Design Recommendations for Intelligent Tutoring Systems (ITSs) explores the impact of intelligent tutoring system design on education and training. Specifically, this volume examines “Domain Modeling”. The “Design Recommendations book series examines tools and methods to reduce the time and skill required to develop Intelligent Tutoring Systems with the goal of improving the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is a modular, service-oriented architecture developed to capture simplified authoring techniques, promote reuse and standardization of ITSs along with automated instructional techniques and effectiveness evaluation capabilities for adaptive tutoring tools and methods.

This book is the fifth in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tutoring, machine learning, and potential standards) in intelligent tutoring system (ITS) design through the lens of the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg & Holden, 2012; Sottilare, Brawner, Sinatra, & Johnston, 2017). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes. Along with this volume, the first four books in this series, Learner Modeling (ISBN 978-0-9893923-0-3), Instructional Management (ISBN 978-0-9893923-2-7), Authoring Tools (ISBN 978-0-9893923-6-5) and Domain Modeling (978-0-9893923-9-6) are freely available at www.GIFTtutoring.org and on Google Play.

This book is a resource for those who are new to intelligent tutoring systems (ITSs), as well as those with a great deal of experience with them. This is the tenth book in our Design Recommendations for Intelligent Tutoring Systems book series. The focus of this book is on Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analyses of varying components of ITSs. Each chapter in the book represents a different topic area, and includes a SWOT analysis that is specific to that topic and how it relates to ITSs. This book can be read in order, or a reader can choose a specific topic area and move directly to that chapter. Each SWOT Analysis describes the current state of the topic area, and how the lessons learned from the analysis could be applied to the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare et al., 2012; Sottilare et al., 2017). GIFT is an ITS architecture that is open-source, modular, and domain independent (Sottilare et al., 2017). Each book in the design recommendations series has addressed a different ITS topic area, and how the work in each chapter can relate to and inform the GIFT architecture. GIFT has continually been in development, with features consistently being added to improve functionality, as well as reduce the skill requirement for authoring content in GIFT. GIFT is freely available in both downloadable and Cloud versions at https://www.GIFTtutoring.org.

This book on team tutoring is the sixth in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tu-toring, machine learning for self-improving systems, potential standards, and learning effect evaluation methods) in intelligent tutoring system (ITS) design. This book focuses on team tutoring. The discussion chapters in this book examine topics through the lens of the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg & Holden, 2012; Sottilare, Brawner, Sinatra, & Johnston, 2017). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, distribute ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes. Along with this volume, the first five books in this series, Learner Modeling (ISBN 978-0-9893923-0-3), Instructional Management (ISBN 978-0-9893923-2-7), Authoring Tools (ISBN 978-0-9893923-6-5), Domain Modeling (978-0-9893923-9-6) and Assessment Methods (ISBN 978-0-9977257-2-8) are freely avail-able at www.GIFTtutoring.org and on Google Play.

This book focuses on the topic of competency-based scenario design as it relates to Intelligent Tutoring Systems (ITSs). The current book is the ninth in a series of books that examine key topics in ITSs. The chapters in this book specifically relate the work presented to applications for the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg, & Holden, 2012; Sottilare, Brawner, Sinatra, & Johnston, 2017). GIFT is an open-source, domain independent, service-oriented, modular architecture for ITSs. GIFT has specifically been designed to allow for reusability of the GIFT architecture, GIFT tools, and instructional content materials. Further, GIFT has been designed with the goals of reducing the amount of time necessary to author ITSs, and reducing the skill level required for the authoring process. GIFT can be used to create ITSs that can be distributed both locally on a computer and virtually in the Cloud. In addition to creating ITSs, GIFT can be used to examine instructional outcomes, and conduct research. The topic of this book, Competency-Based Scenario Design is highly relevant to the development of ITSs. Scenarios are information-rich task/problem contexts that are closely aligned with real-world situations that professionals face in their jobs. The tasks/problems exhibit ecological validity rather than stripped-down abstract simplifications. Developers of ITSs and other adaptive instructional systems need to have principled guidance on how to design these scenarios. An example scenario may be a close match to a particular situation in the past, but not be representative of a large range of situations that professionals experience in their job. An example scenario may be very realistic, but not provide reliable and valid assessments of the learners' performance to guide assessments (summative, formative, or stealth). Research teams that build high quality scenarios need to include expertise in the targeted profession, assessment, learning science, and computer science. The current book brings together experts on ITSs to discuss their work as it applies to Competency-Based Scenario Design. We believe that this book can be used as a resource for those who have an interest in developing Scenarios for ITSs, and who want to learn more about how to do so.

This volume constitutes the refereed proceedings of the Second International Conference on Adaptive Instructional Systems, AIS 2020, which was due to be held in July 2020 as part of HCI International 2020 in Copenhagen, Denmark. The conference was held virtually due to the COVID-19 pandemic. A total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings from a total of 6326 submissions. The 41 papers presented in this volume were organized in topical sections as follows: designing and developing adaptive instructional systems; learner modelling and methods of adaptation; evaluating the effectiveness of adaptive instructional systems. Chapter "Exploring Video Engagement in an Intelligent Tutoring System" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. Chapters “An Ambient and Pervasive Personalized Learning Ecosystem: “Smart Learning” in the Age of the Internet of Things“ and “Exploring Video Engagement in an Intelligent Tutoring System" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022. The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was „AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI."

Gathering insightful and stimulating contributions from leading global experts in Artificial Intelligence in Education (AIED), this comprehensive Handbook traces the development of AIED from its early foundations in the 1970s to the present day.

This book on data visualization is the eighth in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, team tutoring, self-improving systems, data visualization, and competency based scenario design) in intelligent tutoring system (ITS) design. This book focuses on data visualization and how it is applied in ITSs. The chapters within this book specifically examine topics in relationship to the Generalized Intelligent Framework for Tutoring (GIFT) (Sottilare, Brawner, Goldberg & Holden, 2012; Sottilare, Brawner, Sinatra, & Johnston, 2017). GIFT is an open-source, domain-independent, modular, service-oriented architecture for ITSs. The design of GIFT allows for reusability, reduction in authoring time, and reducing the skill level needed to create an ITS. GIFT provides functionality to create ITSs, distribute ITSs to learners through the Cloud, conduct research to evaluate ITSs, and to examine instructional outcomes. Data visualization is an important topic for ITSs, as there are many different users of the systems (including learners, instructors, researchers, subject matter experts). The data that is collected by the ITS can be organized and displayed in a number of different ways. The current book includes a general discussion of how data visualizations can be applied in ITSs, as well as detailed specific examples of existing implementations, and technical details related to incorporating data visualization in ITSs. We believe this book can be used as a design tool for data visualization interfaces in ITSs.

This book on self-improving systems is the seventh in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tutoring, self-improving systems, data visualization) in intelligent tutoring system (ITS) design. This book focuses on self-improving systems. The discussion chapters in this book examine topics through the lens of the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, distribute ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes.