Intelligent tutoring system based on personalized learning for teaching health care protocols

Authors

DOI:

https://doi.org/10.24054/rcta.v2i44.2866

Keywords:

Health Education, Pedagogical Strategy, Personalized Learning, Case-Based Reasoning, Intelligent Tutoring System

Abstract

Our journal has a biannual basis and is dedicated to the engineering area, mainly to the disciplines of electrical, electronics, telecommunications and systems engineering, so the target audience for the magazine that is interested in such areas. We publish scientific research papers or problem reflections in a specific topic, review articles, papers, reviews, discussions and translations, within this thematic framework. We use the IEEE standards for publications.

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Author Biographies

Monica Isabel Hanna Lavalle, Universidad de Córdoba

Magíster en Administración, Universidad Nacional – Bogotá, Colombia.

Adan Alberto Gomez Salgado, Universidad de Córdoba

Estudiante de Doctorado en Ciencias Cognitivas. Rensselaer Polytechnic Institute, New York, Estados Unidos.

Laura Andrea Marquez Garcia, Universidad Pedagógica Nacional

Magíster en Tecnologías de la información aplicadas a la Educación, Universidad Pedagógica Nacional, Bogotá, Colombia.

References

A. Klasnja-Milicevic, B. Vesin, M. Ivanovic, y Z. Budimac, «E-Learning personalization based on hybrid recommendation strategy and learning style identification», Comput. Educ., vol. 56, n.o 3, pp. 885-899, 2011, doi: https://doi.org/10.1016/j.compedu.2010.11.001.

G. Bahg, «The Effects of Personalization on Category Learning», 2021, [En línea]. Disponible en: http://rave.ohiolink.edu/etdc/view?acc_num=osu1638475531086215

M. Lefevre, S. Jean-Daubias, y N. Guin, «An approach for unified personalization of learning», jun. 2022, doi: https://doi.org/10.48550/arXiv.2309.02856 Focus to learn more.

A. Gomez, M. Fernando, y C. Piñeres, «Meta-Modeling Process of Pedagogical Strategies in Intelligent Tutoring Systems Personalization of pedagogical strategies in Intelligent Tutoring Systems», 2018, doi: 10.1109/ICCI-CC.2018.8482046.

M. Lefevre, «Processus unifié pour la personnalisation des activités pédagogiques: méta-modele, modeles et outils», 2009.

B. Clément, «Adaptive Personalization of Pedagogical Sequences using Machine Learning», l’Université de Bordeaux, 2019. [En línea]. Disponible en: https://hal.inria.fr/tel-01968241/file/CLEMENT_BENJAMIN_2018.pdf

L. Marquez, H. Zapa, y A. Gomez, «Design of a Cognitive Control Mechanism for a Goal-based Executive Function of a Cognitive System», en Proceedings of the Ninth Goal Reasoning Workshop, Ohio, Estados Unidos, 2021, p. 8. [En línea]. Disponible en: https://sravya-kondrakunta.github.io/9thGoal-Reasoning-Workshop/papers/Paper_9.pdf

Z. Li, L. Yee, y N. Sauerberg, «Getting too personal(ized): The importance of feature choice in online adaptive algorithms», p. 12, 2020.

A. Klasnja-Milicevic, B. Vesin, M. Ivanovic, y Z. Budimac, «E-Learning personalization based on hybrid recommendation strategy and learning style identification», Comput. Educ., vol. 56, n.o 3, pp. 885-899, 2011, doi: https://doi.org/10.1016/j.compedu.2010.11.001. DOI: https://doi.org/10.1016/j.compedu.2010.11.001

G. Bahg, «The Effects of Personalization on Category Learning», 2021, [En línea]. Disponible en: http://rave.ohiolink.edu/etdc/view?acc_num=osu1638475531086215

M. Lefevre, S. Jean-Daubias, y N. Guin, «An approach for unified personalization of learning», jun. 2022, doi: https://doi.org/10.48550/arXiv.2309.02856 Focus to learn more.

A. Gomez, M. Fernando, y C. Piñeres, «Meta-Modeling Process of Pedagogical Strategies in Intelligent Tutoring Systems Personalization of pedagogical strategies in Intelligent Tutoring Systems», 2018, doi: 10.1109/ICCI-CC.2018.8482046. DOI: https://doi.org/10.1109/ICCI-CC.2018.8482046

M. Lefevre, «Processus unifié pour la personnalisation des activités pédagogiques: méta-modele, modeles et outils», 2009.

B. Clément, «Adaptive Personalization of Pedagogical Sequences using Machine Learning», l’Université de Bordeaux, 2019. [En línea]. Disponible en: https://hal.inria.fr/tel-01968241/file/CLEMENT_BENJAMIN_2018.pdf

L. Marquez, H. Zapa, y A. Gomez, «Design of a Cognitive Control Mechanism for a Goal-based Executive Function of a Cognitive System», en Proceedings of the Ninth Goal Reasoning Workshop, Ohio, Estados Unidos, 2021, p. 8. [En línea]. Disponible en: https://sravya-kondrakunta.github.io/9thGoal-Reasoning-Workshop/papers/Paper_9.pdf

Z. Li, L. Yee, y N. Sauerberg, «Getting too personal(ized): The importance of feature choice in online adaptive algorithms», p. 12, 2020.

M. Zanker, L. Rook, y D. Jannach, «Measuring the impact of online personalisation: Past, present and future», Int. J. Hum.-Comput. Stud., vol. 131, pp. 160-168, nov. 2019, doi: 10.1016/j.ijhcs.2019.06.006. DOI: https://doi.org/10.1016/j.ijhcs.2019.06.006

M. Kravcik et al., Requirements and Solutions for Personalized Adaptive Learning. 2005. [En línea]. Disponible en: https://hal.archives-ouvertes.fr/hal-00590961

M. F. Caro, «Metamodel for personalized adaptation of pedagogical strategies using metacognition in Intelligent Tutoring Systems», Tesis Doctoral, Universidad Nacional de Colombia, Medellín, Colombia, 2015. Accedido: 29 de julio de 2021. [En línea]. Disponible en: https://repositorio.unal.edu.co/handle/unal/55505

A. Gómez, L. Márquez, H. Zapa, y M. Florez, «GDA-Based Tutor Module of an Intelligent Tutoring System for the Personalization of Pedagogic Strategies», en Emerging Trends in Intelligent and Interactive Systems and Applications, M. Tavana, N. Nedjah, y R. Alhajj, Eds., en Advances in Intelligent Systems and Computing. Cham: Springer International Publishing, 2021, pp. 742-750. doi: 10.1007/978-3-030-63784-2_92. DOI: https://doi.org/10.1007/978-3-030-63784-2_92

J. Joy y R. V. G. Pillai, «Review and classification of content recommenders in E-learning environment», J. King Saud Univ.-Comput. Inf. Sci., 2021, [En línea]. Disponible en: https://doi.org/10.1016/j.jksuci.2021.06.009

S. Sarwar, Z. U. Qayyum, R. García-Castro, M. Safyan, y R. F. Munir, «Ontology based E-learning framework: A personalized, adaptive and context aware model», Multimed. Tools Appl., vol. 78, n.o 24, pp. 34745-34771, dic. 2019, doi: 10.1007/s11042-019-08125-8. DOI: https://doi.org/10.1007/s11042-019-08125-8

E. Delozanne, C. Vincent, B. Grugeon, J.-M. Gélis, J. Rogalski, y L. Coulange, «From errors to stereotypes: Different levels of cognitive models in school algebra», presentado en E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Association for the Advancement of Computing in Education (AACE), 2005, pp. 262-269. [En línea]. Disponible en: https://www.learntechlib.org/p/21181/

A. Mitrovic, «A knowledge-based teaching system for SQL», presentado en Proceedings of ED-MEDIA, Citeseer, 1998, pp. 1027-1032. [En línea]. Disponible en: https://www.csse.canterbury.ac.nz/tanja.mitrovic/702.pdf

J. A. Jiménez Builes, «Un modelo de planificación instruccional usando razonamiento basado en casos en sistemas multi-agente para entornos integrados de sistemas tutoriales inteligentes y ambientes colaborativos de aprendizaje», Tesis Doctoral, Universidad Nacional de Colombia, Colombia, 2006. Disponible en: https://repositorio.unal.edu.co/handle/unal/11028

E. G. Nihad, K. Mohamed, y E.-N. El Mokhtar, «Designing and modeling of a multi-agent adaptive learning system (MAALS) using incremental hybrid case-based reasoning (IHCBR).», Int. J. Electr. Comput. Eng. 2088-8708, vol. 10, n.o 2, 2020, doi: 10.11591/ijece.v10i2.pp1980-1992. DOI: https://doi.org/10.11591/ijece.v10i2.pp1980-1992

«Review and classification of content recommenders in E-learning environment», J. King Saud Univ. - Comput. Inf. Sci., jul. 2021, doi: 10.1016/j.jksuci.2021.06.009. DOI: https://doi.org/10.1016/j.jksuci.2021.06.009

S. H. Almurshidi, S. S. A. Naser, y S. S. Abu, «Design and Development of Diabetes Intelligent Tutoring SystemDesign and Development of Diabetes Intelligent Tutoring System», Eur. Acad. Res., vol. 4, n.o 9, pp. 8117-8128, 2016.

S. Matthews, «Integrating Technology Acceptance Model and Health Belief Model Factors to Better Estimate Intelligent Tutoring System Use for Surge Capacity Public Health Events and Training», Doctoral, University of Central Florida, Estados Unidos, 2020. [En línea]. Disponible en: https://stars.library.ucf.edu/etd2020/381

K. M. Bauer, M. A. Corcorran, J. Z. Budak, C. Johnston, y D. H. Spach, «Leveraging E-Learning Infrastructure in Times of Rapid Change: Use of the National Sexually Transmitted Diseases Curriculum in the Era of COVID-19», Sex. Transm. Dis., vol. 48, n.o 8 Suppl, pp. S50-S53, ago. 2021, doi: 10.1097/OLQ.0000000000001462. DOI: https://doi.org/10.1097/OLQ.0000000000001462

L. H. A. Bos-Bonnie, J. E. A. M. van Bergen, E. te Pas, M. A. Kijser, y N. van Dijk, «Effectiveness of an individual, online e-learning program about sexually transmitted infections: a prospective cohort study», BMC Fam. Pract., vol. 18, n.o 1, p. 57, dic. 2017, doi: 10.1186/s12875-017-0625-1. DOI: https://doi.org/10.1186/s12875-017-0625-1

S. M. C. de Almeida, L. M. Brasil, H. S. Carvalho, E. Ferneda, y R. P. Silva, «The Diagnosis Support System for Ischemic Cardiopathy: A Case Study in the Context of IACVIRTUAL Project», en World Congress on Medical Physics and Biomedical Engineering 2006, vol. 14, R. Magjarevic y J. H. Nagel, Eds., en IFMBE Proceedings, vol. 14. , Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 3677-3680. doi: 10.1007/978-3-540-36841-0_931. DOI: https://doi.org/10.1007/978-3-540-36841-0_931

M. C. Duffy y R. Azevedo, «Motivation matters: Interactions between achievement goals and agent scaffolding for self-regulated learning within an intelligent tutoring system», Comput. Hum. Behav., vol. 52, pp. 338-348, nov. 2015, doi: 10.1016/j.chb.2015.05.041. DOI: https://doi.org/10.1016/j.chb.2015.05.041

M. de S. Dutra Davilla et al., «Cervical cancer tracking virtual learning object», Acta Paul. Enferm., vol. 34, jul. 2021, doi: 10.37689/acta-ape/2021AO00063. DOI: https://doi.org/10.37689/acta-ape/2021AO00063

C. Gonzalez et al., «ITS-TB: an intelligent tutoring system to provide e-learning in public health», en 16th EAEEIE conference, Lappeenranta, 2005. [En línea]. Disponible en: https://www.researchgate.net/publication/228623709

C. S. Hunt, D. Panigrahi, y A. Momenipour, «Augmenting the information systems curriculum with a course in health informatics», vol. 2, n.o 1, p. 15, 2015.

M. Royo-Leon et al., SEXWISE: An IBM Watson-Powered Mobile Application to Promote Sexual Education. 2016. [En línea].

S. P. Somashekhar et al., «Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board», Ann. Oncol., vol. 29, n.o 2, pp. 418-423, feb. 2018, doi: 10.1093/annonc/mdx781. DOI: https://doi.org/10.1093/annonc/mdx781

G. E. Thibault, «The future of health professions education: Emerging trends in the United States», FASEB BioAdvances, vol. 2, n.o 12, pp. 685-694, 2020, doi: 10.1096/fba.2020-00061. DOI: https://doi.org/10.1096/fba.2020-00061

B. Williamson, «Computing brains: learning algorithms and neurocomputation in the smart city», Inf. Commun. Soc., vol. 20, n.o 1, pp. 81-99, ene. 2017, doi: 10.1080/1369118X.2016.1181194. DOI: https://doi.org/10.1080/1369118X.2016.1181194

C. A. Ahumada, M. H. Lavalle, y M. V. Chamorro, «Sífilis gestacional: enfermedad de interés en salud pública, Córdoba-Colombia, 2015», Rev. Cuid., vol. 8, n.o 1, pp. 1449-1458, 2017, doi: https://doi.org/10.15649/cuidarte.v8i1.350. DOI: https://doi.org/10.15649/cuidarte.v8i1.350

L. A. D. Cruz, «Sífilis gestacional: un problema de salud pública», Rev. Fac. Med., vol. 59, n.o 3, pp. 163-165, 2011.

M. H. Owais, Development of Intelligent Systems to Optimize Training and Real-World Performance Amongst Health Care Professionals. The University of Toledo, 2019.

K.-C. Pai, B.-C. Kuo, C.-H. Liao, y Y.-M. Liu, «An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning», Educ. Psychol., vol. 41, pp. 1-16, feb. 2020, doi: 10.1080/01443410.2020.1731427. DOI: https://doi.org/10.1080/01443410.2020.1731427

A. Gomez, «Design of a Self-Control Mechanism for an GDA-Based Tutor Module of an Intelligent Tutoring System», 2021, [En línea]. Disponible en: https://sravya-kondrakunta.github.io/9thGoal-Reasoning-Workshop/papers/Paper_8.pdf

A. A. Gómez, E. P. Flórez, y L. A. Márquez, «Design of the tutor module for an intelligent tutoring system (ITS) based on science teachers’ pedagogical content knowledge (PCK)», presentado en International Congress on Education and Technology in Sciences, Springer, 2019, pp. 141-157. doi: https://doi.org/10.1007/978-3-030-45344-2_12. DOI: https://doi.org/10.1007/978-3-030-45344-2_12

R. M. Felder y L. Silverman, «LEARNING AND TEACHING STYLES IN ENGINEERING EDUCATION», Eng. Educ., vol. 78, p. 10, 1988.

Published

2024-07-03

How to Cite

Hanna Lavalle, M. I., Gomez Salgado, A. A., & Marquez Garcia, L. A. (2024). Intelligent tutoring system based on personalized learning for teaching health care protocols. COLOMBIAN JOURNAL OF ADVANCED TECHNOLOGIES, 2(44), 45–54. https://doi.org/10.24054/rcta.v2i44.2866