Exploring The Use Of Cognitive Tests To Predict Programming Performance: A Systematic Literature Review

The ability to predict the future programming performance of prospective students is beneficial to school administration and students. This can help decrease the dropout rate and save valuable resources. A variety of types of features have been explored to predict programming performance since the 1960s and still, research is ongoing in this field. Cognitive abilities are one of those features that don’t depend on programming knowledge and is a non-subjective measure of ability. To investigate the growing claim that cognitive abilities aren’t reliable predictors for programming performance, this literature review examines the use of cognitive abilities in predicting programming performance from 1960 to 2020. We highlight top reported correlations of cognitive tests with programming performance, though, we see contradictory findings of the tests and their significance across the literature. The Cattell-Horn-Carroll theory is utilized to categorize the tests and provide future researchers with common vocabulary and framework to choose from alternative tests. We view our work as a benchmark comparing the strength of correlation of cognitive tests with programming ability, a guide for future researchers in their choice of cognitive tests and address some of the shortcomings we identified in the field. This will help us in the endeavour to explain what programming fundamentally is and thus help in the career advising process.