PALE 2018:
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. In particular, the PALE session at AIED 2018 is specially focused on the enhanced sensitivity towards the management of educational data coming from multimodal learners' interactions and technological deployment, and how this wide range of situations and features can impact on modeling the learner interaction and context.

This workshop format aims to foster interactive presentations and constructive work. It combines quick 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.

June 30th, 2018

London, UK (co-located with AIED 2018)

For the session at AIED 2018, 3 Learning Cafés are set up, as scheduled below. Each one consists in brief presentations (no more than 5 minutes!) of the key questions posed and small group discussions with participants randomly grouped at tables (Learning Café discussions of 25 minutes).

Each table will be moderated by one expert in the topic under discussion (i.e., the presenter of the paper who has addressed the issue). In the middle of the Learning Café participants of one table will be asked to move to the other table, so ideas discussed in one groups are taken to the discussion held in the other group.

  • 14:30 - 14:40 PALE 2018 Introduction
  • 14:40 - 16:00 Session 1: 4 presentations, Learning Café 1 & 2
  • 16:00 - 16:15 Break
  • 16:15 - 16:55 Session 2: 2 presentations, Learning Café 3
  • 17:00 - 17:30 PALE 2018 Sharing outcomes of the Learning Cafés

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

Session 1: Multimodal input data
  • 14:40 - 14:45 Measuring Learner Tone and Sentiment at Scale Via Text Analysis of Forum Posts (M. Schubert, D. Durruty and D.Joyner).
  • 14:45 - 14:50 Personalized (meta)-cognitive scaffolding for enabling students to learn aspects of scientific written argumentation (N. Elouazizi).
  • 14:55 - 15:20 Learning Café 1.
  • 15:20 - 15:25 Detecting reading strategies during task-oriented reading: Building an automated classifier (G. Kachergis, J. Kielstra, L. Bokkers, B. Persad and I. Molenaar).
  • 15:25 - 15:30 Eye Gaze Feature Classification for Predicting Levels of Learning (S. Parikh and H. Kalva).
  • 15:35 - 16:00 Learning Café 2.
Session 2: Technological deployment
  • 16:15 - 16:20 An Analysis of Student Belief and Behavior in Learning by Explaining to a Digital Doppelganger (N. Wang, A. Shapiro, A. Feng, C. Zhuang, D. Schwartz and S. Goldberg).
  • 16:20 - 16:25 Effective Learning Recommendations powered by AI Engine (X. Dang and I. Ghergulescu).
  • 16:30 - 16:55 Learning Café 3.