Use of Intelligent Tutor in Post-Secondary Mathematics Educationi the United Arab Emirates

 

ABSTRACT

The purpose of this paper is to determine potential identifiers of studentsí academic success in foundation mathematics course from the data logs of the intelligent tutor Assessment for Learning using Knowledge Spaces (ALEKS). A cross-sectional study design was used.  A sample of 152 records, which accounts to approximately 60% of the population, was extracted from the data-logs of the intelligent tutor, ALEKS. Two-step clustering, correlation and regression analysis, Chi-square analysis and ANOVA tests were applied to address the research questions. The data-logs of ALEKS include information about number of topics practiced and number of topics mastered by each student. A derived attribute, which is the ratio of number of topics mastered to number of topics practiced is found to be a predictor of final marks in the foundation mathematics course. This variable is represented by the name mtop. Cluster classification based on this derived attribute resulted into three groups of students for which the mean values of the variable mtop are 0.80, 0.66 and 0.53 respectively. A moderately strong, positive and significant correlation was found between mtop and the final exam marks.