Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis
Competency-Based Education (CBE) has been widely studied since the 1970s, yet it remains innovative due to its challenges across disciplines and cultures. Tecnológico de Monterrey, a Mexican private institution, implements CBE through its Tec21 model, which emphasizes challenge-based learning to dev...
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MDPI AG
2025-04-01
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| author | Enrique Solera Ernestina Menasalvas Mario Martín Marta Zorrilla Danilo Valdés-Ramírez Genaro Zavala Raúl Monroy |
| author_facet | Enrique Solera Ernestina Menasalvas Mario Martín Marta Zorrilla Danilo Valdés-Ramírez Genaro Zavala Raúl Monroy |
| author_sort | Enrique Solera |
| collection | DOAJ |
| description | Competency-Based Education (CBE) has been widely studied since the 1970s, yet it remains innovative due to its challenges across disciplines and cultures. Tecnológico de Monterrey, a Mexican private institution, implements CBE through its Tec21 model, which emphasizes challenge-based learning to develop disciplinary and transversal skills. Since its launch in 2019, Tec21 has generated extensive data, offering an opportunity to assess its performance and ensure quality. This study analyzes data from six academic semesters in the School of Engineering and Sciences to address key quality assurance questions. First, we evaluate whether initially enrolling in a generic area before selecting a specific program improves long-term student outcomes. Second, we examine competency development, identifying challenges in achieving certain skills and their links to dropout rates and module difficulty. Third, we explore the relationship between final grades, module credit allocation, and Tec weeks to assess curriculum alignment with academic performance. Using data from over 550,000 evaluations of 4500+ students, our analysis provides robust quality metrics. Findings suggest that students who start in generic areas perform better long term and highlight the complex interplay between competencies, module characteristics, and academic success. These insights deepen the understanding of CBE implementation and offer recommendations to improve educational strategies and quality assurance within competency-based frameworks. |
| format | Article |
| id | doaj-art-d50d9f0251834650bd83cf68bc145228 |
| institution | OA Journals |
| issn | 2227-7102 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Education Sciences |
| spelling | doaj-art-d50d9f0251834650bd83cf68bc1452282025-08-20T02:17:25ZengMDPI AGEducation Sciences2227-71022025-04-0115451310.3390/educsci15040513Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven AnalysisEnrique Solera0Ernestina Menasalvas1Mario Martín2Marta Zorrilla3Danilo Valdés-Ramírez4Genaro Zavala5Raúl Monroy6Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28040 Madrid, SpainFacultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28040 Madrid, SpainDepartamento de Ingeniería Informática y Electrónica, Facultad de Ciencias, Universidad de Cantabria, Santander, 39005 Cantabria, SpainDepartamento de Ingeniería Informática y Electrónica, Facultad de Ciencias, Universidad de Cantabria, Santander, 39005 Cantabria, SpainTecnológico de Monterrey, Institute for the Future of Education, Monterrey 64700, MexicoTecnológico de Monterrey, Institute for the Future of Education, Monterrey 64700, MexicoTecnológico de Monterrey, School of Engineering and Sciences, Monterrey 06500, MexicoCompetency-Based Education (CBE) has been widely studied since the 1970s, yet it remains innovative due to its challenges across disciplines and cultures. Tecnológico de Monterrey, a Mexican private institution, implements CBE through its Tec21 model, which emphasizes challenge-based learning to develop disciplinary and transversal skills. Since its launch in 2019, Tec21 has generated extensive data, offering an opportunity to assess its performance and ensure quality. This study analyzes data from six academic semesters in the School of Engineering and Sciences to address key quality assurance questions. First, we evaluate whether initially enrolling in a generic area before selecting a specific program improves long-term student outcomes. Second, we examine competency development, identifying challenges in achieving certain skills and their links to dropout rates and module difficulty. Third, we explore the relationship between final grades, module credit allocation, and Tec weeks to assess curriculum alignment with academic performance. Using data from over 550,000 evaluations of 4500+ students, our analysis provides robust quality metrics. Findings suggest that students who start in generic areas perform better long term and highlight the complex interplay between competencies, module characteristics, and academic success. These insights deepen the understanding of CBE implementation and offer recommendations to improve educational strategies and quality assurance within competency-based frameworks.https://www.mdpi.com/2227-7102/15/4/513competency-based educationeducational quality assuranceSTEAM programslearning analyticshigher educationdata analysis |
| spellingShingle | Enrique Solera Ernestina Menasalvas Mario Martín Marta Zorrilla Danilo Valdés-Ramírez Genaro Zavala Raúl Monroy Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis Education Sciences competency-based education educational quality assurance STEAM programs learning analytics higher education data analysis |
| title | Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis |
| title_full | Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis |
| title_fullStr | Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis |
| title_full_unstemmed | Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis |
| title_short | Evaluating Competency Development and Academic Outcomes: Insights from Six Semesters of Data-Driven Analysis |
| title_sort | evaluating competency development and academic outcomes insights from six semesters of data driven analysis |
| topic | competency-based education educational quality assurance STEAM programs learning analytics higher education data analysis |
| url | https://www.mdpi.com/2227-7102/15/4/513 |
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