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PALE 2017 : 7th International Workshop on Personalization Approaches in Learning Environments


When Jul 9, 2017 - Jul 9, 2017
Where Bratislava
Submission Deadline Apr 20, 2017
Notification Due May 20, 2017
Final Version Due May 28, 2017
Categories    personalization   adaptivity   learner modeling   learning environment

Call For Papers

PALE 2016 Workshop is held in conjunction with ACM UMAP 2017 Conference ( It is a follow-up of the six previous PALE editions.

The focus of this workshop series is on the different perspectives, in which personalization can be addressed in learning environments. Its aim is to share and discuss the new trends in current research on how user modeling and associated artificial intelligent techniques are able to contextualize and manage the increasing amount of information coming from the task at hand and its surrounding environment, in order to provide personalized learning support, which is sensitive to learners and their context. This covers many interrelated fields, including intelligent tutoring systems, learning management systems, personal learning environments, serious games, agent-based learning environments, and informal workplace learning settings. Moreover, we are especially interested in the enhanced sensitivity towards the management of vast data coming from learners’ interactions (like sensor detection of affect in context) and technological deployment (including web, mobiles, tablets, tabletops, wearable technology), and how can this wide range of situations and features impact on modeling the learner context and interaction. Furthermore, we aim to cover the need of personalized learning in various settings, ranging from formal to informal ones.

The higher-level research question to be addressed in the workshop is: “How to deal with the increasing amount of information available from various resources and contexts, in order to provide effective personalized assistance in learning situations?” PALE workshop includes (but is not limited to) the following topics:

- Learner and context modeling
- Modeling affective, motivational, and metacognitive aspects of learning
- Big data and visual narratives in education
- Adaptive mobile learning
- Learning recommendations and explanations
- Educational data mining and learning analytics
- Wearable technologies and augmented reality in adaptive training
- Personalization in MOOCs and educational games
- Cognitive and meta-cognitive scaffolding
- Open-corpus educational systems
- Social issues in personalized learning environments
- Reusability, interoperability, scalability
- Evaluation of adaptive learning environments

Workshop Format

Following the experience from previous editions of this and related workshops, PALE combines the classic 'mini-conferences' approach with working group meetings around a specific problem. It follows the Learning Cafe methodology to promote discussions on some of the open issues coming from the presented papers. Each Learning Cafe consists of brief presentations of the key questions posed and small group discussions with participants randomly grouped at tables. Each table is moderated by one expert in the topic under discussion (mostly the presenter of the paper who has addressed the issue) and participants change tables during the discussion with the aim to share ideas among the groups.

Submission Details and Publication

To keep the focus on the key issues to be discussed in the workshop, contributions are suggested to be prepared in 6 page limit (including references). Papers must be formatted using the ACM SIG proceedings template and submitted via EasyChair. Each submission will be reviewed by at least 3 PC members. Accepted papers will be published in the ACM Extended Proceedings of UMAP 2017. PALE workshop papers will be available also at the workshop web page.

Submission templates:
Easychair submission site:

Organizing Committee

Milos Kravcik, RWTH Aachen University, Germany
Olga C. Santos, aDeNu Research Group, UNED, Spain
Jesus G. Boticario, aDeNu Research Group, UNED, Spain
Maria Bielikova, Slovak University of Technology, Slovakia
Tomas Horvath, Eötvös Lorand University, Hungary

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