Métricas alternativas
Datos de los fondos
Palabras clave
recursos educativos digitales
resultado académico
fsQCA longitudinal
enseñanza superior Flipped classroom
digital educational resources
academic performance
longitudinal fsQCA
higher education
Cómo citar
Resumen
El uso de las Tecnologías de la Información y Comunicación en el ámbito docente ha supuesto la proliferación de Recursos Educativos Digitales (REDs) que tratan de fomentar el aprendizaje autónomo y asíncrono de los estudiantes buscando, a su vez, mejorar el resultado académico. Sin embargo, en pocos casos se evalúa las consecuencias de dichos recursos en el proceso de aprendizaje.
En este trabajo, se propone la metodología fsQCA para establecer las combinaciones de REDs que facilitan la obtención de un mejor desempeño de los estudiantes, frente metodologías que se basan en el estudio de los efectos netos de cada recurso. El trabajo se complementa con un análisis para varios cursos académicos a través de la metodología fsQCA longitudinal, lo que facilita realizar un análisis en el tiempo, propiciando una visión dinámica de oportunidad y relevancia de los REDs. Los resultados de la investigación sugieren que no existe una única combinación de REDs que conduzcan al éxito, sino que la utilización de dichos recursos de diferentes formas combinadas permite a los estudiantes el logro de sus objetivos académicos, concluyendo que la metodología planteada puede resultar de utilidad para la evaluación de REDs con independencia de la tipología de los mismos.
Citas
Barhate, B., & Dirani, K. M. (2022). Career aspirations of generation Z: a systematic literature review. European Journal of Training and Development, 46(1/2), 139–157. https://doi.org/10.1108/EJTD-07-2020-0124
Bendjebar, S., Djebarnia, N. E. I., Mehenaoui, Z., & Lafifi, Y. (2023). Recommendation of pedagogical resources based on learners’ profiles. International Journal of Informatics and Applied Mathematics. https://doi.org/10.53508/ijiam.1213949
Bergmann, J., & Sams, A. (2012). Flip Your Classroom: Reach Every Student in Every Class Every Day. International Society for Technology in Education.
Campbell, J. T., Sirmon, D. G., & Schijven, M. (2015). Fuzzy Logic and the Market: A Configurational Approach to Investor Perceptions of Acquisition Announcements. Academy of Management Journal, 59(1), 163–187. https://doi.org/10.5465/amj.2013.0663
Cickovska, E. (2020). Understanding and Teaching Gen Z in Higher Education. Horizons Serie A, 26, 275–290. https://doi.org/10.20544/HORIZONS.A.26.3.20.P22
Di Meo, F., & Martí-Ballester, C.-P. (2020). Effects of the perceptions of online quizzes and electronic devices on student performance. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.4888
Drozdikova-Zaripova, A. R., & Sabirova, E. G. (2020). Usage of Digital Educational Resources in Teaching Students with Application of “Flipped Classroom” Technology. Contemporary Educational Technology, 12(2), ep278. https://doi.org/10.30935/cedtech/8582
Estrada-Molina, O., Fuentes-Cancell, D. R., & Morales, A. A. (2022). The assessment of the usability of digital educational resources: An interdisciplinary analysis from two systematic reviews. Education and Information Technologies, 27(3), 4037–4063. https://doi.org/10.1007/s10639-021-10727-5
Federo, R., & Saz-Carranza, A. (2018). A configurational analysis of board involvement in intergovernmental organizations. Corporate Governance: An International Review, 26(6), 414–428. https://doi.org/https://doi.org/10.1111/corg.12241
Ferrando Rodríguez, L., Gabarda-Mendez, V., Marin Suelves, D., & Ramón-Llin Más, J. (2023). ¿Crea contenidos digitales el profesorado universitario? Un diseño mixto de investigación. Pixel-Bit. Revista de Medios y Educación, 66, 137–172. https://doi.org/10.12795/pixelbit.96309
Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organizational research. Academy of Management Journal, 54, 393–420. https://doi.org/10.5465/AMJ.2011.60263120
Greckhamer, T., Misangyi, V. F., & Fiss, P. C. (2013). Chapter 3 The Two QCAs: From a Small-N to a Large-N Set Theoretic Approach. In P. C. Fiss, B. Cambré, & A. Marx (Eds.), Configurational Theory and Methods in Organizational Research (Vol. 38, pp. 49–75). Emerald Group Publishing Limited. https://doi.org/10.1108/S0733-558X(2013)0000038007
Gutiérrez-González, C., Montero, L., Espitia, L., & Torres, Y. (2023). Análisis de la producción científica relacionada con Recursos Educativos Digitales (RED) y Objetos Virtuales de Aprendizaje (OVA), entre 2000 – 2021. Revista de Investigación Educativa, 41(1), 263–280. https://doi.org/10.6018/rie.518741
Hasan, R., Palaniappan, S., Mahmood, S., Abbas, A., Sarker, K. U., & Sattar, M. U. (2020). Predicting Student Performance in Higher Educational Institutions Using Video Learning Analytics and Data Mining Techniques. Applied Sciences, 10(11), 3894. https://doi.org/10.3390/app10113894
Haxhi, I., & Aguilera, R. V. (2017). An Institutional Configurational Approach to Cross-National Diversity in Corporate Governance. Journal of Management Studies, 54(3), 261–303. https://doi.org/https://doi.org/10.1111/joms.12247
Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142. https://doi.org/10.1016/J.TATE.2017.06.001
Latif, E., & Miles, S. (2020). The Impact of Assignments and Quizzes on Exam Grades: A Difference-in-Difference Approach. Journal of Statistics Education, 28(3), 289–294. https://doi.org/10.1080/10691898.2020.1807429
Maquilón Sánchez, J. J., Mirete Ruz, A. B., García Sánchez, F. A., & Hernández Pina, F. (2013). Valoración de las TIC por los estudiantes universitarios y su relación con los enfoques de aprendizaje. Revista de Investigación Educativa, 31(2), 537–554. https://doi.org/10.6018/rie.31.2.151891
Ndiyae, N. M., Chaabi, Y., Lekdioui, K., & Lishou, C. (2019). Recommending system for digital educational resources based on learning analysis. Proceedings of the New Challenges in Data Sciences: Acts of the Second Conference of the Moroccan Classification Society. https://api.semanticscholar.org/CorpusID:85519277
Noetel, M., Griffith, S., Delaney, O., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2021). Video Improves Learning in Higher Education: A Systematic Review. Review of Educational Research, 91(2), 204–236. https://doi.org/10.3102/0034654321990713
Okike, E. U., & Mogorosi, M. (2020). Educational Data Mining for Monitoring and Improving Academic Performance at University Levels. International Journal of Advanced Computer Science and Applications, 11(11). https://doi.org/10.14569/IJACSA.2020.0111171
Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58, 102310. https://doi.org/10.1016/J.IJINFOMGT.2021.102310
Pérez de Albéniz Iturriaga, A., Escolano Pérez, E., Pascual Sufrate, M. T., Lucas Molina, B., & Sastre i Riba, S. (2015). Metacognición en un proceso de aprendizaje autónomo y cooperativo en el aula universitaria. Contextos Educativos, 18, 95–108. https://doi.org/10.18172/con.2576
Prensky, M. (2001). Digital Natives, Digital Immigrants Part 1. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816
Ragin, C. C. (2000). Fuzzy-Set Social Science. University of Chicago Press.
Ragin, C. C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press. https://doi.org/10.7208/chicago/9780226702797.001.0001
Ragin, C. C., & Davey, S. (2022). Fuzzy-set/Qualitative comparative analysis 4.0. In Department of Sociology, University of California. http://www.socsci.uci.edu/~cragin/fsQCA/software.shtml
Ragin, C. C., & Rihoux, B. (2004). Qualitative Comparative Analysis (QCA): State of the Art and Prospects. Qualitative Methods, 3–13. https://doi.org/10.5281/zenodo.998222
Rozo, H., & Real, M. (2019). Pedagogical guidelines for the creation of adaptive digital educational resources: A review of the literature. Journal of Technology and Science Education, 9(3), 308. https://doi.org/10.3926/jotse.652
Russo, I., & Confente, I. (2019). From dataset to qualitative comparative analysis (QCA)—Challenges and tricky points: A research note on contrarian case analysis and data calibration. Australasian Marketing Journal, 27(2), 129–135. https://doi.org/https://doi.org/10.1016/j.ausmj.2018.11.001
Schneider, C. Q., & Wagemann, C. (2010). Standards of Good Practice in Qualitative Comparative Analysis (QCA) and Fuzzy-Sets. Comparative Sociology, 9(3), 397–418. https://doi.org/https://doi.org/10.1163/156913210X12493538729793
Schwieger, D., & Ladwig, C. (2018). Reaching and Retaining the Next Generation: Adapting to the Expectations of Gen Z in the Classroom. Information Systems Education Journal, 3, 16. http://iscap.info;http://isedj.org
Segura-Robles, A., Parra-González, M., & Gallardo-Vigil, M. (2020). Bibliometric and Collaborative Network Analysis on Active Methodologies in Education. Journal of New Approaches in Educational Research, 9(2), 259–274.
Soffer, T., & Cohen, A. (2019). Students’ engagement characteristics predict success and completion of online courses. Journal of Computer Assisted Learning, 35(3), 378–389. https://doi.org/10.1111/jcal.12340
Sotola, L. K., & Crede, M. (2021). Regarding Class Quizzes: a Meta-analytic Synthesis of Studies on the Relationship Between Frequent Low-Stakes Testing and Class Performance. Educational Psychology Review, 33(2), 407–426. https://doi.org/10.1007/s10648-020-09563-9
Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66, 463–472. https://doi.org/10.1016/j.jbusres.2012.12.021
Woodside, A. G. (2014). Embrace perform model: Complexity theory, contrarian case analysis, and multiple realities. Journal of Business Research, 67(12), 2495–2503. https://doi.org/10.1016/j.jbusres.2014.07.006
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Derechos de autor 2023 Pixel-Bit. Revista de Medios y Educación