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

Chidi Ukamaka Betrand; Sylvanus Okwudili Anigbogu; Oluchukwu Uzoamaka Ekwealor; Ifeoma MaryAnn Orji

doi:doi:10.11648/j.ajai.20220601.11

| Peer-Reviewed

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

Chidi Ukamaka Betrand, Sylvanus Okwudili Anigbogu, Oluchukwu Uzoamaka Ekwealor, Ifeoma MaryAnn Orji

Published in American Journal of Artificial Intelligence (Volume 6, Issue 1)

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

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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), 2022. Published by Science Publishing Group

Keywords

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

References

[1]	Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Calstron, A. (2004). Do Psychosocial and Study Skill Factors predict Colledge Outcomes? A Meta – Analysis. American Psychological Association. 130 (2), 261-288.
[2]	Weihrich, H. & Koontz, H. (1988). Principles of management and analysis of management functions. Singapore: McGraw-Hill.
[3]	Grrenberg, J. & Baron, R. A. (2003). Behavior in organisations: Understanding and managing the human side of work. Pearson Colledge Division.
[4]	Katzenbach, J. R., & Smith, D. K. (1993). The wisdom of teams: Creating the high performance organization. Boston: Harvard Business School Press.
[5]	Sottilare, S., Burke, S., Sinatra, A. N., Johnston, J., Salas, E. (2020). Toward a Scientifically Rooted Design Architecture of Team Process and Performance Modeling in Adaptive, Team-Based Intelligent Tutoring Systems. CCDC Soldier Center, Simulation and Training Technology Center Orlando de Kok, I., Hulsmann, F., Waltemate, T., & Frank, C. (2017). The Intelligent Coaching Space: A Demonstration. Paper presented at the 17^th Conference IVA Stockholm Sweden. 105 108.
[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 14^th 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 24^th International Conference on Intelligent User Interfaces., NY, USA.
[10]	Myers, K., Berry, P., Blythe, J., Conley, K. (2007). An intelligent personal assistant for task and time management. AI Magazine, 28 (2), 47-49.
[11]	Prabhu, N. K. (2011). Human resource management at the crossroads. International Business & Economic Research Journal (IBER) 10 (8), 23-34.
[12]	Marks, M. A, Mathieu, J. E., &Zaccaro, S. J. (2001). A Temporally Based Framework and Taxonomy of Team Processes. Academy of Management Review, 26 (3).
[13]	Kirkman, B. L., Rosen, B., Tesluk, P. E., & Gibson, C. B. (2004). The impact of team empowerment on virtual team performance: The moderating role of face-to-face interaction. Academy of Management Journal, 47, 175-192.
[14]	Salas, E., Dickson, T. L., Converse, S. A. & Tannenbaum, S. I. (1992). Toward an understanding of team performance and training in Teams: Their training and performance. Ablex Publication Corporation Norwood, New Jersey. 3-29.
[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 16^th International Conference on Artificial Intelligence in Education. Memphis, USA.
[18]	Gilbert, S., Winer, E., Holub, J., Richardson, T., Dorneich, M. & Hoffman, (2015). Characteristics of a multi – user tutoring architecture. Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium, 39.
[19]	Cohen, P. R., & Levesque, H. J., (1991). Teamwork, in Handbook of Multi-agentSystems., 2 487-512.
[20]	Wooldridge, M., & Jennings, N. R., (1994). Towards a theory of cooperative problem solving. In Proceedings of Modeling Autonomous Agents in a Multi-Agent. Odense, Denmark.
[21]	Tambe, M., Pynadath, D. V., &Chauvat, N. (2000). Adaptive Agent Architectures for Heterogeneous Team Members. Paper presented at the Fourth International Conference on Multi-Agent Systems (ICMAS-2000), 301-308.
[22]	Yen, J., Yin, J., Ioerger, T. R., Miller, M., Xu, D., and Volz, R. A., (2001). CAST: Collaborative Agents for Simulating Teamwork. Paper presented at the Seventeenth International Joint Conference on Artificial Intelligence.

Cite This Article

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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
Y1  - 2022/01/20
PY  - 2022
N1  - https://doi.org/10.11648/j.ajai.20220601.11
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  -

Copy | Download

Author Information

Chidi Ukamaka Betrand

Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Owerri, Nigeria
Sylvanus Okwudili Anigbogu

Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria
Oluchukwu Uzoamaka Ekwealor

Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University, Awka, Nigeria
Ifeoma MaryAnn Orji

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

Download PDF

Sections

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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
Y1  - 2022/01/20
PY  - 2022
N1  - https://doi.org/10.11648/j.ajai.20220601.11
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  -

Copy | Download