• Publications
  • Influence
Panorama of Recommender Systems to Support Learning
In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework and analysed for their contribution to the evolution of the RecSysTEL research field.
Recommender Systems for Technology Enhanced Learning
The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.
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 and design methodologies, such as TORMES, when developing systems that address the psychomotor learning domain.
Usability in e-Learning Platforms : heuristics comparison between Moodle , Sakai and dotLRN
Recently, educational institutions largely adopted open source elearning platforms. Several studies and comparisons between those platforms were conducted. However, these analyses were more focused
An Evaluation of Mouse and Keyboard Interaction Indicators towards Non-intrusive and Low Cost Affective Modeling in an Educational Context
A series of indicators, which derive from user's interactions with mouse and keyboard, are proposed, to evaluate their use in identifying affective states and behavior changes in an e-learning platform by means of non-intrusive and low cost methods.
Extending web-based educational systems with personalised support through User Centred Designed recommendations along the e-learning life cycle
An educational-oriented approach for building personalised e-learning environments that focuses on putting the learners' needs in the centre of the development process is provided.
Affective issues in Semantic Educational Recommender Systems
The benefits of considering affective issues in educational recommender systems are discussed and 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 is described.
Modeling recommendations for the educational domain
A semantic recommendations model is defined that can be used to describe the recommendations for technology enhanced learning that should be guided by educational objectives, and not only by the users’ preferences.
An Open Sensing and Acting Platform for Context-Aware Affective Support in Ambient Intelligent Educational Settings
Supporting learners affectively while carrying out stressful educational activities is an open research issue. It requires the appropriate infrastructure for recognizing emotional states and reacting
Practical guidelines for designing and evaluating educationally oriented recommendations
Practical guidelines to produce personalised recommendations that are meant to foster active learning in online courses are compiled, targeting to cope with one of the main challenges in current massive open online courses.