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A case study report on integrating statistics, problem-based learning, and computerized data analysis.

T T Hewett1, D V Porpora

  • 1Department of Psychology/Sociology/Anthropology, Drexel University, Philadelphia, PA 19104, USA. hewett@drexel.edu

Behavior Research Methods, Instruments, & Computers : a Journal of the Psychonomic Society, Inc
|September 25, 1999
PubMed
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Integrating statistics into computer-assisted data analysis courses enhances student learning. This approach moves beyond rote memorization, enabling students to effectively apply statistical methods independently.

Area of Science:

  • Educational Psychology
  • Data Science Pedagogy

Background:

  • Traditional statistics courses often fail to foster practical application skills.
  • Undergraduate psychology and sociology majors require robust data analysis capabilities.

Purpose of the Study:

  • To evaluate the pedagogical benefits of integrating statistics into computer-assisted data analysis.
  • To assess the effectiveness of a two-term integrated course at Drexel University.
  • To determine if students can apply statistical procedures independently after the course.

Main Methods:

  • A comparative pedagogical approach was implemented over ten years.
  • The study involved undergraduate psychology and sociology majors.
  • The curriculum integrated statistical concepts within hands-on, problem-based computer-assisted data analysis.

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Main Results:

  • Students demonstrated an improved ability to apply statistical procedures.
  • The integrated approach fostered independent problem-solving skills.
  • Positive student engagement and learning outcomes were observed.

Conclusions:

  • Teaching statistics integrated with computer-assisted data analysis offers significant pedagogical advantages.
  • This model enhances students' capacity for independent application of statistical knowledge.
  • The Drexel University model serves as a successful example for statistical education.