Multi-layer Adaptive Fuzzy Inference System for Predicting Student Performance in Online Higher Education
Keywords:
Computational Intelligence, fuzzy system, hybrid intelligent systems, Artificial Neural Network, multi-layer adaptive fuzzy inference system, student performance, online education, e-learningAbstract
Research on student performance prediction has evolved from the early application of statistical techniques to later use of computational techniques. Results in this field are varied thus, we have to take advantage of previous research results. This study proposes a Multi-layer Adaptive Neuro-Fuzzy Inference System (MANFIS) for student performance prediction in online Higher Education settings. To generate the MANFIS, we used a dataset integrated by the scores obtained by students in four online Higher Education courses. The MANFIS prediction accuracy was statistically compared against the accuracies of three neural networks. The results indicate that MANFIS is an alternative model to predict student performance in online Higher Education settings