length Research Paper deals with the effectiveness of training using educational robots on developing various skills for metacognitive thinking and engagement. Educational Robotics (ER) is a subject that aims to introduce children to robotics and programming through hands-on activities starting at a young age. There is evidence that ER plays a crucial role in enhancing students' academic achievement, cognitive abilities, and programming skills. Despite the growing interest in implementing ER to promote learning outcomes, there has been far too little focus on demonstrating ER effects on the development of certain types of thinking abilities (e.g. reflective thinking), and social skills that include engagement and its pedagogical implications. This study aims to evaluate the effects of ER on STEM students' engagement and reflective thinking. A sample of 24 middle school students (age range: 11–13 years) took part in an intensive ER-Lab for 6 sessions (3 weeks) by using open-source hardware and software kits through articulated robots and mobile robots. The research data in this study are drawn from two main sources on a five-point Likert scale: engagement questionnaire, and reflective thinking scale. The results of this investigation showed that students keep pleasure experience interacting and performing robotics activities. The results also showed a remarkable superiority of the students' reflective thinking skills on the dimensions (habitual action, understanding, reflection, and critical reflection). Students reflected their expectations and challenges after ER training with sets of recommendations accordingly. This study contributes to robotics' STEM education by expanding the scope of prior research to provide evidence of ER impact on 21st-century skills, particularly, reflective thinking skills. Based on the study's findings, we suggest developing robotic activities in different ER learning scenarios for a better understanding of the engagement processes. We recommend expanding the pedagogical possibilities of ER in improving extensive thinking skills, adaptation, and encouraging socialization and collaboration. This encourages exploring the feedback, reflection, and needs of the teachers and parents in terms of the impact of ER training on students thinking skills.

The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.

Many students suffer from a lack of motivation and interest in doing their homework. This paper introduced a micro-design approach for implementing gamification of learning assignments, led to the extraction of the procedures for gamifying assignment with the micro-design approach, and a suggested conceptual design model called “Snowflake”. The most interesting finding was that micro-level analysis has a positive impact on a gamified assignment which begins with the identification of raw objects such as quizzes, lessons, learning objects and resources.