Can We Use Technology to Predict Student Success and Failure in Higher Education (64912)

Session Information:

Session: On Demand
Room: Virtual Video Presentation
Presentation Type:Virtual Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

The aim of this research was to identify those technological factors that contribute to success/failure in Higher Education. Many factors contribute to a students’ success or lack of success in higher education. Some of these will be individual factors such as personality, motivation, previous educational experiences and many others. Other factors that contribute to success or otherwise, will be focused on the institution and the technology, courses and facilities that are provided The data was collected automatically via the technologies used by the university. These included student use of the computer network; student access to online learning materials; the number of times the library was used; use of the virtual learning environment, and finally the degree to which student support services and careers advice was utilised. The students (N = 301) in this study were all enrolled on a BSc (Hons) Psychology programme at a University in the North of England. In addition to the behavioural data, student academic performance was also assessed using the existing assessments for the taught programme. The findings revealed that although some of the predicted relationships were confirmed, for example library use was a good predictor of academic performance, other predictions, for example use of the virtual learning environment, were not predictive of success. However, although a general model predicting student performance was not forthcoming, it was found that the data was useful in predicting “at-risk” students, i.e those individuals likely to drop out before completing their studies.

Peter Eachus, University of Salford, United Kingdom

About the Presenter(s)
Dr Peter Eachus is a University Administration at University of Salford in United Kingdom

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00