Exploration of a Learning Outcomes Evaluation Model for the Engineering Faculty of the University of La Guajira.

Autores/as

  • Pilar Pomárico Pimienta Universidad de la Guajira - (CO), Colombia
  • Jorge Enrique Taboada Alvarez Universidad EAN - (CO), Colombia
  • Rafael Meléndez Surmay Universidad de la Guajira - (CO), Colombia
  • Aslin Botello Plata Universidad de la Guajira - (CO), Colombia
  • Milton Januario Rueda Varon Universidad EAN - (CO), Colombia

DOI:

https://doi.org/10.18687/LACCEI2024.1.1.1005

Palabras clave:

Skills Training, Learning Results, Learning Evaluation, Emerging Technologies

Resumen

This document will show the results of pilot tests with emerging technologies to explore the model of evaluation of Learning Results (RA) in the programs of the Faculty of Engineering of the University of La Guajira. This pilot test is based on theoretical analyses of the exegesis of the training and evaluation process, opting for the taxonomic classification of levels of cognitive complexity in multicultural and multiethnic environments; according to the "SOLO Taxonomy" (Structure of the Observed Learning Outcome), a theory developed by John Biggs and Kevin Collis. The pilot study is carried out with two samples, one of applicants for higher education studies and the other of students from the University of La Guajira to whom the Learning Results established in the appropriation cycle are evaluated. For data collection, a survey methodology is used and a series of instruments focused on evaluation are developed, and articulated through items in contexts, blocks, and booklets. The analysis of the responses obtained is carried out through the application of Psychometric Theories and Statistical techniques, to identify the most recurrent difficulties of the students, and then opt for technological transfers that imply a positive paradigm change of quality indicators. The conclusions of the study suggest that Mobile Learning increases the accessibility and flexibility of learning, by allowing you to study at any time and place; Consequently, Cloud Computing facilitates access to resources and online collaboration. Finally, Adaptive Learning with Artificial Intelligence (AI) personalizes the educational content, adapting to the learning styles and rhythms of each student, which leads to developing unique generic competencies, thus allowing us to meet the objective of sustainable development Quality of education, ensuring inclusive, equitable, quality education and promoting learning opportunities for all by increasing the number of engineers who have the necessary skills, particularly technical and professional, to access employment, decent work, entrepreneurship, which promote sustainable development, including through education for sustainable development and sustainable lifestyles.

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Publicado

2024-07-27

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Articles

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Licencia Creative Commons

Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).

Cómo citar

Pomárico Pimienta, P., Taboada Alvarez, J. E., Meléndez Surmay, R., Botello Plata, A., & Rueda Varon, M. J. (2024). Exploration of a Learning Outcomes Evaluation Model for the Engineering Faculty of the University of La Guajira. LACCEI, 1(10). https://doi.org/10.18687/LACCEI2024.1.1.1005

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