MyMathLab is an online tool for teaching and learning mathematics. The system is designed to give students immediate feedback when their answers are entered. In addition, MyMathLab includes different adaptive learning resources. These include study plans, study plan assignments, and personalized homework. Intermediate Algebra is an introductory course offered at Qatar University to all non-science students, and in particular, to Art, Business, Education, etc. students. The present paper seeks to identify the relationships between the online activities practiced through MyMathLab and the final grade in the course. In addition to this goal, the factors that affected students' performance will be addressed based on the academic data available. The dataset used in this project is related to 54 female students enrolled in an Intermediate Algebra course offered in two consecutive semesters (Fall 2015 & Spring 2016) during the academic year 2015/2016. Two data mining classification algorithms, decision trees and logistic regression, were applied in order to classify students based on certain rules and to extract certain patterns that describe students' performance. The decision tree model managed to classify 90% of the data and several rules were extracted that helped in understanding students' performance in different assessment tools. The regression model managed to classify only 75% of the dataset.
