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Exploring Initiative as a Signal of Knowledge Co-Construction During Collaborative Problem Solving.

Cynthia Howard1, Barbara Di Eugenio2, Pamela Jordan3

  • 1Department of Computer and Mathematical Sciences, Lewis University.

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Summary
This summary is machine-generated.

Task initiative shifts in peer dialogues indicate collaborative learning. This finding helps develop instructional software to support student collaboration and knowledge co-construction (KCC).

Keywords:
Computer Science educationDialog modelingEducational technology to support collaborationPeer learning

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Area of Science:

  • Educational Technology
  • Computer Science Education
  • Cognitive Science

Background:

  • Peer interaction supports learning, with knowledge co-construction (KCC) as a key mechanism.
  • KCC is abstract, posing challenges for developing supportive instructional software.
  • Identifying measurable indicators of KCC is crucial for software development.

Purpose of the Study:

  • To analyze peer dialogs in introductory Computer Science to find measurable indicators of KCC.
  • To investigate the relationship between task initiative shifts, KCC, and learning outcomes.
  • To explore the potential of task initiative shifts for modeling productive peer collaboration in software.

Main Methods:

  • Analysis of a corpus of peer dialogs from introductory Computer Science courses.
  • Identification and quantification of "task initiative shifts" within dialogs.
  • Correlation analysis between task initiative shifts, KCC episodes, and student learning (pre-test scores).

Main Results:

  • Task initiative shifts correlate positively with both KCC episodes and learning.
  • Task initiative shifts occur more frequently during KCC episodes.
  • Task initiative shifts within KCC episodes correlate with learning for low pre-testers; total shifts correlate for high pre-testers.

Conclusions:

  • Task initiative shifts serve as a measurable indicator of productive peer collaboration and KCC.
  • Task initiative shifts are a more accessible construct than KCC for modeling in instructional software.
  • This research provides a foundation for developing intelligent tutoring systems that foster collaborative learning.