Where Is the Teacher in Data Analytics in Education?

Evaluating the Maturity of Analytics Solutions and Frameworks Supporting Teachers

Abstract

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.