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The numbers tell it all: students don't like numbers!
Bob Uttl1, Carmela A White1, Alain Morin1
1Department of Psychology, Mount Royal University, Calgary, Alberta, Canada.
Plos One
|December 21, 2013
Summary
Undergraduate students show very low interest in quantitative courses, especially statistics, compared to non-quantitative ones. Women reported less interest than men in these essential analytical subjects.
Area of Science:
- Psychology
- Higher Education Studies
- Educational Psychology
Background:
- Student interest in quantitative versus non-quantitative courses is crucial for higher education but understudied.
- Prior research on course interest is confounded by end-of-course evaluations (Student Evaluation of Teaching - SET), not initial interest.
- This study uniquely assesses first-year undergraduate interest in quantitative courses before enrollment.
Purpose of the Study:
- To investigate first-year undergraduate students' interest in quantitative versus non-quantitative psychology courses.
- To identify potential gender differences in interest towards quantitative coursework.
- To explore the implications of student interest levels for course evaluation and curriculum development.
Main Methods:
- Survey administered to 340 undergraduate students.
- Students rated their interest in 44 described psychology courses.
- Analysis focused on interest differences between quantitative and non-quantitative courses and by gender.
Main Results:
- Student interest in quantitative courses, particularly statistics, was significantly lower than in non-quantitative courses (mean difference nearly 6 SDs).
- Women expressed less interest in quantitative courses compared to men.
- Low interest suggests potential issues with course enrollment and future career paths in quantitative fields.
Conclusions:
- Standardized Student Evaluation of Teaching (SET) metrics may be inappropriate for comparing quantitative and non-quantitative courses.
- Using uniform SET standards could incentivize teaching to evaluations rather than student learning.
- Universities prioritizing student learning should reconsider reliance on SETs, while those prioritizing satisfaction might reduce quantitative offerings.
- Lack of interest in quantitative courses may deter students from pursuing graduate studies and independent data analysis skills.
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