fondo titulo
ANTONIO RODRIGUEZ ANAYA

ANTONIO RODRIGUEZ ANAYA

PROFESOR CONTRATADO DOCTOR

INTELIGENCIA ARTIFICIAL

ESCUELA TÉCN.SUP INGENIERÍA INFORMÁTICA

arodriguez@dia.uned.es

(+34) 91398-6550

Academic Information

Ph.D., Artificial Intelligence, UNED, 2009
Thesis: Collaboration Research Using Data Mining Tools In Open Collaborative Learning Environments With The Aims Of Improving The Management Of Collaboration Process

Bachelor of Astrophysics, Universidad Complutense de Madrid, 1999

Academic positions held

Mathematical logic 2004/2005 2005/2006 UNED

Digital electronic 2003/2004 2014/2015 UNED

Artificial intelligence and engineering based on Knowledge 2004/2005 2014/2015 UNED

Learning interactive system 2013/2014 2017/2018 UNED

Applications of the AI for the human and sustainable development 2014/2015 2017/2018 UNED

Analysis Of Collaborative Environments And Social Networks 2016/2017 2017/2018 UNED

Research activity

Member  Research group aDeNu (https://adenu.ia.uned.es/web/), support by UNED (Ref: G74E25),  02/05/2004, Present

Research visitor Fraunhofer Institut: Angewandte Informationstechnik, in Sankt Augustin/Bonn, Germany, 01/07/2007, 01/10/2007

Research visitor Max Planck Institute für Astronomie, in Heidelberg, Germany, 01/10/2012 01/01/2013

Research visitor Universidad di Pisa, in Pisa, Italia, 01/04/2018 01/07/2018

Professional experience

He is currently a PhD contracted professor in the Department of Artificial Intelligence at the National Distance Education University (UNED), a member of the aDeNu research group at UNED.

He is the author of national and international scientific publications, and has participated as a researcher in national and European projects. His research activity has focused on the application of data mining techniques to analyze learning processes in collaborative environments.

His teaching activity in undergraduate and postgraduate courses is linked to the analysis and development of collaborative environments and social networks, as well as adaptive teaching and learning systems.

Research

RESEARCH GROUPS

  • aDeNu aDeNu (Adaptive Dynamic online Educational systems based oN User modelling) is a research and development (R&D) group and it belongs to the Artificial Intelligence Department of the Computer Science School of the Spanish National University for Distance Education (UNED). This group is specialized in the development of adaptive interfaces through Internet, which intend to reduce the problems of decentralized and non-presential education. + info

RESEARCH PROJECTS

  • Active Learning For Adaptive Internet Union Europea - 5º Programa Marco I+D  Colaborador 2002-2005
  • SAMAP SAMAP: An User-Oriented Adaptive System For Planning Tourist Visits Ministerio de Educacion y Ciencia  Colaborador 2003-2005
  • EU4ALL European Unified Approach for Assisted Lifelong Learning European Commision (6th Framework Programme) Colaborador 2006-2010
  • INT2AFF Enfoque de desarrollo INTeligente e INTrasujeto para mejorar acciones en sistemas adaptativos educativos que consideran el estado AFFectivo (INT2AFF) Ministerio de Ciencia, Innovación y Universidades  Colaborador 2018-2022

N.º of recognized sections of research activity

1

Publications

  • PUBLICATIONS IN MAGAZINES Castillo, L., Armengol, E., Onaindía, E., Sebastiá, L., González-Boticario, J., Rodríguez, A., Fernández, S., Arias, J., Borrajo, D. (2008). SAMAP: An user-oriented adaptive system for planning tourist visits. Expert Systems with Applications, 34(2), 1318-1332.

    Anaya, A. R., & Boticario, J. G. (2009). Clustering learners according to their collaboration. 13TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (540-545)

    Anaya, A. R., & Boticario, J. G. (2009, June). Reveal the Collaboration in a Open Learning Environment. In International Work-Conference on the Interplay Between Natural and Artificial Computation (pp. 464-475). Springer, Berlin, Heidelberg.

    Anaya, A. R., & Boticario, J. G. (2011). Application of machine learning techniques to analyse student interactions and improve the collaboration process. Expert Systems with Applications, 38(2), 1171-1181.

    Anaya, A. R., & Boticario, J. G. (2011). Content-free collaborative learning modeling using data mining. User Modeling and User-Adapted Interaction, 21(1-2), 181-216.

    Anaya, A. R., Luque, M., & García-Saiz, T. (2013). Recommender system in collaborative learning environment using an influence diagram. Expert Systems with Applications, 40(18), 7193-7202.

    Anaya, A. R., & Boticario, J. G. (2013). A domain-independent, transferable and timely analysis approach to assess student collaboration. International Journal on Artificial Intelligence Tools, 22(04), 1350020

    Anaya, A. R., Luque, M., & Peinado, M. (2016). A visual recommender tool in a collaborative learning experience. Expert Systems with Applications, 45, 248-259.

    APA

    Anaya, A. R., Luque, M., Letón, E., & Hernández‐del‐Olmo, F. (2019). Automatic assignment of reviewers in an online peer assessment task based on social interactions. Expert Systems, 36(4), e12405.

  • PUBLICATIONS AT CONFERENCES Helping the Tutor to Manage a Collaborative Task in a Web-Based Learning Environment** 4 9 Artificial Intelligence in Education (Aied) Int. Contribución Actas del congreso 2003

    Support to Learners Based on Implicit Collaborative Interactions** 4 2 IAIC 04. Workshop Artificial Intelligence in Computer Supported Collaborative Learning Int. Contribución Actas del workshop 2004

    Knowledge Discovery Tools for the Spanish Virtual Observatory** 3  Joint European And National Astronomy Meeting Int. Poster Actas del congreso 2004

    Clustering Learners According to their Collaboration** 2 5 The 13th International Conference On Computer Supported Cooperative Work In Design Int. Contribución y presentación oral Actas del congreso 2009

    Reveal the Collaboration in a Open Learning Environment** 2 11 3rd International Work-Conference On The Interplay Between Natural And Artificial Computation Int. Poster Actas del congreso 2009

    A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks** 2 9 2nd International Conference On Educational Data Mining Int. Poster y presentación oral Actas del congreso 2009

    Ranking Learner Collaboration According to their Interactions** 2 6 The 1st Annual Engineering Education Conference (Educon) Int. Contribución y presentación oral Actas del congreso 2010

    Towards Improvements on Domain-Independent Measurements for Collaborative Assessment** 2 2 The 4th International Conference On Educational Data Mining Int. Poster Actas del congreso 2011

    An influence diagram

    for the collaboration in e-learning environments**

     2 10 5th. International Work-Conference On The

    Interplay Between Natural And Artificial Computation Int. Contribución Actas del congreso 2013

    Collaboration analytics in the socialization era: Advantages and difficulties 1 52 International Workshop “LASI-Local Madrid” Int. Ponencia  2014

    Towards Using Influence Diagram on Social-Network Based Analysis for Managing Students’ Collaborations** 4 2 1th International Conference on Computer Supported Collaborative Learning Int. Contribución y poster Actas del congreso 2015

    An Approach of Collaboration Analytics in MOOCs Using Social Network Analysis and Influence Diagram** 4 4 8th International Conference on Educational Data Mining Int. Contribución y presentación oral Actas del congreso 2015

  • PUBLICACIONES EN LÍNEA Ir a Google Scholar

    Ir a Orcid

Otros

Other activities

Summer courses

Participation in the summer course Technologies in the knowledge society and distance education. Programming, augmented reality, artificial intelligence, active approaches, and educational technology dated July 4-6, 2022.

Others

Language Level
English Fluent
Germany Beginner
Finnish Beginner

Technology
Database server: Informix (Admin and Developer), Oracle (developer), Postgresql (Admin and Developer)
Computer science languages: sql (high), pl/sql (high), Java and javascrip (high), LISP (medium), TCL (medium), PERL (low), C (low), Fortran (low).
Meta language: HTML (high), OWL (high), XML (medium).
Data mining tools: Weka (high), Gephi (high), R (medium), Python (medium)