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Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm

Received: 25 October 2021    Accepted: 11 November 2021    Published: 20 January 2022
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Abstract

Teamwork has been one of the effective responses to the changes over the years in the world of today. Teamwork is being relied upon as a preferred performance arrangement to fulfill visions, execute and achieve goals in all sectors. It is also one of the most important elements in continuous improvement systems, as it facilitates the sharing of information, problem solving and the development of employee responsibility. This study was on an intelligent coaching agent that modeled team performance using the Supervised Learning algorithm. The Object Oriented System Analysis and Design Methodology was used. For effective implementation of this study, some web application languages were used and these includes; Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), MySQL, Cascaded Style Sheet (CSS), Java Script, Dream weaver, and Fireworks. Dream weaver is an HTML-based application that is used to generate graphical user interfaces. This study was able to arrive at a system that will remove biases in performance evaluation since the performance appraisal is automatic; each task has been assigned a weighted score, so as soon as an employee performs the task the system automatically scores him/her. Making it easy to track individual performance as well as team performance. The system developed utilizes supervised learning to monitor the task executions and determine the weight score for the task before scoring the team. This system will help those that are worthy of keeping their jobs keep it and help improve employees that need to work on some specific areas to develop themselves as plainly revealed. The purpose of this study which is to demonstrate an event based performance approach via the design and implementation of intelligent coaching agents within a team training framework via supervised learning was achieved and the result shows positive impacts on team’s performance.

Published in American Journal of Artificial Intelligence (Volume 6, Issue 1)
DOI 10.11648/j.ajai.20220601.11
Page(s) 1-9
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Intelligent Agent, Coaching, Team, Human Teamwork, Proactive, Behaviors, Performance, Task Supervised Learning

References
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[6] Albatish, I., Mosa, M. J., &Naser S. A. S. (2018). An Intelligent Training System on ARDUINO. International Journal of Engineering and Information Systems, 2 (1), 236-245.
[7] Munawar, S., Toor, S. K., Aslam, M. &Aimeur, E. (2019). PACA-ITS: A Multi- A Agent System for Intelligent Virtual Laboratory Courses. Journal of Applied Sciences (9) 5084.
[8] Tabrez, S., Agrawal S., & Hayes, B. (2019). Explanation-Based Reward Coaching to Improve Human Performance via Reinforcement Learning. Paper presented at the 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 249 -257.
[9] Xiao, Z., Zhou, M. X., & Fu, W. (2019). Who Should Be My Teammates: Using A Conversational Agent to Understand Individuals and Help Teaming. Paper presented at the 24th International Conference on Intelligent User Interfaces., NY, USA.
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[15] Brusilovsky, P. &Peylo, C. (2003). Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education (13), 156–169. IOS Press.
[16] Capuano, N., Mqrsella, M., &Salemo, S. (2000). ABITS: An Agent Based Intelligent Tutoring System for Distance Learning. Proceedings of the Intelligent Tutoring System, Montreal Canada, June 19-23, 2000.
[17] Carter, E. & Blank, G. D. (2013). An Intelligent Tutoring System to Teach Debugging. Paper presented at the 16th International Conference on Artificial Intelligence in Education. Memphis, USA.
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Cite This Article
  • APA Style

    Chidi Ukamaka Betrand, Sylvanus Okwudili Anigbogu, Oluchukwu Uzoamaka Ekwealor, Ifeoma MaryAnn Orji. (2022). Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm. American Journal of Artificial Intelligence, 6(1), 1-9. https://doi.org/10.11648/j.ajai.20220601.11

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    ACS Style

    Chidi Ukamaka Betrand; Sylvanus Okwudili Anigbogu; Oluchukwu Uzoamaka Ekwealor; Ifeoma MaryAnn Orji. Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm. Am. J. Artif. Intell. 2022, 6(1), 1-9. doi: 10.11648/j.ajai.20220601.11

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    AMA Style

    Chidi Ukamaka Betrand, Sylvanus Okwudili Anigbogu, Oluchukwu Uzoamaka Ekwealor, Ifeoma MaryAnn Orji. Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm. Am J Artif Intell. 2022;6(1):1-9. doi: 10.11648/j.ajai.20220601.11

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  • @article{10.11648/j.ajai.20220601.11,
      author = {Chidi Ukamaka Betrand and Sylvanus Okwudili Anigbogu and Oluchukwu Uzoamaka Ekwealor and Ifeoma MaryAnn Orji},
      title = {Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm},
      journal = {American Journal of Artificial Intelligence},
      volume = {6},
      number = {1},
      pages = {1-9},
      doi = {10.11648/j.ajai.20220601.11},
      url = {https://doi.org/10.11648/j.ajai.20220601.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajai.20220601.11},
      abstract = {Teamwork has been one of the effective responses to the changes over the years in the world of today. Teamwork is being relied upon as a preferred performance arrangement to fulfill visions, execute and achieve goals in all sectors. It is also one of the most important elements in continuous improvement systems, as it facilitates the sharing of information, problem solving and the development of employee responsibility. This study was on an intelligent coaching agent that modeled team performance using the Supervised Learning algorithm. The Object Oriented System Analysis and Design Methodology was used. For effective implementation of this study, some web application languages were used and these includes; Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), MySQL, Cascaded Style Sheet (CSS), Java Script, Dream weaver, and Fireworks. Dream weaver is an HTML-based application that is used to generate graphical user interfaces. This study was able to arrive at a system that will remove biases in performance evaluation since the performance appraisal is automatic; each task has been assigned a weighted score, so as soon as an employee performs the task the system automatically scores him/her. Making it easy to track individual performance as well as team performance. The system developed utilizes supervised learning to monitor the task executions and determine the weight score for the task before scoring the team. This system will help those that are worthy of keeping their jobs keep it and help improve employees that need to work on some specific areas to develop themselves as plainly revealed. The purpose of this study which is to demonstrate an event based performance approach via the design and implementation of intelligent coaching agents within a team training framework via supervised learning was achieved and the result shows positive impacts on team’s performance.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Intelligent Coaching Agent for Enhancing Proactive Behaviors in Human Teamwork Using Supervised Learning Algorithm
    AU  - Chidi Ukamaka Betrand
    AU  - Sylvanus Okwudili Anigbogu
    AU  - Oluchukwu Uzoamaka Ekwealor
    AU  - Ifeoma MaryAnn Orji
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    DO  - 10.11648/j.ajai.20220601.11
    T2  - American Journal of Artificial Intelligence
    JF  - American Journal of Artificial Intelligence
    JO  - American Journal of Artificial Intelligence
    SP  - 1
    EP  - 9
    PB  - Science Publishing Group
    SN  - 2639-9733
    UR  - https://doi.org/10.11648/j.ajai.20220601.11
    AB  - Teamwork has been one of the effective responses to the changes over the years in the world of today. Teamwork is being relied upon as a preferred performance arrangement to fulfill visions, execute and achieve goals in all sectors. It is also one of the most important elements in continuous improvement systems, as it facilitates the sharing of information, problem solving and the development of employee responsibility. This study was on an intelligent coaching agent that modeled team performance using the Supervised Learning algorithm. The Object Oriented System Analysis and Design Methodology was used. For effective implementation of this study, some web application languages were used and these includes; Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), MySQL, Cascaded Style Sheet (CSS), Java Script, Dream weaver, and Fireworks. Dream weaver is an HTML-based application that is used to generate graphical user interfaces. This study was able to arrive at a system that will remove biases in performance evaluation since the performance appraisal is automatic; each task has been assigned a weighted score, so as soon as an employee performs the task the system automatically scores him/her. Making it easy to track individual performance as well as team performance. The system developed utilizes supervised learning to monitor the task executions and determine the weight score for the task before scoring the team. This system will help those that are worthy of keeping their jobs keep it and help improve employees that need to work on some specific areas to develop themselves as plainly revealed. The purpose of this study which is to demonstrate an event based performance approach via the design and implementation of intelligent coaching agents within a team training framework via supervised learning was achieved and the result shows positive impacts on team’s performance.
    VL  - 6
    IS  - 1
    ER  - 

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Author Information
  • Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Owerri, Nigeria

  • Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

  • Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria

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