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A learning service computing model in Computer-Supported Collaborative Learning (CSCL)
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DOI：10.1080/10494820.2024.2443777.png)
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Abstract
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Computer-supported collaborative learning (CSCL) is a digital environment specifically designed for collaborative learning services. Computing metrics are used to measure the computational effectiveness of learning services at CSCL. User attributes, learning domains, group attributes, and learning service technologies are among the current computational metrics. Computing learning services' effectiveness can be evaluated using only one metric. Systemic learning service computing based on these four groups of metrics has received minimal discussion. The next problem is the lack of explanation of learning and service analysis methods for these metrics. There are difficulties in measuring and analyzing the effectiveness of computing learning services at CSCL. Research problem question how is an effective a learning service computing model in CSCL. Developing a learning service computing model in CSCL is the objective of this research. Service computing models and evaluation methods are included in the outputs to assess the effectiveness of learning services at CSCL. This research applies Design Research Methodology (DRM) and a model development strategy based on the dynamic system modeling process. This research applies a CSCL environment with the name smart learning environment. Model testing results demonstrate the effectiveness of computing learning services on CSCL.
Keywords:
Learning service computing model
computation metrics
Computer-Supported Collaborative Learning (CSCL)
learning evaluation methods
computing technology
collaborative learning
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