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.
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.
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 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.
Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education. Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.
Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system. - Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available - Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet - Features algorithmic material that enables programmers and researchers to design building components and intelligent systems
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.
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.
