A Long-Life Predictive Guidance with Homogeneous Competence Promotion for University Teaching Design

Loading...
Thumbnail Image

Identifiers

Publication date

Reading date

Authors

Aciego Gallardo, Juan José
Claros Colomé, Alicia
González Prieto, Ignacio
González Prieto, Ángel

Collaborators

Advisors

Tutors

Editors

Journal Title

Journal ISSN

Volume Title

Publisher

MDPI

Metrics

Google Scholar

Share

Research Projects

Organizational Units

Journal Issue

Department/Institute

Keywords

Abstract

Even though planning the educational action to optimize student performance is a very complex task, teachers typically face this challenging issue with no external assistance. Previous experience is, in most cases, the main driving force in curriculum design. This procedure commonly overlooks the students’ perception and weakly integrates the students’ feedback by using a non-systematic approach. Furthermore, transverse competences are, unfortunately, typically omitted in this procedure. This work suggests the use of a predictive tool that determines the optimal application time of different methodological instruments. The suggested method can be used for an infinite number of scenarios of promoted competences. The results can be regarded as a guide to modify the course structure, but, more importantly, it offers valuable information to understand better what is occurring in the teaching-learning process and detect anomalies in the subject and avoid the students’ exclusion. The predictive scheme simultaneously considers the teacher’s perspective, the student’s feedback, and the previous scores in a systematic manner. Therefore, results provide a broader picture of the educational process. The proposal is assessed in a course of Electrical Machines at the University of Malaga during the academic year 2021–2022.

Description

Bibliographic citation

Aciego JJ, Claros Colome A, Gonzalez-Prieto I, Gonzalez-Prieto A, Duran MJ. A Long-Life Predictive Guidance with Homogeneous Competence Promotion for University Teaching Design. Education Sciences. 2023; 13(1):31. https://doi.org/10.3390/educsci13010031

Collections

Endorsement

Review

Supplemented By

Referenced by

Creative Commons license

Except where otherwised noted, this item's license is described as Atribución 4.0 Internacional