Prediction and assessment of student learning outcomes in structural mechanics a decision support of integrating data mining and fuzzy logic

This paper focuses on the issue of continuous improvement on educational outcomes and takes the engineering mechanics course as an example to help students overcome their learning difficulties. A decision support system based on data mining and fuzzy logic is proposed to predict the student learning outcomes. The methodologies involves four steps: fuzzy theory to identify the factors on learning outcomes; data mining to construct influence diagram; machine learning to establish the fuzzy inference relations; and the model to predict the exam scores at the beginning of course and thereby to help students enhance their scores according to their weakness.