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Abstract. Studies carried out in classroom-based learning context, have consistently shown a positive relation between students' conscientiousness and their academic success. We hypothesize that time management and regularity are main constructing blocks of students' conscientiousness in the context of online education. In online education, despite intuitive arguments supporting on-demand courses as more flexible delivery of knowledge, completion rate is higher in the courses with rigid temporal constraints and structure. In this study, we further investigate how students' regularity affects their learning outcome in MOOCs. We propose several measures to quantify students regularity. We validate accuracy of these measures as predictors of students' performance in the course.

Education is experiencing a paradigm shift towards blended learning models in technology-enhanced learning (TEL). Despite the potential benefits of blended learning, it also entails additional complexity in terms of monitoring, awareness and reflection, as learning happens across different spaces and modalities. In recent years, literature on Learning Analytics (LA) and Educational Data Mining (EDM) has gained momentum and started to address the issue. To provide a clear picture of the current state of the research on the topic and to outline open research gaps, this paper presents a systematic literature review of the stateof-the-art of research in LA and EDM on monitoring, awareness and reflection in blended TEL scenarios. The search included six main academic databases in TEL that were enriched with the proceedings of the workshop on 'Awareness and Reflection in TEL' (ARTEL), resulting in 1089 papers out of which 40 papers were included in the final analysis.

In this integrated study of dynamics in MOOCs discussion forums, we analyze the interplay of temporal patterns, discussion content, and the social structure emerging from the communication using mixed methods. A special focus is on the yet under-explored aspect of time dynamics and influence of the course structure on forum participation. Our analyses show dependencies between the course structure (video opening time and assignment deadlines) and the overall forum activity whereas such a clear link could only be partially observed considering the discussion content. For analyzing the social dimension we apply role modeling techniques from social network analysis. While the types of user roles based on connection patterns are relatively stable over time, the high fluctuation of active contributors lead to frequent changes from active to passive roles during the course. However, while most users do not create many social connections they can play an important role in the content dimension triggering discussions on the course subject. Finally, we show that forum activity level can be predicted one week in advance based on the course structure, forum activity history and attributes of the communication network which enables identification of periods when increased tutor supports in the forum is necessary.