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Evaluating the Efficacy of and Preference for Interactive Computer Training with Student-Generated Examples.

Sylvia C Aquino1, Stephanie A Hood1, Tara A Fahmie2

  • 1Marquette University, Milwaukee, WI USA.

Behavior Analysis in Practice
|January 10, 2025
PubMed
Summary
This summary is machine-generated.

Interactive computer training (ICT) using peer-generated examples was preferred by students over other formats but did not improve knowledge assessments. Further improvements to ICT are discussed for behavior analysis training.

Keywords:
Higher educationInteractive computer trainingTeaching

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Area of Science:

  • Behavior analysis
  • Educational psychology
  • Instructional design

Background:

  • Undergraduate behavior analysis training often aims for effective and preferred teaching methods.
  • Peer-generated examples were previously found to be preferred over textbook examples but did not enhance knowledge acquisition.

Purpose of the Study:

  • To investigate the efficacy and preference of interactive computer training (ICT) embedding peer-generated examples for behavior analysis concepts.
  • To extend previous findings on peer-generated examples by incorporating interactive elements.

Main Methods:

  • Peer-generated examples were integrated into an interactive computer training (ICT) module.
  • The ICT module included features like active responding, prompt fading, automated feedback, and practice with examples and non-examples.
  • Student preference and knowledge assessment performance were compared to video and textual examples.

Main Results:

  • Interactive computer training (ICT) did not yield significant improvements in knowledge assessments.
  • Students showed a preference for ICT over video and textual examples.
  • Specific interactive features within the ICT were identified as contributing to student preference.

Conclusions:

  • While ICT with peer-generated examples is preferred, its efficacy in improving knowledge requires further enhancement.
  • Future research should focus on refining ICT features to boost both preference and learning outcomes in behavior analysis education.