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Self-efficacy and behavior patterns of learners using a real-time collaboration system developed for group
Ting-Chia Hsu1, Hal Abelson2, Evan Patton2
1Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei City, 10610 Taiwan.
International Journal of Computer-Supported Collaborative Learning
|January 10, 2022
Summary
A new real-time collaboration (RTC) version of MIT App Inventor (MAI) enhances block-based programming (BBP) for co-creation. Computer Science majors showed higher self-efficacy in collaborative programming environments.
Area of Science:
- Computer Science Education
- Human-Computer Interaction
- Learning Analytics
Background:
- Co-creation in programming education is challenging for non-collocated learners.
- MIT App Inventor (MAI) is a popular block-based programming (BBP) environment.
- Real-time collaboration (RTC) tools can address challenges in remote group work.
Purpose of the Study:
- To implement and evaluate an RTC version of MAI for co-creation.
- To investigate the impact of disciplinary background on self-efficacy and collaborative behavior in RTC-enabled MAI.
- To analyze learner behavior patterns using learning analytics.
Main Methods:
- Developed and implemented an RTC version of MIT App Inventor.
- Conducted an empirical study comparing learners with different disciplinary backgrounds (CS majors vs. non-CS majors).
- Utilized learning analytics to examine collaborative and individual behavior patterns.
Main Results:
- RTC enabled simultaneous multi-user programming, fostering joint engagement.
- Overall Computer Programming Self-Efficacy (CPSE) was similar for individual and multi-user programming.
- Homogeneous CS-major groups in RTC showed higher CPSE than non-CS-major and heterogeneous groups.
Conclusions:
- Collaborative engagement with MAI, particularly in RTC, is beneficial, especially for CS majors.
- The RTC design facilitates parallel task execution and collaborative learning.
- Further research into RTC design for collaborative programming environments is warranted.
Keywords:
Behavior and sequential analysisBlock-based programming learningLearning analyticsMIT App InventorOnline real-time collaborationMore Related Videos
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