Quasi-experimental design was used in this research. Both courses had several features in common. All were
taught by the same instructor and had the same objectives, content, and homework assignments. The instructor
was an experienced professor who has been teaching the three credit hour introductory statistics courses since
1970. Different editions of the same textbook (Gravetter and Wallnau, 2000) have been used in this class for
more than eight years. The instructor worked with two doctoral level assistants across seven different offerings
of the course that were trained to teach the CAI portion. With the exception of the two graduate assistants, the
CAI components were identical from quarter to quarter. Course content included descriptive statistics, frequency
distribution, central tendency and variability, hypothesis testing, t tests, correlation, regression and nonparametric
statistics (chi-square).
Students in all courses took the same multiple-choice Midterm and Final exams. Both exams consisted of 62
multiple-choice questions. Of the 62 questions of the Midterm and Final examinations, 50 items tested
generalized learning (Hannafin and Carney, 1991; Worthington et al., 1996), however, 12 items (those questions
reflecting in the CAI session) tested domain-specific learning (Worthington et al., 1996). While Midterm
examination was administered after the 7th week of the course (middle of the quarter) to each session, Final
examination was administered to each section at the end of the quarter, (15th week). Generalized learning items
included definitions, interpretations and discriminate of terms and concepts, calculations of statistics, and
interpretations of results.
Students in the Lecture-plus-CAI section attended 40-minute class each week and completed systematically
computerized exercises and tutorials. After learning concept and theory in Lecture-only part of the course,
students who choose Lecture-plus-CAI section came to the computer lab and lab instructors show them how to
make practice on real data set. For example, students learn and understand theoretical base of the measure of
central tendency and what it means in the Lecture-only class. And then in Lab, students learn how to run
measure of central tendency, get computer outputs, analyze and interpret them appropriately. Software used to
provide these exercises was a data analysis package, SPSS (Statistical Package for Social Sciences).