Research in Science Education

, Volume 48, Issue 1, pp 151–163 | Cite as

Predicting Student Success in a Major’s Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

  • E. David Thompson
  • Bethany V. Bowling
  • Ross E. Markle


Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson’s Classroom Test of Scientific Reasoning in predicting success in a major’s introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.


Introductory biology First-year students Predictive model Scientific reasoning Student success Retention 



The authors are very grateful to the students who agreed to participate in this project.


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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • E. David Thompson
    • 1
  • Bethany V. Bowling
    • 1
  • Ross E. Markle
    • 2
  1. 1.Department of Biological Sciences, 204D Natural Science CenterNorthern Kentucky UniversityHighland HeightsUSA
  2. 2.Educational Testing ServicePrincetonUSA

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