**
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 students’ 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.