Publications

Call on Student Dropout

More information about this call:
"Bringing New Solutions to the Challenges of Predicting and Countering Student Dropout in Higher Education"

Related publications:

Alvarado-Uribe, J.; Mejía-Almada, P.; Masetto Herrera, A.L.; Molontay, R.; Hilliger, I.; Hegde, V.; Montemayor Gallegos, J.E.; Ramírez Díaz, R.A.; Ceballos, H.G. Student Dataset from Tecnologico de Monterrey in Mexico to Predict Dropout in Higher Education. Data 2022, 7, 119. https://doi.org/10.3390/data7090119
Talamás-Carvajal, J. A., & Ceballos, H. G. (2023). A stacking ensemble machine learning method for early identification of students at risk of dropout. Education and Information Technologies, https://doi.org/10.1007/s10639-023-11682-z
Talamas-Carvajal, J. A. (2023). The Middle-Man Between Models and Mentors: Using SHAP Values to Explain Dropout Prediction Models in Higher Education. In Companion Proceedings 13th International Conference on Learning Analytics & Knowledge (LAK23), pp. 68-70.
Kuz, A., & Morales, R. (2023). Ciencia de Datos Educativos y aprendizaje automático: un caso de estudio sobre la deserción estudiantil universitaria en México. Education in the Knowledge Society (EKS), 24, e30080. https://doi.org/10.14201/eks.30080
Gonzalez-Nucamendi, A., Noguez, J., Neri, L., Robledo-Rella, V., & García-Castelán, R.M.G. (2023). Predictive analytics study to determine undergraduate students at risk of dropout. Front. Educ. 8:1244686. doi: 10.3389/feduc.2023.1244686
Rodríguez-Hernández, C. F., Musso, M., & Cascallar, E. (2023, March 9-11). An Artificial Neural Network Approach to Analyze Students' Dropout in Higher Education [Poster presentation]. International Convention of Psychological Science (ICPS) 2023, Brussels, Belgium.
A. Gonzalez-Nucamendi, J. Noguez, L. Neri, V. Robledo-Rella and R. Guadalupe Garcia-Castelan, "Analysis of Categorical and Numerical Variables for Dropout Intervention in Educational Settings," in 2023 IEEE Frontiers in Education Conference (FIE), College Station, TX, USA, 2023 pp. 1-8. doi: 10.1109/FIE58773.2023.10343519
E. S. Karabacak and Y. Yaslan, "Comparison of Machine Learning Methods for Early Detection of Student Dropouts," 2023 8th International Conference on Computer Science and Engineering (UBMK), Burdur, Turkiye, 2023, pp. 376-381, doi: https://doi.org/10.1109/UBMK59864.2023.10286747
Velarde-Camaqui, D., Peláez-Sánchez, I.C., Viehmann, C. (2024). Unveiling Success: An Analysis of Academic Performance Predictors in a Private High School in Mexico Through Learning Analytics. In: Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (eds) Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-97-1814-6_82
Talamás-Carvajal, J.A. (2024). Research Plan on the Effects of Interventions on Dropout Predictions for Higher Education Institutions. In: Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (eds) Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-97-1814-6_77

Call on Competency-based Higher Education

More information about this call:
"Fostering the Analysis of Competency-based Higher Education"

Related publications:

Glasserman-Morales, L. D., Alcantar-Nieblas, C., & Sisto, M. I. (2024). Demographic and school factors associated with digital competences in higher education students. Contemporary Educational Technology, 16(2), ep498. https://doi.org/10.30935/cedtech/14288
Mejía-Manzano, L.A.; Vázquez-Villegas, P.; Díaz-Arenas, I.E.; Escalante-Vázquez, E.J.; Membrillo-Hernández, J. Disciplinary Competencies Overview of the First Cohorts of Undergraduate Students in the Biotechnology Engineering Program under the Tec 21 Model. Educ. Sci. 2024, 14, 30. https://doi.org/10.3390/educsci14010030
Talamás-Carvajal, J. A., Ceballos, H. G., & Ramírez-Montoya, M.-S. (2024). Identification of Complex Thinking Related Competencies: The Building Blocks of Reasoning for Complexity. Journal of Learning Analytics, 11(1), 37-48. https://doi.org/10.18608/jla.2024.8079

Call on Remote Labs

More information about this call:
"Measuring the impact on the teaching/learning process derived from the introduction and experimentation with remote laboratories in higher education STEM courses."

N. Assaf and L. F. Morán-Mirabal, "Instructional Usability and Learner-User eXperience Assessment in a Virtual Reality Educational Milieu: A Deductive Tech-Instructionality Model from EdTech," 2023 Future of Educational Innovation-Workshop Series Data in Action, Monterrey, Mexico, 2023, pp. 1-8, https://doi.org/10.1109/IEEECONF56852.2023.10104873

IFE Data Hub Private Collections

Ramirez-Montoya, M., Ceballos, H., Martínez-Pérez, S., & Romero-Rodríguez, L. (2023). Impact of Teaching Workload on Scientific Productivity: Multidimensional Analysis in the Complexity of a Mexican Private University. Publications 11(2), June 2023, Article number 27. https://www.mdpi.com/2304-6775/11/2/27
Butt, S., Mejía-Almada, P., Alvarado-Uribe, J., Ceballos, H., Sidorov, G., Gelbukh, A. (2023). MF-SET: A Multitask Learning Framework for Student Evaluation of Teaching. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 1. FTC 2023. Lecture Notes in Networks and Systems, vol 813. Springer, Cham. https://doi.org/10.1007/978-3-031-47454-5_20
Gallardo, K., Butt, S., Ceballos, H. (2023). Improvement of Teaching Competencies Training in Higher Education Faculty Based on Student Evaluations of Teaching and AI Systems. In: Mesquita, A., Abreu, A., Carvalho, J.V., Santana, C., de Mello, C.H.P. (eds) Perspectives and Trends in Education and Technology. ICITED 2023. Smart Innovation, Systems and Technologies, vol 366. Springer, Singapore. https://doi.org/10.1007/978-981-99-5414-8_51
Talamas-Carvajala J., & Ceballos-Cancino H. (2024). Use of SHAP values for identifying differences in behaviors for subpopulations under intervention. CEUR Workshop Proceedings, 3667, pp. 139-149. https://ceur-ws.org/Vol-3667/DS-LAK24_paper_4.pdf

IFE LL&DH Publications

L.F. Morán-Mirabal, J. Alvarado-Uribe, and H. Ceballos (2023). Using AI for Educational Research in Multimodal Learning Analytics. In M. Cebral-Loureda, E. G. Rincón-Flores, & G. Sánchez-Ante (Eds.), What AI Can Do? Strengths and Limitations of Artificial Intelligence (First edition., pp. 155-176). Chapman & Hall/CRC (Taylor & Francis Group). https://doi.org/10.1201/b23345
Castañeda-Garza, G., Ceballos Cancino, H. G., & Mejía Almada, P. G. (2023). Artificial Intelligence for Mental Health: A Review of AI Solutions and their Future. In M. Cebral-Loureda, E. G. Rincón-Flores, & G. Sánchez-Ante (Eds.), What AI Can Do? Strengths and Limitations of Artificial Intelligence (First edition., pp. 373–400). Chapman & Hall/CRC (Taylor & Francis Group). https://doi.org/10.1201/b23345
K. Gallardo, R. E. Díaz-Méndez, J. A. González, P. G. Mejía-Almada and H. G. Ceballos, "Tailor-Made Nutrition Education for University Students through Data Science," 2023 Future of Educational Innovation-Workshop Series Data in Action, Monterrey, Mexico, 2023, pp. 1-7, https://doi.org/10.1109/IEEECONF56852.2023.10104772.
V. V. Pineda-Romero, C. E. Orozco-Mora and H. G. Ceballos, "Factors to improve online education: A study on the impact of COVID-19 on Delhi students," 2023 Future of Educational Innovation-Workshop Series Data in Action, Monterrey, Mexico, 2023, pp. 1-8, https://doi.org/10.1109/IEEECONF56852.2023.10104773.
Hilliger, I., Ceballos, H. G., Maldonado-Mahauad, J., & Ferreira, R. (2024). Applications of Learning Analytics in Latin America. Journal of Learning Analytics, 11(1), 1-5. https://doi.org/10.18608/jla.2024.8409
Bautista Godínez, T., Castañeda Garza, G., Pérez Mora, R., Ceballos, H. G., Luna de la Luz, V., Moreno-Salinas, J. G., Zavala-Sierra, I. R., Santos-Solórzano, R., Moreno Arellano, C. I., & Sánchez-Mendiola, M. (2024). Perspectives and Opportunities for Learning Analytics Integration: A Qualitative Study in Mexican Universities. Journal of Learning Analytics, 11(1), 49-66. https://doi.org/10.18608/jla.2024.8125
Ceballos, H.G., Castañeda, G., Alvarado-Uribe, J., Mejía-Almada, P. & Martínez-Carranza, U. (2024). The Data Hub of the Institute for the Future of Education. In LAK24 Conference Proceedings. The 14th International Conference on Learning Analytics & Knowledge. pp. 33-36. https://www.solaresearch.org/wp-content/uploads/2024/03/LAK24_CompanionProceedings.pdf