Performance metrics of item developers for the assessment of learning outcomes
DOI:
https://doi.org/10.56294/sctconf20241006Keywords:
Teaching Performance, Learning Results, Preparation of Exams, Continuous ImprovementAbstract
The evaluation of learning results is a strategy that generates inputs for curricular feedback and continuous improvement of the academic management of vocational training programs. On the one hand, it contributes to determining the level of achievement of the graduation profile that students reach according to the progress of the study plan and, on the other, it allows identifying the level of performance of the teachers who participate during the design and application processes of the evaluation instruments. This article shows the application of three performance indicators: efficiency, quality and estimation, to identify the potential of teachers according to the role they must assume in an evaluation process. The study was carried out based on the learning results evaluation methodology developed by the Technical University of Cotopaxi in which 224 teachers participated, of which 143 met acceptable parameters of efficiency, quality and estimation, allowing 67 to be categorized as developers. of items, 56 as technical reviewers and 20 as technical heads
References
1. Álvarez-Pérez PR, López-Aguilar D. Competencias genéricas y resultados de aprendizaje en los estudios de grado de Pedagogía. Roja U [Internet]. 2018 [consultado el 20 de junio del 2024];16(1):137. Disponible en: https://polipapers.upv.es/index.php/REDU/article/view/8895
2. Pérez Gamboa AJ, Díaz-Guerra DD. Artificial Intelligence for the development of qualitative studies. LatIA. 2023;1:4.
3. Educa.co. [consultado el 20 de junio de 2024]. Disponible en: https://repositorio.itm.edu.co/bitstream/handle/20.500.12622/6235/Buenas_Pra%CC%81cticas_2023.pdf?sequence=5&isAllowed=y#page=64
4. Edu.co. [cited 2024 Jun 20]. Available from: https://ww2.ufps.edu.co/public/archivos/oferta_academica/a00ca7dc282007f8c767802321fc3761.pdf
5. Cano CAG, Troya ALC. Artificial Intelligence applied to teaching and learning processes. LatIA 2023;1:2-2. https://doi.org/10.62486/latia20232.
6. Educa.co. [consultado el 21 de junio de 2024]. Disponible en: https://repositorio.itm.edu.co/handle/20.500.12622/5781?locale-attribute=en
7. Kamandhari HH, Lavandera Ponce S. Guidelines for the alignment of indirect measures of teaching performance: Triangular perspectives of students, peer faculty, and external reviewers. Int J Assess Eval [Internet]. 2021;28(2):91–117. Available from: https://www.proquest.com/openview/5b5952766b23906f962ed40a692832a9/1?pq-origsite=gscholar&cbl=5528231
8. Gómez Cano CA, Colala Troya AL. Artificial Intelligence applied to teaching and learning processes. LatIA. 2023;1:2.
9. Escuelasdearte.es. [consultado el 21 de junio de 2024]. Disponible en: http://www.escuelasdearte.es/news/2012almeria/stuff/guiasdocentes.pdf
10. Mario Luis P, Alejandra Elena M, Néstor Horacio B. El desafío del aprendizaje en las organizaciones: La necesidad de aprender a aprender para enfrentar el futuro [Internet]. Cgscholar.com. [consultado el 21 de junio de 2024]. Disponible en: https://cgscholar.com/bookstore/works/el-desafio-del-aprendizaje-en-las-organizaciones?category_id=cgrn-es
11. Gamboa AJP, Díaz-Guerra DD. Artificial Intelligence for the development of qualitative studies. LatIA 2023;1:4-4. https://doi.org/10.62486/latia20234.
12. UNESCO. Declaración de Incheon. Educación 2030: Hacia una educación inclusiva y equitativa de calidad y un aprendizaje a lo largo de la vida para todos. 2015 [cited 2024 Jun 21]; Available from: https://bibliotecadigital.mineduc.cl/handle/20.500.12365/18066
13. Vizcaóno JJ, Rojas N, Cisneros D. LA EVALUACIÓN DEL DESEMPEÑO DOCENTE. ENFOQUES Y MODELOS. Prospectivas UTC “Revista de Ciencias Administrativas y Económicas” [Internet]. 2022 [cited 2024 Jun 21];13–21. Available from: http://investigacion.utc.edu.ec/index.php/prospectivasutc/article/view/475
14. Wambua R, Mwaura P, Dinga J. Psychometric properties of a test anxiety scale for use in computer-based testing in Kenya. Int J Assess Eval [Internet]. 2023;31(1):1–18. Available from: https://www.proquest.com/openview/46948fd44ccb3871e02dd4b86bc8a23b/1?pq-origsite=gscholar&cbl=5528231
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Copyright (c) 2024 Carlos Andrés Bravo Erazo, Juan José Vizcaíno Figueroa, Patty Janeth Guarnizo Cumbicus (Author)

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