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Daily Online Testing in Large Classes: Boosting College Performance while Reducing Achievement Gaps

Overview of attention for article published in PLOS ONE, November 2013
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Title
Daily Online Testing in Large Classes: Boosting College Performance while Reducing Achievement Gaps
Published in
PLOS ONE, November 2013
DOI 10.1371/journal.pone.0079774
Pubmed ID
Authors

James W. Pennebaker, Samuel D. Gosling, Jason D. Ferrell

Abstract

An in-class computer-based system, that included daily online testing, was introduced to two large university classes. We examined subsequent improvements in academic performance and reductions in the achievement gaps between lower- and upper-middle class students in academic performance. Students (N = 901) brought laptop computers to classes and took daily quizzes that provided immediate and personalized feedback. Student performance was compared with the same data for traditional classes taught previously by the same instructors (N = 935). Exam performance was approximately half a letter grade above previous semesters, based on comparisons of identical questions asked from earlier years. Students in the experimental classes performed better in other classes, both in the semester they took the course and in subsequent semester classes. The new system resulted in a 50% reduction in the achievement gap as measured by grades among students of different social classes. These findings suggest that frequent consequential quizzing should be used routinely in large lecture courses to improve performance in class and in other concurrent and subsequent courses.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
United States 12 7%
Netherlands 1 <1%
Italy 1 <1%
Germany 1 <1%
Canada 1 <1%
Brazil 1 <1%
Japan 1 <1%
Romania 1 <1%
Unknown 146 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 18%
Researcher 26 16%
Professor > Associate Professor 17 10%
Student > Master 15 9%
Student > Bachelor 15 9%
Other 45 27%
Unknown 17 10%
Readers by discipline Count As %
Psychology 35 21%
Social Sciences 29 18%
Agricultural and Biological Sciences 13 8%
Computer Science 11 7%
Medicine and Dentistry 8 5%
Other 43 26%
Unknown 26 16%