Learning from Learning Analytics: How Much Do We Know About Patterns of Student Engagement?

2021 ◽  
pp. 163-197
Author(s):  
Belinda A. Chiera ◽  
Małgorzata W. Korolkiewicz ◽  
Lisa J. Schultz
Author(s):  
Erkan Er ◽  
Cristina Villa-Torrano ◽  
Yannis Dimitriadis ◽  
Dragan Gasevic ◽  
Miguel L. Bote-Lorenzo ◽  
...  

Big Data ◽  
2016 ◽  
pp. 1717-1735
Author(s):  
Paul Prinsloo ◽  
Sharon Slade

Learning analytics is an emerging but rapidly growing field seen as offering unquestionable benefit to higher education institutions and students alike. Indeed, given its huge potential to transform the student experience, it could be argued that higher education has a duty to use learning analytics. In the flurry of excitement and eagerness to develop ever slicker predictive systems, few pause to consider whether the increasing use of student data also leads to increasing concerns. This chapter argues that the issue is not whether higher education should use student data, but under which conditions, for what purpose, for whose benefit, and in ways in which students may be actively involved. The authors explore issues including the constructs of general data and student data, and the scope for student responsibility in the collection, analysis and use of their data. An example of student engagement in practice reviews the policy created by the Open University in 2014. The chapter concludes with an exploration of general principles for a new deal on student data in learning analytics.


Author(s):  
Prerna Lal

The online education environment is becoming complex day-by-day. Nowadays, educational institutes are offering various types of courses online to a large number of students having a diverse background, with the flexibility of time and geography. This results in creating a large repository of online data regarding courses, students and instructors. These data may be in text, audio or video format. This chapter is an attempt to understand the use of Learning Analytics that advocates for analysis of these data and to understand the learning process better in terms of student engagement, pedagogy, content and assessment. Educational institutes can utilize the intelligence revealed by learning analytics processes, and communicate them to those involved in strategic institutional planning.


2019 ◽  
Vol 10 (2) ◽  
pp. 47-58 ◽  
Author(s):  
Jill Lawrence ◽  
Alice Brown ◽  
Petrea Redmond ◽  
Marita Basson

Universities increasingly implement online delivery to strengthen students’ access and flexibility. However, they often do so with limited understanding of the impact of online pedagogy on student engagement. To explore these issues, a research project was conducted investigating the use of course-specific learning analytics to ‘nudge’ students into engaging more actively in their courses. Drawing on perspectives emanating from communication and critical theories, the research involved a staged intervention strategy conducted across three courses (n=892) focussing on a range of timely, strategic communication interventions. Research findings revealed benefits for students who felt supported by explicit expectation management and the strategic use of early nudging to enhance their prioritisation of key course-specific resources. Academics benefited by making use of nudging templates/principles to increase student engagement in their courses. The course-specific context meant that academics and students explicitly shared ways of working in the one place where learners ultimately succeed – the course.    


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