PALE 2015:
Personalization Approaches
in Learning Environments

Schedule

The main goal of this workshop is to compile all discussion topics regarding user modeling and personalization in the educational domain following a well-established methodology called the Learning Cafe to involve the participation of relevant actors. This workshop format aims to foster interactive presentations and constructive work. It combines presentations of original achievements with creative group work around specific topics.

Thus, following the experience in previous editions of this and related workshops, PALE combines the classic 'mini-conferences' approach with working group meetings around a specific problem to promote discussions on open issues related to personalization in learning environments.

In addition, this year we are pleased to announce an invited talk by Judy Kay, who knows very well the workshop methodology, as has been actively involved in previous editions of PALE.

June 30th, 2015

In this ocasion, 3 Learning Cafes are set up, as scheduled below. Each one consists in brief presentations of the key questions posed and small group discussions with participants randomly grouped at 2 tables. Each table will be moderated by one expert in the topic under discussion (mostly the presenter of the paper who has addressed the issue) and participants will change tables during the discussion with the aim to share ideas among the groups.

  • 08:00 - 09:00 Registration at UMAP.
  • 09:00 - 09:10 PALE 2015 Introduction [slides].
  • 09:10 - 10:30 Keynote: Judy Kay [1]; [slides].
  • 10:30 - 11:00 Coffee Break.
  • 11:00 - 12:30 Session 1: 2 presentations, Learning Café, Summary.
  • 12:30 - 14:00 Lunch Break.
  • 14:00 - 15:30 Session 2: 2 presentations, Learning Café, Summary.
  • 15:30 - 16:00 Session 3 - part I: 2 presentations.
  • 16:00 - 16:30 Coffee Break.
  • 16:30 - 17:30 Session 3 - part II: Learning Café, Summary.
  • 17:30 - 18:00 PALE 2015 conclusions.

The papers presented and discussed in each session are the following:

Session 1: Adaptation
  • 11:00 - 11:15 Benefits and costs of emphasis adaptation in study workflows (Tintarev et al.) [slides].
  • 11:15 - 11:30 The Student Advice Recommender Agent: SARA (Greer et al.) [slides].
  • 11:30 - 11:55 Learning Café 1 - round 1.
  • 11:55 - 12:20 Learning Café 1 - round 2.
  • 12:20 - 12:30 Summary of the Learning Café 1.
Session 2: Student modelling
  • 14:00 - 14:15 Personalising e-Learning Systems: Lessons learned from a vocational education case study (Tang & Yacef) [slides].
  • 14:15 - 14:30 Modeling Learner information within an Integrated Model on standard-based representations (Chacon et al.) [slides].
  • 14:30 - 14:55 Learning Café 2 - round 1.
  • 14:55 - 15:20 Learning Café 2 - round 2.
  • 15:20 - 15:30 Summary of the Learning Café 2.
Session 3: Behaviour analysis
  • 15:30 - 15:45 Patterns of Confusion: Using Mouse Logs to Predict User Emotional State (Pentel) [slides].
  • 15:45 - 16:00 Using Problem Statement Parameters and Ranking Solution Difficulty to Support Personalization (Silva et al.) [slides].
  • 16:30 - 16:55 Learning Café 3 - round 1.
  • 16:55 - 17:30 Learning Café 3 - round 2.
  • 17:20 - 17:30 Summary of the Learning Café 3.

Invited talk

Title: User models, big personal data, user control for life-wide lifelong learning

Abstract:
This talk will present a view of user models as independent user controlled data stores with multiple roles for personalised learning. The talk will illustrate this in terms a series of projects that are based on the Personis framework. This was designed from its foundations to enable users to control their own personal data. It provides a flexible representation for both personalisation and for open learner models (OLMs) that support and nurture self-regulated learning and can provide meta-cognitive scaffolding. The talk will show how this links to the ProGoSs system for modelling competencies and their development across subjects and years of a degree programme. The talk will also illustrate the ways this role of user models for lifelong and life-wide learning that makes use of a range of emerging technologies, from MOOCs to activity trackers, smart fabrics and new ways for people to engage with interactive tabletops and walls.

Keynote's Bio:
Judy Kay is Professor of Computer Science, with primary research and teaching in human computer interaction (HCI), ranging from creating new technology to broader studies to inform its design and learn about its use. She is a leader of the CHAI: Computer Human Adapted Interaction Research Group and the new large interdisciplinary Human Centred Technology Cluster. She is a member of multi-disciplinary research networks: PLANET - Physical Activity Network, leading its New technology Research Theme and the STL - Sciences and Technologies of Learning Network. For learning contexts, she has created software infrastructures to support personalised learning. This involves systematic approaches to defining and tracking learning competencies and creating interfaces that harness learners' digital footprints in useful forms for long term learning and self-monitoring. She has extensive publications, and has presented invited keynote addresses in peak venues for personalisation and advanced learning technology.