Agent-Based Simulation of Learning Dissemination in a Project-Based Learning Context Considering the Human Aspects

Autor/inn/en	Seman, Laio Oriel; Hausmann, Romeu; Bezerra, Eduardo Augusto
Titel	Agent-Based Simulation of Learning Dissemination in a Project-Based Learning Context Considering the Human Aspects
Quelle	In: IEEE Transactions on Education, 61 (2018) 2, S.101-108 (8 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Seman, Laio Oriel)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0018-9359
DOI	10.1109/TE.2017.2754987
Schlagwörter	Active Learning; Student Projects; Vignettes; Classroom Environment; Simulation; Engineering Education; Teaching Methods; Pretesting; Simulated Environment; Least Squares Statistics; Cognitive Mapping; Cooperative Learning; Structural Equation Models; Hypothesis Testing; Human Factors Engineering; Higher Education; Foreign Countries; Brazil + Suchen Sie Ihr Suchwort? Aktives Lernen; Schulprojekt; Klassenklima; Unterrichtsklima; Simulation program; Simulationsprogramm; Ingenieurausbildung; Teaching method; Lehrmethode; Unterrichtsmethode; Vortest; Künstliche Umwelt; Kooperatives Lernen; Hypothesenprüfung; Hypothesentest; Hochschulbildung; Hochschulsystem; Hochschulwesen; Ausland; Brasilien
Abstract	Contribution: This paper presents the "PBL classroom model," an agent-based simulation (ABS) that allows testing of several scenarios of a project-based learning (PBL) application by considering different levels of soft-skills, and students' perception of the methodology. Background: While the community has made great advances in conducting engineering education studies, achieving goals of meaningful learning is still difficult. In this context, each new teaching methodology should be field tested, which can be time consuming. Introducing a simulation that can pre-test methodologies to check their efficiency can assist in the methodological building process.Research questions: The proposed simulation environment helps in understanding the differences in the learning rate of a group of agents (students) with different levels of humanization and instruction. Methodology: Partial least squares path modeling (PLS-PM) was used to build the causal relationship between the students and a PBL methodology, to generate the input data for the simulation. Based on the analysis of the responses to a survey performed over five consecutive semesters, it was possible to generate some cause-effect data parameters to be used as the input for a hybrid type of ABS, known as PLS agent.Findings: The use of the proposed model, based on a computational approach, to study the educational process was validated; the simulation outcomes indicate that higher levels of self-esteem, self-realization, and cooperation result in better learning experiences. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01