Predicting academic performance: The role of cognition, motivation and learning approaches. A neural network analysis

The current chapter starts from the idea that phenomena such as student learning, academic performance and educational research topics in general are complex in nature. Consequently, research methods that can deal with this complexity are needed. We introduce neural network analysis as one method that has the potential to deal with this complexity as it can handle large numbers of variables as well as non-linear relationships when predicting a specific target. The chapter starts with introducing neural network analysis on a conceptual level and continuous with an illustration of how students’ academic performance at the end of the first year of university can be predicted based on students’ cognitive capacities, motivation and study approaches. To conclude, both the results of the illustration as well as the implications of the method of analysis are discussed.status: publishe