Although learning analytics (LA) often processes massive data, not all courses in higher education institutions are on a large scale, such as courses for employed adult learners (EALs) or master’s students. This places LA in a new situation with small datasets. This paper explores the contemporary situation of how LA has been used for small datasets, whereby we examine how the observed LA provisions can be validated in practice, which opens up possible LA solutions for small datasets and takes a further step from previous studies to enhance this topic. By examining the field of LA, a systematic literature review on state-of-the-art LA and small datasets was conducted. Thirty relevant articles were selected for the final review. The results of the review were validated through a small-scale course for EALs at a Swedish university. The findings revealed that the methods of multiple analytical perspectives and data sources with the support of contexts and learning theories are useful for strengthening the reliability of results from small datasets. More empirical evidence is required to validate possible LA methods for small datasets. The LA cycle should be closed to be able to further assess the goodness of the models generated from small datasets.

The benefits of teacher-facing dashboards are incontestable, yet their evidence is finite in terms of long-term use, meaningful usability, and maturity level. Thus, this paper uses design science research and critical theory to design and develop TEADASH to support teachers in making decisions on teaching and learning. Three cycles of design science research and multiple small loops were implemented to develop the dashboard. The tool was then deployed and evaluated in real time with the authentic courses. Five courses from two Swedish universities were included in this study. The co-design with teachers is crucial to the applicability of this dashboard, while letting teachers use the tool during their courses is more important to help them to recognize the features they actually use and the tool’s usefulness for their teaching practices. TEADASH can address the prior matters, align with the learning design, and meet teachers’ needs. The technical and co-design aspects, as well as the advantages and challenges of applying TEADASH in practice, are also discussed here.

With the growing need for developing competence at workplaces, the number of employed adult learners is increasing in higher education institutions to follow continuing education. Often they are educated and treated as traditional students. To satisfy the learning demands of employed learners, work-integrated education has emerged to spotlight the importance of the integration of work and education in contemporary education. Many studies show that employed adult learners have different and more complex ways of learning compared to traditional students. Furthermore, employed adult learners have lacked the attention of researchers and educators to enhance their learning in general and online learning in particular. Meanwhile, online learning is a preferred way for learners who work and study in tandem. This study aims to make the online learning design for employed adult learners more effective and adaptable to their circumstances by asking the research question “How can online learning design for employed adult learners be improved?”. The case study of a course for employed adult learners was examined with a mixed method approach including interview and learning analytics. The interview data laid the groundwork for developing assumptions and hypotheses for the examination of employed adult learners’ learning patterns. Learning analytics consist of data visualization, which revealed employed adult learners’ learning patterns, and statistical tests, which inspected the validity and reliability of the patterns revealed by the log data. The log data were extracted from the learning management system, which recorded the educational activities of the learners during the course. This study exposed the pitfalls of the learning design including average to low engagement not only in learning but also in the course. As a result, the indicators to improve the online learning design for employed adult learners comprise investing in learning materials and increasing online interaction to fortify learner engagement in the course, thereby enhancing course completion. The indicators are viewed as the first step in the process of developing a proper and effective online learning design for employed adult learners. Finally, the reflection on online interaction for employed adult learners is also discussed.

COVID-19 has changed the mindset of many teachers from traditional education to online education. The increased use of learning management systems is leveraging opportunities for increased use of learner data to draw insights about the learners and the learning environment. However, typically learners are the primary beneficiaries, while teachers are quite invisible in the research of data analytics in education, although both are equally important. Thus, this paper aims to position teachers in the spotlight by differentiating between these current two definitions of learning analytics (LA) and teaching analytics (TA) and evaluating the applicability and maturity of existing analytics solutions to support teachers in making decisions on teaching and learning. A systematic literature review was conducted in relevant scientific fields. The results showed clear evidence to distinguish TA from LA and that there are only a few TA solutions and frameworks that can be applied widely or in reality. Evaluating TA solutions and frameworks needs to be attentively considered. This paper also contributes a comprehensive TA process framework that encapsulates the missing elements in the previous models and adds the recent highlights raised in the fields. The implications for research and practice are also discussed.