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

Abstract

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.



Author Information
Peter Eachus, University of Salford, United Kingdom

Paper Information
Conference: ACP2023
Stream: Psychology and Education

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Posted by James Alexander Gordon