Modelo de dados do estudante e do profissional na era da aprendizagem continuada: uma proposta para identificar conhecimentos, reais e potenciais, neste novo paradigma do século XXI/ Student and professional data model in the era of lifelong learning: a proposal to identify real and potential knowledge in this new XXI paradigm

Authors

  • Marcio Porto Feitosa
  • Nizam Omar

DOI:

https://doi.org/10.34117/bjdv5n12-152

Keywords:

Conceito, Estrutura Cognitiva, Representação do Conhecimento, Aprendizagem Significativa

Abstract

Este trabalho apresenta um modelo computável que representa o conhecimento apreendido continuadamente por um determinado indivíduo com o objetivo de identificar competências instantâneas, projetadas e também deficiências. Fortemente embasado na teoria da Aprendizagem Significativa, o conhecimento é fragmentado em unidades conceituais e armazenado a cada evento aferidor, sendo esses últimos conduzidos por sujeitos externos (avaliadores humanos ou computadorizados) ou pelo próprio indivíduo por autodeclarações. A continuidade se caracteriza não só pelo registro histórico de todos os eventos aferidores, mas pela propagação, em cascata, dos novos conhecimentos, através da rede dos conceitos relacionados ao subdomínio aferido. O modelo proposto registra cada evento em que o indivíduo é arguido sobre determinado conceito e contém uma série de indicadores, tanto da quantidade do conhecimento em si, como também ponderaradores da sua importância no contexto e no tempo.

References

D. C. McClelland, "Testing for competency rather than for intelligence", American Psychologist, p. 28, 1973

S. B. Parry, "The quest for competencies: competency studies can help you make HR decisions, but the results are only as good as the study", Training (http://trainingmag.com) - New York, N.Y. - 33, pp. 48-56, 1996.

P. Perrenoud, "Ten new competencies for teaching" in the original "Dix nouvelles compétences pour enseigner", Paris: ESF Éditeur, 1999.

D. P. Ausubel, "The acquisition and retention of knowledge: a cognitive view", Springer Science + Business Media Dordrecht, 2000.

M. Demirel, "Lifelong learning and schools in the twenty-first century", in Procedia - Social and Behavioral Sciences, v. 1, World Conference on Educational Sciences 2009 - Nicosia (Cyprus), Elsevier, 2009, p. 1709–1716.

K. A. Haydar Ates, "The importance of lifelong learning has been increasing", in Procedia - Social and Behavioral Sciences, v. 46, Elsevier, 2012, p. 4092 – 4096.

A. L. Marjan Laal, "Challenges for lifelong learning", in Procedia - Social and Behavioral Sciences, v. 47, Elsevier, 2012, p. 1539 – 1544.

M. V. Konstantina Chrysafiadi, "Student modeling approaches: a literature review for the last decade", in Expert System with Applications, v. 40, Elsevier, 2013, pp. 4715-4729.

D. McCoy, "Domain models, student models and assessmeni methods: three areas in need of standards for adaptive instruction" - In the Adaptative Instructional System (AIS) Standards Workshop of lhe 14th International Conference of the Intelligent Tutoring Systems (ITS) Conference, Montreal, Quebec, Canada - June 2018.

N. Khodeir, N. Wanas - "Constraint-based student modeling in probability story problems with scaffolding techniques" - International Journal of Emerging Technologies in Learning (iJET) - https://doi.org/10.3991/ijet.v13i01.7397

H. Gasmi, A. Bouras - "Ontology-based education/industry collaboration system" - IEEE Open Access Journal - volume 6, 2018 - pg. 1362-1371.

M. Villamañe, A. Alvarez e M. Larrañaga, "Supporting competence-based learning with visual learning analytics and recommendations", IEEE Computer Society, pp. 1572-1575, 2018, from Global Engineering Education Conference (EDUCON).

C.-Y. Law, J. Grundy, A. Cain e R. Vasa, "A preliminary study of open learner model representation formats to support formative assessment", IEEE Computer Society, pp. 887-892, 2015, from 39th Annual International Computers, Software & Applications Conference.

B. V. Aguirre, J. A. R. Uresti, B. Boulay - "An analysis of student model portability", International Journal of Artificial Intelligence in Education Society - pp. 932-974, 2016.

D. Pérez-Marín, I. Pascual-Nieto - "Showing automatically generated students conceptual models to students and teachers" - International Journal of ArtificialIntelligence in Education 20 (2010) pp. 47-72.

A. Karaci - "Intelligent tutoring system model based on fuzzy logic and constraint-based student model", in Springer: https://doi.org/10.1007/s00521-017-3311-2 from The Natural Computing Applications Forum, 2018.

A. R-Noriega, R. J-Ramirez, Y. M-Ramirez - "Evaluation module based on bayesian Networks to Intelligent Tutoring Systems", Elsevier - International Journal of Information Management, 37, pp. 1488-1498, 2017.

Y. Huang, "Deeper knowledge tracing by modeling skill application context for better personalized learning", UMAP '16: Conference on User Modeling Adaptation and Personalization, pp. 325-328, 2016

Published

2019-12-11

How to Cite

Feitosa, M. P., & Omar, N. (2019). Modelo de dados do estudante e do profissional na era da aprendizagem continuada: uma proposta para identificar conhecimentos, reais e potenciais, neste novo paradigma do século XXI/ Student and professional data model in the era of lifelong learning: a proposal to identify real and potential knowledge in this new XXI paradigm. Brazilian Journal of Development, 5(12), 30236–30251. https://doi.org/10.34117/bjdv5n12-152

Issue

Section

Original Papers