Competency-based assessment tools for engineering higher education: a case study on complex problem-solving

Higher Education faces challenges in providing learning experiences and cultivating competencies in our modern environment. Academic discourse centres on tutoring automation, a complicated educational dilemma in the age of Machine Learning, Deep Learning, and Artificial Intelligence. Establishing a structured technique for real competency assessments is an early challenge. Therefore, this research develops and implements a structured evaluation process to assess student competencies in complex problem-solving scenarios. The study finds dimensional variation in student performance through statistical analysis of multivariate data from two engineering courses, demonstrating that each evaluation method measures different competencies. Key findings demonstrate that while traditional evaluation methods provide quantitative results, the newly proposed instruments offer a nuanced understanding of student abilities by capturing quantitative and qualitative data. This approach standardises the assessment process and lays the groundwork for developing intelligent tutoring systems to automate and personalise learning. This method may lead to computer-assisted instruction to adapt educational technology for engineering complex problem-solving and other skills. It provides a solid foundation for personalised learning technology assessment methods.

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Publication Details

Journal
Cogent Education
Published
2024-09-02
DOI
https://doi.org/10.1080/2331186x.2024.2392424
Citations
10
Primary Topic
Higher Education Learning Practices
Type
article
Field-Weighted Citation Impact
20.96
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article

Competency-based assessment tools for engineering higher education: a case study on complex problem-solving

Carlos Gijón-Rivera, Gerardo Domínguez-Ramírez, A.A. Castillo-Paz, Alberto Oliart-Ros et al.
10 citations
Cogent Education
Higher Education Learning Practices
20.96
article

Competency-based assessment tools for engineering higher education: a case study on complex problem-solving

Carlos Gijón-Rivera, Gerardo Domínguez-Ramírez, A.A. Castillo-Paz, Alberto Oliart-Ros, Conrado Rosales-Torres, Claudia Lizette Garay-Rondero
article en
10 citations

Abstract

Higher Education faces challenges in providing learning experiences and cultivating competencies in our modern environment. Academic discourse centres on tutoring automation, a complicated educational dilemma in the age of Machine Learning, Deep Learning, and Artificial Intelligence. Establishing a structured technique for real competency assessments is an early challenge. Therefore, this research develops and implements a structured evaluation process to assess student competencies in complex problem-solving scenarios. The study finds dimensional variation in student performance through statistical analysis of multivariate data from two engineering courses, demonstrating that each evaluation method measures different competencies. Key findings demonstrate that while traditional evaluation methods provide quantitative results, the newly proposed instruments offer a nuanced understanding of student abilities by capturing quantitative and qualitative data. This approach standardises the assessment process and lays the groundwork for developing intelligent tutoring systems to automate and personalise learning. This method may lead to computer-assisted instruction to adapt educational technology for engineering complex problem-solving and other skills. It provides a solid foundation for personalised learning technology assessment methods.

Cogent EducationVol. 11(1)
Institute for the Future (US), Universidad de las Américas Puebla (MX), Tecnológico de Monterrey (MX)
Quality Education
Openalex Percentile: Top 1%
Higher Education Learning Practices
20.96
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Competency-based assessment tools for engineering higher education: a case study on complex problem-solving — Carlos Gijón-Rivera, Gerardo Domínguez-Ramírez, et al. · Cogent Education (2024) | TGRS Research Map | TGRS