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.

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.

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 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 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 includes a collection of expanded papers from the 2019 Sino-German Symposium on AI-supported educational technologies, which was held in Wuhan, China, March, 2019. The contributors are distinguished researchers from computer science and learning science. The contributions are organized in four sections: (1) Overviews and systematic perspectives , (2) Example Systems, (3) Algorithms, and (4) Insights gained from empirical studies. For example, different data mining and machine learning methods to quantify different profiles of a learner in different learning situations (including interaction patterns, cognitive modes, knowledge skills, interests and emotions etc.) as well as connections to measurements in psychology and learning sciences are discussed in the chapters.

The GIFT Users Symposia began in 2013 with the goal to capture successful implementations of GIFT from the user community and to share recommendations leading to more useful capabilities for authors, researchers, and learners of Adaptive Instructional Systems (AIS). The attached proceedings resulted from papers accepted for the 8th Annual GIFT Users Symposium held virtually (due to COVID-19) on 28-29 May 2020. It is a excellent collection of contributions covering all aspects of AIS implementation, with special attention towards future training and education concepts centered around collaboration and team dynamics.

Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the end user, being a student, a teacher, a manager or a persona in a different role, an instructional designer can design a way to produce a practical dashboard that helps him improve that very user’s performance, interaction, motivation or just grading. This book provides a thorough approach on how education, as such, from teaching to learning through management, is improved by a smart analysis of available data, making visible and useful behaviours, predictions and patterns that are hinder to the regular eye without the process of massive data.

These proceedings are intended to document the evolutions of GIFT as a tool for the authoring of intelligent tutoring systems (ITSs) and the evaluation of adaptive instructional tools and methods. Papers in this volume were selected with the following goals in mind: (1) The candidate papers describe tools and methods that raise the level of knowledge and/or capability in the ITS research and development community (2) The candidate papers describe research, features, or practical applications of GIFT (3) The candidate papers expand ITSs into previously untapped domains (4) The candidate papers build/expand models of automated instruction for individuals and/or teams

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.