Making Better Decisions on Placement in Mathematics Courses

• Activity Number: 256
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Education
• Author(s): W. Stephenson* and Chen Hua and Elgin Johnston
• Companies: Iowa State University and Iowa State University and Iowa State University
• Keywords: ALEKS, Mathematics Placement, Logistic Regression

Abstract

ALEKS (Assessment and LEarning in Knowledge Spaces) is educational software based on knowledge space theory (Doignon and Falmagne, 1999, 2011; Falmagne, Koppen, Villano, Doignon, and Johanessen, 1990). ALEKS software claims to be able to assess an individual's mastery of certain types of problems and to be able to indicate what topics the individual is prepared to learn. One of the ALEKS assessments looks at various areas of mathematics with the intent of assessing mastery of those areas and indicating readiness for further study. The ALEKS mathematics assessment is increasingly being used to assist in the placement of students into appropriate courses that require prerequisite knowledge of certain areas of mathematics. This paper looks at the relationship between students' ALEKS mathematics assessment scores and their success in mathematics and statistics courses. Logistic regression is used to model the relationship between the ALEKS mathematics assessment score, or sub-score, and the probability of "success" in a specific mathematics or statistics course. Different levels of "success", from simply passing the course to attaining a specific grade are investigated.