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CfP - Personalization Approaches in Learning Environments
Workshops (PALE 2018)
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**Apologies for cross-posting**
CALL FOR PAPERS
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PALE 2018: 8th International Workshop on Personalization
Approaches in Learning Environments
http://adenu.ia.uned.es/workshops/pale2018/
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.
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PALE 2018, June 27-30, 2018, London (UK)
In conjunction with AIED, 19th International Conference on
Artificial Intelligence in Education
https://aied2018.utscic.edu.au/
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PALE 2018, July 8-11, 2018, Singapore
In conjunction with UMAP, 26th International Conference on User
Modelling, Adaptation and Personalization
http://www.um.org/umap2018/
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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:
http://www.acm.org/publications/proceedings-template
Easychair submission site:
https://easychair.org/conferences/?conf=pale2018
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)
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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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