iTextbooks 2022 : iTextbooks 2022 : Fourth Workshop on Intelligent Textbooks at AIED 2022

Workshop Description

Textbooks have evolved over the last several decades in many aspects. Most textbooks can be accessed online, many of them freely. They often come with libraries of supplementary educational resources or online educational services built on top of them. As a result of these enrichments, new research challenges and opportunities emerge that call for the application of AIED methods to enhance digital textbooks and learners’ interaction with them. Therefore, we ask: How to facilitate the access to textbooks and improve the reading process? What can be extracted from textbook content and data-mined from the logs of students interacting with it? This workshop seeks research contributions addressing these and other research questions related to the idea of intelligent textbooks. It aims at bringing together researchers working on different aspects of learning technologies to establish intelligent textbooks as a new, interdisciplinary research field.


Topics of Interest

The workshop themes include but are not limited to:
* Modeling and representation of textbooks: examining the prerequisite and semantic structure of textbooks to enhance their readability;
* Analysis and mining of textbook usage logs: analyzing the patterns of learners’ use of textbooks to obtain insights on learning and the pedagogical value of textbook content;
* Generation, manipulation, and presentation: exploring and testing different formats and forms of textbook content to find the most effective means of presenting different knowledge;
* Assessment and personalization: developing methods that can generate assessments and enhance textbooks with adaptive support to meet the needs of every learner using the textbook;
* Knowledge visualization: augmenting textbooks with concept maps, open learner models and other knowledge-rich extensions;
* Smart interactive content: extending online textbooks with various kinds of smart interactive Content to improve learning, engagement, learned modeling, and personalization;
* Intelligent information retrieval and question-answering for digital textbooks;
* Collaborative technologies: building and deploying social components of digital textbooks that enable learners to interact with not only content but other learners;
* Content curation and enrichment: sorting through external resources on the web and finding the relevant resources to augment the textbook and provide additional information for learners.


Important Dates

* Paper submission: May 16, 2022
* Notification of acceptance: TBA
* Final version of accepted papers: TBA


Submission Instructions

All papers must be original and not simultaneously submitted to another journal or conference.
Accepted papers will be presented orally and included in the workshop proceedings.
At this point we invite full (up to 12 pages) and short (up to 4 pages) paper submissions.
Submissions should follow the Springer format. See here for details.
Submission should be made in pdf format through the EasyChair system https://easychair.org/conferences/?conf=itextbooks2022.
Submissions will be reviewed by members of the workshop program committee.


Organization

The program will include a mixture of paper presentations and demonstrations of iTextbooks systems and services.
All accepted publications will appear in the workshop proceedings published as a CEUR-WS volume.
See the volumes of the two previous workshops here: 2019 | 2020 | 2021


Workshop Organizers

Sergey Sosnovsky, Utrecht University

Peter Brusilovsky, University of Pittsburgh

Andrew S. Lan, University of Massachutsetts Amherst



Program Committee

Debshila Mallick OpenStax, Rice University

Paulo Carvalho, Carnegie Mellon University

Vinay Chaudhri, SRI International

Paul Denny, The University of Auckland

Brendan Flanagan, Kyoto University

Reva Freedman, Northern Illinois University

Roger Nkambou, Université du Québec à Montréal

Andrew Olney, University of Memphis

Benjamin Paassen, German Research Center for Artificial Intelligence

Atsushi Shimada, Kyushu University

Khushboo Thaker, University of Pittsburgh

Ilaria Torre, University of Genoa