Proposal Abstract

Like many higher education institutions, Coker College admits a diverse student body. This diversity extends to the spectrum of mathematical ability of the newly admitted class. Traditionally, secondary education grade point averages alongside national standardized test scores were used as the primary metrics to determining the mathematics course that a student would be placed. This method of placement frequently resulted in students that were erroneously placed as indicated by poor first semester performances. Given the relatively modest size of the incoming class, this was deemed particularly troublesome. Consequently, the first of the two authors sought to improve student placement outcomes by devising a placement exam that whose questions were chosen using data mining techniques. An unsurprising byproduct of this effort was an increased number of students enrolled in remedial classes for which the institution was not well-staffed enough to handle. To aid with the newly discovered need for remediation, the second of the two authors created an online transition course that was made openly available to all students that did not achieve sufficiently high placement exam scores to place out of a basic mathematics course. By recording all student activity on the placement exam and transition course, the faculty is able to analyze trends and adapt instruction and preparation quickly to best serve incoming students. Instruction, placement, and the entrance exam will continue to be revised as more collected information creates a clearer picture of incoming Coker students. The presentation will close with a discussion exploring adaptations of these methods to other disciplines.

Location

Room 1220

Publication Type and Release Option

Presentation (Open Access)

 
Mar 28th, 10:00 AM Mar 28th, 10:45 AM

College Mathematics: Placement and Remediation through Data Mining

Room 1220

Like many higher education institutions, Coker College admits a diverse student body. This diversity extends to the spectrum of mathematical ability of the newly admitted class. Traditionally, secondary education grade point averages alongside national standardized test scores were used as the primary metrics to determining the mathematics course that a student would be placed. This method of placement frequently resulted in students that were erroneously placed as indicated by poor first semester performances. Given the relatively modest size of the incoming class, this was deemed particularly troublesome. Consequently, the first of the two authors sought to improve student placement outcomes by devising a placement exam that whose questions were chosen using data mining techniques. An unsurprising byproduct of this effort was an increased number of students enrolled in remedial classes for which the institution was not well-staffed enough to handle. To aid with the newly discovered need for remediation, the second of the two authors created an online transition course that was made openly available to all students that did not achieve sufficiently high placement exam scores to place out of a basic mathematics course. By recording all student activity on the placement exam and transition course, the faculty is able to analyze trends and adapt instruction and preparation quickly to best serve incoming students. Instruction, placement, and the entrance exam will continue to be revised as more collected information creates a clearer picture of incoming Coker students. The presentation will close with a discussion exploring adaptations of these methods to other disciplines.