Self-directed learning is generally considered a key competence in higher education. To enable self-directed learning, assessment practices increasingly embrace assessment for learning rather than the assessment of learning, shifting the focus from grades and scores to provision of rich, narrative, and personalized feedback. Students are expected…

Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…

This paper explores the affordances and constraints of STEM faculty members' instructional data-use practices and how they engage students (or not) in reflection around their own learning data. We found faculty used a wide variety of instructional data-use practices. We also found several constraints that influenced their instructional data-use…

Background: Data-driven educational technology solutions have the potential to support teachers in different tasks, such as the designing and orchestration of collaborative learning activities. When designing, such solutions can improve teacher understanding of how learning designs impact student learning and behaviour; and guide them to refine…

This study investigates the possibility of utilizing online learning data to design face-to-face activities in a flipped classroom. We focus on heterogeneous group formation for effective collaborative learning. Fifty-three undergraduate students (18 males, 35 females) participated in this study, and 8 students (3 males, 5 females) among them…

As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…

Problem based learning (PBL) supports the development of transversal skills and could underpin the training of a workforce competent to withstand the constant generation of new information. However, the application of PBL is still facing challenges, as educators are usually unsure how to structure student-centred courses, how to monitor students'…

Purpose: The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward…

Dramatic shifts brought about by globalization, technological innovation, and data-driven decision-making practices are immensely reflected in the landscape of 21st century higher education. Learning Analytics or LA is an emerging multidisciplinary, technological practice with the ultimate goal of producing effective learning to improve students'…

The objective of the research is to develop a methodology to analyse a set of data extracted from a learning management system, in order to implement a dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of analysing 9,257 records extracted…

The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report…

The purpose of this review is to investigate the trends in the body of research on machine learning in educational technologies, published between 2007 and 2017. The criteria for article selection were as follows: (1) study on machine learning in educational/learning technologies, (2) published between 2007-2017, (3) published in a peer-reviewed…

Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…

This article presents the findings of a systematic qualitative analysis of research in the ethics of digital trace data use in learning and education. From the resulting analysis of 77 peer-reviewed studies, we (1) map the characteristics of research by study type, academic community, institutional setting, and national context; (2) identify the…

Purpose: This paper aims to present a review of case studies on the use of learning analytics in Science, Technology, Engineering, (Arts), and Mathematics (or STE[A]M) education. It covers the features and trends of learning analytics practices as revealed in case studies. Design/methodology/approach: A total of 34 case studies published from 2013…