Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm

Fabiola M. Talavera-Mendoza; Carlos Eduardo Atencio Torres; David A. Deza Veliz; Juan M. Llano-Barsaya

doi:10.1109/ICIET51873.2021.9419654

Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm

Fabiola M. Talavera-Mendoza, Carlos Eduardo Atencio Torres, David A. Deza Veliz, Juan M. Llano-Barsaya

Departamento Académico de Ingeniería de Sistemas e Informática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Pedagogical agents are computational entities that interact with users and facilitate learning opportunities. They usually need to be programmed to follow a set of commands for an effective personalized exchange of knowledge and tasks. In this study, we evaluate the effectiveness of a policy-based model and its level of satisfaction about the interaction without and with the pedagogical agent using the bio-inspired roulette selection algorithm. The approach is quantitative, with an exploratory and descriptive study. The results revealed that our agent achieved great acceptance among the users who rated it as intelligent, friendly, and reliable. It is evidenced that the agent can influence the attitude, perception, and behavior of the user to reach better self-regulated learning.

Original language	English
Title of host publication	2021 9th International Conference on Information and Education Technology, ICIET 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	78-84
Number of pages	7
ISBN (Electronic)	9781665419338
DOIs	https://doi.org/10.1109/ICIET51873.2021.9419654
State	Published - 27 Mar 2021
Event	9th International Conference on Information and Education Technology, ICIET 2021 - Okayama, Japan Duration: 27 Mar 2021 → 29 Mar 2021

Publication series

Name	2021 9th International Conference on Information and Education Technology, ICIET 2021

Conference

Conference	9th International Conference on Information and Education Technology, ICIET 2021
Country/Territory	Japan
City	Okayama
Period	27/03/21 → 29/03/21

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This article has been prepared within the framework of the project IBA-0017-2018 titled “Recommendation System for Learning Objects in Regular Basic Education, focused on competencies using Deep Learning and Big Data” and funded by the Universidad Nacional de San Agustin de Arequipa, Peru to who we are deeply grateful.

Publisher Copyright:
© 2021 IEEE.

Keywords

learning
pedagogical agents
roulette

Access to Document

10.1109/ICIET51873.2021.9419654

Cite this

Talavera-Mendoza, F. M., Atencio Torres, C. E., Deza Veliz, D. A., & Llano-Barsaya, J. M. (2021). Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm. In 2021 9th International Conference on Information and Education Technology, ICIET 2021 (pp. 78-84). [9419654] (2021 9th International Conference on Information and Education Technology, ICIET 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIET51873.2021.9419654

Talavera-Mendoza, Fabiola M. ; Atencio Torres, Carlos Eduardo ; Deza Veliz, David A. et al. / Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm. 2021 9th International Conference on Information and Education Technology, ICIET 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 78-84 (2021 9th International Conference on Information and Education Technology, ICIET 2021).

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title = "Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm",

abstract = "Pedagogical agents are computational entities that interact with users and facilitate learning opportunities. They usually need to be programmed to follow a set of commands for an effective personalized exchange of knowledge and tasks. In this study, we evaluate the effectiveness of a policy-based model and its level of satisfaction about the interaction without and with the pedagogical agent using the bio-inspired roulette selection algorithm. The approach is quantitative, with an exploratory and descriptive study. The results revealed that our agent achieved great acceptance among the users who rated it as intelligent, friendly, and reliable. It is evidenced that the agent can influence the attitude, perception, and behavior of the user to reach better self-regulated learning.",

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note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; null ; Conference date: 27-03-2021 Through 29-03-2021",

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Talavera-Mendoza, FM, Atencio Torres, CE, Deza Veliz, DA & Llano-Barsaya, JM 2021, Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm. in 2021 9th International Conference on Information and Education Technology, ICIET 2021., 9419654, 2021 9th International Conference on Information and Education Technology, ICIET 2021, Institute of Electrical and Electronics Engineers Inc., pp. 78-84, 9th International Conference on Information and Education Technology, ICIET 2021, Okayama, Japan, 27/03/21. https://doi.org/10.1109/ICIET51873.2021.9419654

Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm. / Talavera-Mendoza, Fabiola M.; Atencio Torres, Carlos Eduardo; Deza Veliz, David A. et al.

2021 9th International Conference on Information and Education Technology, ICIET 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 78-84 9419654 (2021 9th International Conference on Information and Education Technology, ICIET 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm

AU - Talavera-Mendoza, Fabiola M.

AU - Atencio Torres, Carlos Eduardo

AU - Deza Veliz, David A.

AU - Llano-Barsaya, Juan M.

PY - 2021/3/27

Y1 - 2021/3/27

N2 - Pedagogical agents are computational entities that interact with users and facilitate learning opportunities. They usually need to be programmed to follow a set of commands for an effective personalized exchange of knowledge and tasks. In this study, we evaluate the effectiveness of a policy-based model and its level of satisfaction about the interaction without and with the pedagogical agent using the bio-inspired roulette selection algorithm. The approach is quantitative, with an exploratory and descriptive study. The results revealed that our agent achieved great acceptance among the users who rated it as intelligent, friendly, and reliable. It is evidenced that the agent can influence the attitude, perception, and behavior of the user to reach better self-regulated learning.

AB - Pedagogical agents are computational entities that interact with users and facilitate learning opportunities. They usually need to be programmed to follow a set of commands for an effective personalized exchange of knowledge and tasks. In this study, we evaluate the effectiveness of a policy-based model and its level of satisfaction about the interaction without and with the pedagogical agent using the bio-inspired roulette selection algorithm. The approach is quantitative, with an exploratory and descriptive study. The results revealed that our agent achieved great acceptance among the users who rated it as intelligent, friendly, and reliable. It is evidenced that the agent can influence the attitude, perception, and behavior of the user to reach better self-regulated learning.

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Talavera-Mendoza FM, Atencio Torres CE, Deza Veliz DA, Llano-Barsaya JM. Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm. In 2021 9th International Conference on Information and Education Technology, ICIET 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 78-84. 9419654. (2021 9th International Conference on Information and Education Technology, ICIET 2021). https://doi.org/10.1109/ICIET51873.2021.9419654

Policies Selection for Pedagogical Agent Based on the Roulette Wheel Algorithm

Abstract

Publication series

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Bibliographical note

Keywords

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