[AISWorld] CfP - Personalization Approaches in Learning Environments Workshops (PALE 2018)

Jesus G. Boticario jgb at dia.uned.es
Mon Apr 16 11:21:10 -04 2018


CfP - Personalization Approaches in Learning Environments Workshops (PALE 2018)

**Apologies for cross-posting**

PALE 2018: 8th International Workshop on Personalization Approaches in Learning Environments
Submission deadline:  April 22, 2018 (extended)

The PALE 2018 workshop is a follow-up of the seven previous PALE editions.
This year, for the first time, the workshop will be jointly organized at both AIED and UMAP conferences.


PALE 2018, June 27-30, 2018, London (UK)

In conjunction with AIED, 19th International Conference on Artificial Intelligence in Education


PALE 2018, July 8-11, 2018, Singapore

In conjunction with UMAP, 26th International Conference on User Modelling, Adaptation and Personalization


Submission deadline for both PALE sessions: April 22, 2018 (extended)

The focus of the PALE workshop series is put on the different and complementary perspectives how personalization can be provided in various learning contexts (e.g. informal, workplace, lifelong, mobile, contextualized, and self-regulated learning). Its aim is to share and discuss the new trends in current research on how artificial intelligent techniques and user modelling 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.

This workshop edition is specially focused on the enhanced sensitivity towards the management of big educational data coming from learners' interactions (e.g., multimodal sensor detection of attention and affect) and technological deployment (including web, mobiles, tablets, tabletops), and how can this wide range of situations and features impact on modeling the learner interaction and context. Furthermore, we aim to cover the demanding need of personalized learning in wider contexts ranging from daily life activities to massive open online courses (MOOCs). Nonetheless, and with this motivation in mind, the sessions at each conference aim at specific topics, as follows.

* PALE Session at AIED *
The higher-level research question to be addressed in this workshop session is: "Which approaches can be followed to cater for the increasing amount of information available from immediate (e.g. in terms of wearable devices) to broader contexts in order to provide effective and personalized assistance in learning situations bridging the behavioral and the computational?" Thus, it captures current trends of the research fields of AIED, learning sciences, learning analytics as well as multimodal interaction research in HCI. The AIED session of PALE includes (but is not limited to) the following topics:

- User engagement in learning processes
- Data processing within and across learning situations
- Ambient intelligence
- Learner and context awareness
- Cognitive and meta-cognitive scaffolding
- Adaptive mobile learning
- Wearable devices for sensing and acting in ubiquitous learning scenarios
- Tracking technologies for accessible learning for all

* PALE Session at UMAP *
This workshop session is specially focused on analyzing both learning and teaching situations as well as providing explainable support, thus particularizing the research question to: "Which approaches can be followed to cater for the increasing amount of information available from immediate (e.g. in terms of wearable devices) to broader contexts in order to provide effective and personalized assistance in learning and teaching situations?" The UMAP session of PALE will deal mainly with the following topics:

- Affective computing
- Big data in education
- Personal and context modeling
- Personalization in MOOCs
- Learning recommendation and explanations
- Recommender systems for teaching
- Social issues in personalized learning environments
- Open-corpus educational systems
- 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 on http://ceur-ws.org/. PALE workshop papers will be available also at the workshop web page.

Submission templates:

Easychair submission site:

Organizing Committee

Milos Kravcik, Educational Technology Lab, DFKI GmbH, Berlin, Germany
Olga C. Santos, aDeNu Research Group, UNED, Spain
Jesus G. Boticario, aDeNu Research Group, UNED, Spain
Maria Bielikova, Slovak University of Technology in Bratislava, Slovakia
Tomas Horvath, Eotvos Lorand University, Hungary
Ilaria Torre, TEL&DH Research Group, DIBRIS, Genoa University, Italy (AIED)
Filippo Sciarrone, Faculty of Engineering, Roma Tre University, Italy (UMAP)


J. G. Boticario               http://www.ia.uned.es/personal/jgb

Head of aDeNu
Research Group           http://adenu.ia.uned.es
Full Professor
E.T.S. Ingeniería Informática, UNED
Dpto. Inteligencia Artificial

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