Learning assessment in the age of big data: Learning analytics in higher education

• Published in: Cogent Education Vol. 10; no. 1
• Main Author: Caspari-Sadeghi, Sima
• Format: Journal Article
• Language: English
• Published: Abingdon Cogent 31-12-2023; Cogent OA; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Big Data; College Faculty; Data Analysis; Data Use; Educational research; Evaluation Methods; Feedback (Response); Higher Education; Intervention; Learning Analytics; Measurement; Prediction; Prevention; technology-enhanced assessment
• ISSN: 2331-186X; 2331-186X
• DOI: 10.1080/2331186X.2022.2162697

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication applications. Meanwhile, it is acknowledged that education lacks computational infrastructure and human capacity to fully exploit the potential of big data. This paper explores the use of Learning Analytics (LA) in higher education for measurement purposes. Four main LA functions in the assessment are outlined: (a) monitoring and analysis, (b) automated feedback, (c) prediction, prevention, and intervention, and (d) new forms of assessment. The paper concludes by discussing the challenges of adopting and upscaling LA as well as the implications for instructors in higher education.