Fifth Workshop on Intelligent Textbooks (iTextbooks)

The 24th International Conference on Artificial Intelligence in Education (AIED’2023)


Date: July 3, 2023 / Place: Tokio, Japan


This full-day workshop was organized at AIED 2023.

The date of the workshop was July 3, 2023.

AIED 2023 was held in Tokio, Japan during July 3-7, 2022.

See here:

The webpages of the previous workshops of this series: 2019 | 2020 | 2021 | 2022

Call for Papers and Demos

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;
  • Collaborative technologies: building and deploying social components of digital textbooks that enable learners to interact with not only content but other learners;
  • 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;
  • 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 12, 2023 May 19, 2023

Notification of acceptance: Jun 02, 2023 Jun 09, 2023

Final version of accepted papers: June 23, 2023

Submission Instructions


Workshop Organizers

Sergey Sosnovsky, Utrecht University

Peter Brusilovsky, University of Pittsburgh

Andrew S. Lan, University of Massachutsetts Amherst

Program Committee

Isaac Alpizar Chacon (Utrecht University & Instituto Tecnológico de Costa Rica)

Debshila Basu Mallick (OpenStax, Rice University)

Peter Brusilovsky (University of Pittsburgh)

Paulo Carvalho (Carnegie Mellon University)

Vinay Chaudhri

Brendan Flanagan (Kyoto University)

Reva Freedman (Northern Illinois University)

Benny Johnson (VitalSource Technologies)

Andrew Lan (University of Massachusetts Amherst)

Noboru Matsuda (North Carolina State University)

Roger Nkambou (Université du Québec à Montréal)

Andrew Olney (University of Memphis)

Philip Pavlik (University of Memphis)

Cliff Shaffer (Virginia Tech)

Sergey Sosnovsky (Utrecht University)

Khushboo Thaker (University of Pittsburgh)

Ilaria Torre (University of Genoa)


09:00 - 09:30 Intro

09:30 - 10:30 Session 1 (Textbook usage analysis)

  • Analyzing Student Session Data in an eTextbook [paper] [slides]. Samnyeong Heo, Mohammed Farghally, Mostafa Mohammed, Clifford Shaffer
  • Advancing Intelligent Textbooks with Automatically Generated Practice: A Large-Scale Analysis of Student Data [paper] [slides]. Rachel Van Campenhout, Michelle Clark, Bill Jerome, Jeffrey S. Dittel, and Benny G. Johnson

  • 10:30 - 11:00 Coffee break

    11:00 - 12:30 Session 2 (Invited talk + crowdsourcing)

  • Invited talk: eBook + LA => BookRoll. Hiroaki Ogata [Abstract+Bio]
  • Exploring the Content Ecosystem of the First Open-source Adaptive Tutor and its Applications on Intelligent Textbooks [paper] [slides]. Ioannis Anastasopoulos

  • 12:30 - 13:20 Lunch break

    13:20 - 14:50 Session 3 (Textbook content analysis)

  • Layout and Activity-based Textbook Modeling for Automatic PDF Textbook Extraction [paper] [slides]. Élise Lincker, Olivier Pons, Camille Guinaudeau, Isabelle Barbet, Jérôme Dupire, Céline Hudelot, Vincent Mousseau, Caroline Huron
  • Eliminating Hallucinations: GPT-based Explanatory AI for Intelligent Textbooks and Documentation [paper] [slides]. Francesco Sovrano, Kevin Ashley, Alberto Bacchelli
  • Harnessing Textbooks for High-Quality Labeled Data: An Approach to Automatic Keyword Extraction [paper] [slides]. Lorenzo Pozzi, Isaac Alpizar-Chacon, Sergey Sosnovsky

  • 14:50 - 15:20 Coffee break

    15:20 - 16:40 Session 4 (Demos)

  • Digitalizing educational workbooks and collecting handwritten answers for automatic scoring [paper]. Tomo Asakura, Hung Nguyen, Truong Nghia, Nam Ly, Cuong Nguyen, Hiroshi Miyazawa, Yoichi Tsuchida, Takahiro Yamamoto, Masamitsu Ito, Toshihiko Horie, Ikuko Shimizu, Masaki Nakagawa
  • Converting Physical Textbooks into Interactive and Immersive ‘Phygital’ Textbooks: A Proposed System Architecture Design for Textbook Companion Apps [paper]. Devanshu Saindane, Sunny Prakash Prajapati, Syaamantak Das
  • Curio: An On-Demand Help-Seeking System on iTextbooks for Accelerating Research on Educational Recommendation Algorithms [paper]. Ying-Jui Tseng, Yu-Hsin Lin, Gautam Yadav, Norman Bier, Vincent Aleven

  • 16:40 Discussion