PALE 2011:
Personalization Approaches
in Learning Environments


The topics of interest of this workshop include but are not limited to the following: 

  • Motivation, benefits, and issues of personalization of learning
  • Approaches for the personalization of inclusive learning environments
  • Approaches for the personalization of responsive learning environments
  • Approaches for the personalization of interactive learning environments
  • Techniques and Methods
  • Results and Metrics
  • Social and Educational Issues
  • Use of Pedagogic Conversational Agents
  • Affective Computing


The higher-level research question to be addressed in the workshop is the following: Which approaches can be followed to personalize learning environments?

Nevertheless, each Learning Café is focused on specific research questions, as follows.

Learning Café 1 - APLEC
Organizers: Diana Perez-Marin, Susan Bull and Noboru Matsuda

  • Which pedagogic agents are currently taking into account information of the learner model to guide the dialogue?
  • What does an effective conversation between the student and the agent look like? 
  • How could a learner model be used to adapt the pedagogical agent to the student to provide adaptive emotional support?
  • How should the effect of such an adaptation be measured?
  • How could the affect of a pedagogical agent improve a student’s motivation?

Learning Café 2 - ROLE
Organizers: Milos Kravcik, Alexander Nussbaumer and Effie Law

  • How can a whole learning environment or its components be personalized to the needs of learners?
  • What can be personalized and for which purposes?
  • Which models and techniques can be used for personalization?
  • How to adjust the user control of personalization and adaptation to his or her needs?
  • How can adaptive support and guidance for personalization be provided?
  • Which monitoring or tracking methods can be used to automatically create learner profiles?

Learning Café 3 – TUMAS-A:
Organizers: Olga C. Santos and Jesus G. Boticario

  • Which scenarios for personalized inclusive e-learning (PIL) systems can be identified?
  • What user features are required to support PIL scenarios?
  • Which computational methods in PIL exist?
  • What evaluation approaches can be used in PIL scenarios?
  • Which developing methodologies are to be used in PIL?
  • How current standards can be used/adapted/extended to cope with PIL?
  • Which multi-modal and context-based interaction issues impinge on PIL?
  • What are the most appropriate support and guidance approaches to provide adaptation in PIL?