O. Santos

Publications
Influence

Panorama of Recommender Systems to Support Learning

H. Drachsler, K. Verbert, O. Santos, N. Manouselis
Engineering, Computer Science
Recommender Systems Handbook
14 December 2015

We present an extended version of a state-of-the-art review on recommender systems (RecSys) in Technology Enhanced Learning (TEL). Expand

Recommender Systems for Technology Enhanced Learning

N. Manouselis, H. Drachsler, K. Verbert, O. Santos
Computer Science
Springer New York
25 April 2014

An introduction to the deployment of recommender systems in TEL settings, keeping in mind the particularities of this application domain. Expand

Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning

O. Santos
Psychology, Computer Science
International Journal of Artificial Intelligence…
7 March 2016

This paper argues that the research field of Artificial Intelligence in Education (AIED) can benefit from integrating recent technological advances (e.g., wearable devices, big data processing, 3D modelling,3D printing, ambient intelligence) and design methodologies, such as TORMES, when developing systems that address the psychomotor learning domain. Expand

Usability in e-Learning Platforms : heuristics comparison between Moodle , Sakai and dotLRN

L. Martin, D. R. Martínez, O. Revilla, M. J. Aguilar, O. Santos, J. Boticario
2008

Recently, educational institutions largely adopted open source elearning platforms. Several studies and comparisons between those platforms were conducted. However, these analyses were more focused… Expand

Integration of Educational Specifications and Standards to Support Adaptive Learning Scenarios in ADAPTAPlan

Silvia Baldiris, O. Santos, C. Barrera, J. Boticario, J. Velez, R. Fabregat
Computer Science
Int. J. Comput. Sci. Appl.
2008

ADAPTAPlan project provides dynamic assistance for reducing authors’ effort in developing instructional design tasks using user modelling, planning and machine learning techniques and making a pervasive use of educational specifications and standards. Expand

An Evaluation of Mouse and Keyboard Interaction Indicators towards Non-intrusive and Low Cost Affective Modeling in an Educational Context

Sergio Salmeron-Majadas, O. Santos, J. Boticario
Computer Science
KES
2014

We propose a series of indicators, which derive from user's interactions with mouse and keyboard. Expand

Extending web-based educational systems with personalised support through User Centred Designed recommendations along the e-learning life cycle

O. Santos, J. Boticario, D. Pérez
Computer Science
Sci. Comput. Program.
1 August 2014

We provide an educational-oriented approach for building personalised e-learning environments that focuses on putting the learners' needs in the centre of the development process. Expand

Affective issues in Semantic Educational Recommender Systems

O. Santos, J. Boticario
Computer Science, Psychology
RecSysTEL@EC-TEL
2012

We discuss the benefits of considering affective issues in educational recommender systems and describe the extension of the Semantic Educational Recommender Systems (SERS) approach, which is characterized by its interoperability with e-learning services, to deal with learners’ affective traits in educational scenarios. Expand

Modeling recommendations for the educational domain

O. Santos, J. Boticario
Computer Science
RecSysTEL@RecSys
2010

We present TORMES, a semantic recommendations model that can be used to describe the recommendations for technology enhanced learning. Expand

Toward interactive context-aware affective educational recommendations in computer-assisted language learning

O. Santos, Mar Saneiro, J. Boticario, M. Rodriguez-Sánchez
Computer Science
New Rev. Hypermedia Multim.
2 January 2016

This work explores the benefits of supporting learners affectively in a context-aware learning situation. Expand

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