Using database technology to improve STEM student retention: A total quality management approach to early alert and intervention

• Main Authors: Sam Khoury, Kouroush Jenab, Donald Staub, Mark Rajai
• Format: Article
• Language: English
• Published: Growing Science 2012-04-01
• Series: Management Science Letters
• Subjects: STEM; Early Alert; Database Technology; TQM
• Online Access: http://www.growingscience.com/msl/Vol2/msl_2011_107.pdf
• ISSN: 1923-9335; 1923-9343

Students at risk of dropping out of Science, Technology, Engineering, and Mathematics (STEM) programs often display signs that indicate they are at risk. A need exists to identify at risk STEM students early and to develop and implement effective intervention strategies that utilize the Total Quality Management (TQM) approach. Most of all, a database system is needed to track this early intervention process, if retention rates are to be improved. To address this need at a small community college in North Carolina, a system was developed and underwent a pilot study in Fall 2009 and Spring 2010. The two pilot groups were compared to the two control groups to identify differences in retention, course credit completion rates, and grade point averages (GPA). The first pilot group displayed no significant differences, while the second pilot group displayed significant differences in most of the areas analyzed in the study, indicating a database system can be used to improve STEM student retention. While the second of the two pilot groups displayed promising results, managerial and logistical issues, such as less than optimal instructor involvement, impeded success were identified. This paper will describe the design, implementation, and the preliminary results of this study and outlines the need for further research that confirms these preliminary findings.