Predicting introductory programming performance: A multi-institutional multivariate study

Bergin, Susan and Reilly, Ronan (2006) Predicting introductory programming performance: A multi-institutional multivariate study. pp. 303-323.

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Official URL: http://www.tandfonline.com/doi/abs/10.1080/0899340...

Abstract

A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

Item Type: Article
Depositing User: Colin Lowry
Date Deposited: 29 Nov 2015 17:46
Last Modified: 29 Nov 2015 17:46
URI: http://eprints.teachingandlearning.ie/id/eprint/1772

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