Preface

    Sergey Sosnovsky1, Peter Brusilovsky2, Rakesh Agrawal3, Richard G. Baraniuk4,
                                   Andrew S. Lan5
          1
            Utrecht University, Princetonplein 5, Utrecht 3584 CC, the Netherlands
                                  s.a.sosnovsky@uu.nl
      2
        University of Pittsburgh, 135 North Bellefield Ave., Pittsburgh, PA. 15260, USA
                                     peterb@pitt.edu
          3
            Data Insights Laboratories, P.O. Box 41231, San Jose, CA 95160, USA
                               rakesha.prof@gmail.com
                4
                  Rice University, 6100 Main Street, Houston, TX 77005, USA
                                      richb@rice.edu
   5
     University of Massachutsetts Amherst, 140 Governors Dr., Amherst, MA 01003, USA
                               andrewlan@cs.umass.edu

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 new technologies to enhance digital textbooks and learners’
interaction with them. Therefore, we ask: How to facilitate access to textbooks and
improve the reading process? What can be extracted from textbook content and mined
from the logs of students interacting with it? This workshop aimed to bring together
researchers working on different kinds of intelligent learning technologies related to
digital textbook. By starting a dialog between researchers who address the problems
and challenges of intelligent textbooks from different perspectives, we hoped to
establish intelligent textbooks as a new, interdisciplinary research field.
    Our vision of intelligent textbooks as a research field includes the following topics
of interests listed in the workshop’s call for papers:
• Modeling and representation of textbooks: examining the prerequisite and the
  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;
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• Smart interactive content: extending online textbooks with various kinds of smart
  interactive content to improve learning, engagement, learner 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.
While we did not receive submissions addressing all of these topics, the number of
submitted papers was sufficiently large and the diversity of topics was more than
sufficient to represent the emerging field as a whole. After a thorough reviewing, where
each submission was reviewed by three to five members of the reviewing committee,
which included workshop organizers and PC members, we selected six papers for long
presentation and eight other papers and position statements for the short presentation.
    In the workshop program, we loosely coupled the long presentation into two
sessions, one focused on studies and analysis of already developed textbooks and one
focused on technologies for developing novel textbooks. This separation, however, was
more for organization purposes and should not be considered as an attempt to classify
the variety of submitted papers. Not only we have papers that discuss both the
development and evaluation of intelligent textbook, but also many papers that go well
beyond this simple dichotomy. We were specifically happy to see several interesting
vision statements from well-established research groups on what an intelligent textbook
of the future should include. To avoid biasing the readers, we decided not to classify
the papers in the proceedings by fine-grained topics, but simply include them in the
order or their presentation at the workshop. We believe that this organization will be
most convenient for the attendees. We believe, however, that these workshop
proceedings will be of interest to a broader community of researchers. The collection
of papers featured in the proceedings along with the papers mentioned and cited offer
a good representation of the state of the art of this emerging field. We hope, that our
workshop will help to promote interest in intelligent textbooks and encourage follow-
up work.
    We want to thank the program committee members that helped us in preparation of
this workshop:
• Christopher Brinton, Purdue University
• VinayChaudhri, SRI International
• Barbara Ericson, University of Michigan
• Brendan Flanagan, Kyoto University
• Kobi Gal, Ben Gurion University
• Elena Glassman, Harvard University
• Phillip Grimaldi, OpenStax
• Noboru Matsuda, North Carolina State University
• RogerNkambou, Université du Québec À Montréal
• Xavier Ochoa, New York University
• Hiroaki Ogata, Kyoto University
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• Cliff Shaffer, Virginia Tech
• Atsushi Shimada, Kyushu University
• Erin Walker, Arizona State University
• Andrew Waters, OpenStax