- -

Recommending Learning Objects with Arguments and Explanations

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Recommending Learning Objects with Arguments and Explanations

Mostrar el registro completo del ítem

Heras, S.; Palanca Cámara, J.; Rodriguez, P.; Duque-Méndez, N.; Julian Inglada, VJ. (2020). Recommending Learning Objects with Arguments and Explanations. Applied Sciences. 10(10):1-18. https://doi.org/10.3390/app10103341

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/166335

Ficheros en el ítem

Thumbnail
Nombre: Heras;Palanca;Rodrguez ...
Tamaño: 902.1Kb
Formato: PDF
Descripción: Versión editorial
Abrir/Preview

Metadatos del ítem

Título: Recommending Learning Objects with Arguments and Explanations
Autor: Heras, Stella Palanca Cámara, Javier Rodriguez, Paula Duque-Méndez, Néstor Julian Inglada, Vicente Javier
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] The massive presence of online learning resources leads many students to have more information than they can consume efficiently. Therefore, students do not always find adaptive learning material for their needs and ...[+]
Palabras clave: Educational recommender systems , Explanations , Argumentation
Derechos de uso: Reconocimiento (by)
Fuente:
Applied Sciences. (eissn: 2076-3417 )
DOI: 10.3390/app10103341
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/app10103341
Código del Proyecto:
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2018%2F002/ES/TECNOLOGIES PER ORGANITZACIONS HUMANES EMOCIONALS/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095390-B-C31/ES/HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTING/
Agradecimientos:
This work was partially supported by MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government, and by the Generalitat Valenciana (PROMETEO/2018/002) project.
Tipo: Artículo

References

Zapalska, A., & Brozik, D. (2006). Learning styles and online education. Campus-Wide Information Systems, 23(5), 325-335. doi:10.1108/10650740610714080

Rodríguez, P., Heras, S., Palanca, J., Poveda, J. M., Duque, N., & Julián, V. (2017). An educational recommender system based on argumentation theory. AI Communications, 30(1), 19-36. doi:10.3233/aic-170724

Chen, L., & Pu, P. (2011). Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction, 22(1-2), 125-150. doi:10.1007/s11257-011-9108-6 [+]
Zapalska, A., & Brozik, D. (2006). Learning styles and online education. Campus-Wide Information Systems, 23(5), 325-335. doi:10.1108/10650740610714080

Rodríguez, P., Heras, S., Palanca, J., Poveda, J. M., Duque, N., & Julián, V. (2017). An educational recommender system based on argumentation theory. AI Communications, 30(1), 19-36. doi:10.3233/aic-170724

Chen, L., & Pu, P. (2011). Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction, 22(1-2), 125-150. doi:10.1007/s11257-011-9108-6

He, C., Parra, D., & Verbert, K. (2016). Interactive recommender systems: A survey of the state of the art and future research challenges and opportunities. Expert Systems with Applications, 56, 9-27. doi:10.1016/j.eswa.2016.02.013

Vig, J., Sen, S., & Riedl, J. (2009). Tagsplanations. Proceedings of the 14th international conference on Intelligent user interfaces. doi:10.1145/1502650.1502661

Symeonidis, P., Nanopoulos, A., & Manolopoulos, Y. (2009). MoviExplain. Proceedings of the third ACM conference on Recommender systems - RecSys ’09. doi:10.1145/1639714.1639777

Fogg, B. J. (2002). Persuasive technology. Ubiquity, 2002(December), 2. doi:10.1145/764008.763957

Benbasat, I., & Wang, W. (2005). Trust In and Adoption of Online Recommendation Agents. Journal of the Association for Information Systems, 6(3), 72-101. doi:10.17705/1jais.00065

Sikka, R., Dhankhar, A., & Rana, C. (2012). A Survey Paper on E-Learning Recommender System. International Journal of Computer Applications, 47(9), 27-30. doi:10.5120/7218-0024

Salehi, M., Pourzaferani, M., & Razavi, S. A. (2013). Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model. Egyptian Informatics Journal, 14(1), 67-78. doi:10.1016/j.eij.2012.12.001

Dwivedi, P., & Bharadwaj, K. K. (2013). e-Learning recommender system for a group of learners based on the unified learner profile approach. Expert Systems, 32(2), 264-276. doi:10.1111/exsy.12061

Tarus, J. K., Niu, Z., & Mustafa, G. (2017). Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning. Artificial Intelligence Review, 50(1), 21-48. doi:10.1007/s10462-017-9539-5

BRIGUEZ, C. E., CAPOBIANCO, M., & MAGUITMAN, A. G. (2013). A THEORETICAL FRAMEWORK FOR TRUST-BASED NEWS RECOMMENDER SYSTEMS AND ITS IMPLEMENTATION USING DEFEASIBLE ARGUMENTATION. International Journal on Artificial Intelligence Tools, 22(04), 1350021. doi:10.1142/s0218213013500218

Recio-García, J. A., Quijano, L., & Díaz-Agudo, B. (2013). Including social factors in an argumentative model for Group Decision Support Systems. Decision Support Systems, 56, 48-55. doi:10.1016/j.dss.2013.05.007

Briguez, C. E., Budán, M. C. D., Deagustini, C. A. D., Maguitman, A. G., Capobianco, M., & Simari, G. R. (2014). Argument-based mixed recommenders and their application to movie suggestion. Expert Systems with Applications, 41(14), 6467-6482. doi:10.1016/j.eswa.2014.03.046

Klašnja-Milićević, A., Ivanović, M., & Nanopoulos, A. (2015). Recommender systems in e-learning environments: a survey of the state-of-the-art and possible extensions. Artificial Intelligence Review, 44(4), 571-604. doi:10.1007/s10462-015-9440-z

The VARK Questionnaire-Spanish Versionhttps://vark-learn.com/wp-content/uploads/2014/08/The-VARK-Questionnaire-Spanish.pdf

GARCÍA, A. J., & SIMARI, G. R. (2004). Defeasible logic programming: an argumentative approach. Theory and Practice of Logic Programming, 4(1+2), 95-138. doi:10.1017/s1471068403001674

Gelfond, M., & Lifschitz, V. (1991). Classical negation in logic programs and disjunctive databases. New Generation Computing, 9(3-4), 365-385. doi:10.1007/bf03037169

Snow, R. E. (1991). Aptitude-treatment interaction as a framework for research on individual differences in psychotherapy. Journal of Consulting and Clinical Psychology, 59(2), 205-216. doi:10.1037/0022-006x.59.2.205

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem