Article detail · 2015
An Intelligent Approach to Educational Data Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks
Journal
Educational Sciences: Theory & PracticeISSN 1303-0485
- Year
- 2015
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Educational Sciences: Theory & Practice
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The participants’ transcript scores were used as the target variables and the two methods were employed to test the predictors that affected these variables. The results show that the multilayer perceptron artificial neural network outperformed the radial basis artificial neural network in terms of predictive ability. Although the findings suggest that research in quantitative educational science should be conducted by using the former artificial neural network method, additional supporting evidence needs to be collected in related studies.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
26 citations
OpenAlex cited_by_count (cache / database)
19 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
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