The Design Recommendations for Intelligent Tutoring Systems series has covered many different topics over the past ten years. Those topics have ranged from general components of intelligent tutoring systems (ITSs) (Learner Modeling, Instructional Management, Authoring Tools, Domain Modeling) to advanced elements (Assessment Methods, Team Tutoring, Self-Improving Systems, Data Visualization, Competency Based-Scenario Design). Our most recent previous volume included a series of Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analyses on all the initial topics as well as overviews of ITSs in general and the Generalized Intelligent Framework for Tutoring (GIFT) software (Sottilare et al., 2012; Sottilare et al., 2017; Goldberg & Sinatra, 2023). Each book in the Design Recommendations for Intelligent Tutoring Systems series has been associated with an Expert Workshop on the same topic. These workshops are part of a cooperative agreement (W911NF18-2-0039) between US Army Combat Capabilities Development Command (DEVCOM) Soldier Center and University of Memphis. One of the goals of the expert workshops is to learn more about ITS capabilities that are being developed, and how these approaches, as well as lessons learned, could enhance the GIFT software (GIFT is freely available at https://www.GIFTtutoring.org). Invited experts in industry, academia, and government discuss the expert workshop topic, their applicable work, and suggestions for improving GIFT in what is usually a two day event. Both the University of Memphis and GIFT Teams participate in the workshop, help to guide discussion, and ask questions that will provide insight into current challenges in GIFT. The expert workshop associated with this current book was held virtually in October 2022, and included presentations about both general approaches and specific applications to professional education in ITSs. Additionally, the University of Memphis team that participated in the workshop included Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Jody Cockroft. The US Army DEVCOM Soldier Center team who participated in the workshop included Benjamin Goldberg, Gregory Goodwin, Anne M. Sinatra, Randall Spain, and Lisa N. Townsend. The current volume and the expert workshop that was associated with it, branched out in a new direction and rather than addressing specific components of an ITS or types of features/approaches that could be included in ITSs, it focused on how to apply an ITS for specific types of training. The specific focus was on ITSs for Professional Career Education. This topic area was selected, as in general, ITS research tends to be focused on K-12 or college education, and in many cases on domains such as algebra or physics. However, for the military, and for industry, trainees are adult learners and domains tend to be more active, applied, and experiential. This workshop provided an opportunity for discussion of specific examples of applied training that occurs with ITSs, as well as discussion of general approaches and considerations for applied professional education in ITSs.

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 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.

Design Recommendations for Intelligent Tutoring Systems (ITSs) explores the impact of intelligent tutoring system design on education and training. Specifically, this volume examines “Authoring Tools and Expert Modeling Techniques”. 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.

Design Recommendations for Intelligent Tutoring Systems explores the impact of computer-based tutoring system design on education and training. Specifically, this volume, “Learner Modeling” examines the fundamentals of learner modeling and identifies best practices, emerging concepts and future needs to promote efficient and effective tutoring. Part of our design recommendations include current, projected, and needed capabilities within the Generalized Intelligent Framework for Tutoring (GIFT), an open source, modular, service-oriented architecture developed to promote simplified authoring, reuse, standardization, automated instruction and evaluation of tutoring technologies.

Design Recommendations for Intelligent Tutoring Systems explores the impact of intelligent tutoring system design on education and training. Specifically, this volume examines “Instructional Management” techniques, strategies and tactics, and identifies best practices, emerging concepts and future needs to promote efficient and effective adaptive tutoring solutions. Design recommendations include current, projected, and emerging capabilities within the Generalized Intelligent Framework for Tutoring (GIFT), an open source, modular, service-oriented architecture developed to promote simplified authoring, reuse, standardization, automated instructional management and analysis of tutoring technologies.

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

Incorporates several innovative and increasingly popular subject areas, including the gamification of education, assessment, and STEM subjects Combines research and authorship from both civilian and military worlds as well as interdisciplinary fields Rigorously defines and analyzes the criteria of selecting, designing, implementing, and evaluating emerging educational technologies while offering implications for future use

May the Forcing Functions be with You: The Stimulating World of AIED and ITS Research It is my pleasure to write the foreword for Advances in Intelligent Tutoring S- tems. This collection, with contributions from leading researchers in the field of artificial intelligence in education (AIED), constitutes an overview of the many challenging research problems that must be solved in order to build a truly intel- gent tutoring system (ITS). The book not only describes some of the approaches and techniques that have been explored to meet these challenges, but also some of the systems that have actually been built and deployed in this effort. As discussed in the Introduction (Chapter 1), the terms “AIED” and “ITS” are often used int- changeably, and there is a large overlap in the researchers devoted to exploring this common field. In this foreword, I will use the term “AIED” to refer to the - search area, and the term “ITS” to refer to the particular kind of system that AIED researchers build. It has often been said that AIED is “AI-complete” in that to produce a tutoring system as sophisticated and effective as a human tutor requires solving the entire gamut of artificial intelligence research (AI) problems.