Predicting success in an undergraduate exercise science program using science-based admission courses

Area of Science:

• Exercise Science
• Higher Education Studies
• Educational Psychology

Background:

• Student success, including retention, progression, and graduation, is crucial in higher education.
• Research on predictors of success specifically within undergraduate Exercise Science programs is limited.
• This study addresses the need to identify factors influencing student performance in Exercise Science.

Purpose of the Study:

• To evaluate an admission policy's effectiveness in predicting student success in an undergraduate Exercise Science program.
• To identify specific prerequisite courses that predict success in core Exercise Science major courses.
• To provide data-driven insights for improving student retention and program completion rates.

Main Methods:

• Utilized regression analysis on data from 652 Exercise Science students (2012-2018).
• Collected student performance data from the University's Enterprise Information Management system.
• Controlled for performance in other courses to isolate the impact of key predictors.

Main Results:

• Performance in the introductory Exercise Science course (ES 2100) was the strongest predictor of success in required major courses.
• General education courses, including English Composition II, Precalculus, General Chemistry II Laboratory, Human Anatomy and Physiology II, and General Psychology, also significantly predicted major course performance.
• These findings held true even after controlling for performance in other academic areas.

Conclusions:

• Performance in ES 2100 and specific general education courses can effectively predict student success in the Exercise Science major.
• Identifying these predictive courses can inform the development and refinement of program admission policies.
• This research offers valuable insights for Exercise Science programs aiming to enhance student retention, progression, and graduation rates.