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RETRACTED ARTICLE: Cognitive learning performance assessment and analysis with CSCL applied on the NetGuru platform and CSPL applied on the TAoD platform for the network experiment class

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This article was retracted on 10 October 2022

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Abstract

How to find the best learning performance in the network experimental course is an important research topic. Therefore, collaborative learning and personalized learning have been applied in traditional classes for a similar significance regardless of how times change and advancements develop. We used the computer-supported collaborative learning (CSCL) pedagogy with NetGuru network experimental platform and the computer-supported personalized learning (CSPL) pedagogy with the teaching assistant on demand (TAoD) network experimental platform, respectively, in the “Network Engineering Lab (1)” course to assess the distinctions in impacts for the two methods. The objective students were four junior classes of ordinary students in the department of Computer Information and Network Engineering. As a rule, one should think about that CSCL pedagogy is better than CSPL pedagogy because of discussion and collaborative learning between students for learning performances. Nonetheless, the fact that the missing and late rates of students in technical and vocational college are a lot higher that makes adopting CSCL pedagogy difficult. Therefore, we designed and made some assistant materials of “graphical-based teaching powerpoint slides,” “animations of packet transmission process for network protocol theories,” and “Customized IP-oriented template-based assignments (simplified as CIPOTA or template-based assignment)” to be applied to compare and analyze the network practices of CSCL-based on NetGuru platform and CSPL-based on TAoD platform. We also design “satisfaction scale of learning performance” to analyze the students’ satisfaction degrees of learning performance with the pedagogy (CSCL or CSPL), the assignment form (normal assignment or template-based assignment), and the learning satisfaction (CSCL or CSPL combines the normal assignment or template-based assignment). They were for the most part being utilized to demonstrate that TAoD platform-based CSPL pedagogy is truly appropriate for network experiment courses. And the CSPL pedagogy is not more terrible than the CSCL pedagogy and may even bring about optimizing learning results for the learning of network experiment course.

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Acknowledgements

This work was supported by the Ministry of Science and Technology, R.O.C., under Grant MOST 107-2511-H-262-001-.

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Authors and Affiliations

  1. Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taoyuan City, Taiwan

    Yung-Hui Chen

  2. Department of Business Administration, Lunghwa University of Science and Technology, Taoyuan City, Taiwan

    Wei-Chun Lee

  3. Department of Electrical Engineering, Yuan Ze University, Taoyuan City, Taiwan

    Chun-Hsiung Tseng

  4. Department of Computer Science and Information Engineering, St. John’s University, New Taipei City, Taiwan

    Lawrence Y. Deng

  5. Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin County, Taiwan

    Chuan-Yu Chang

  6. Department of Electrical Engineering Information Network Group, Lunghwa Univerisity of Science and Technology, Taoyuan City, Taiwan

    Long-He Lee

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  1. Yung-Hui Chen
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  2. Wei-Chun Lee
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  3. Chun-Hsiung Tseng
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  4. Lawrence Y. Deng
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  5. Chuan-Yu Chang
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  6. Long-He Lee
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Correspondence to Chun-Hsiung Tseng.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11227-022-04855-z

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Chen, YH., Lee, WC., Tseng, CH. et al. RETRACTED ARTICLE: Cognitive learning performance assessment and analysis with CSCL applied on the NetGuru platform and CSPL applied on the TAoD platform for the network experiment class. J Supercomput 76, 16–46 (2020). https://doi.org/10.1007/s11227-019-02836-3

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  • DOI: https://doi.org/10.1007/s11227-019-02836-3

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