GIFT, the Generalized Intelligent Framework for Tutoring, is a modular, service-oriented architecture developed to lower the skills and time needed to author effective adaptive instruction. Design goals for GIFT also include capturing best instructional practices, promoting standardization and reuse for adaptive instructional content and methods, and methods for evaluating the effectiveness of tutoring technologies. Truly adaptive systems make intelligent (optimal) decisions about tailoring instruction in real-time and make these decisions based on information about the learner and conditions in the instructional environment. The GIFT Users Symposia were started in 2013 to capture successful implementations of GIFT from the user community and to share recommendations leading to more useful capabilities for GIFT authors, researchers, and learners.

Welcome to the Proceedings of the 11th Annual GIFT User Symposium! This year we are celebrating 11 years of GIFT Symposiums and have accepted 15 papers for publication. All of the presentations that occurred at GIFTSym11, and the papers in this volume show the versatility of the Generalized Intelligent Framework for Tutoring (GIFT), and the work that is being done with GIFT. GIFT is an open-source intelligent tutoring system (ITS) architecture that is freely available online at GIFTtutoring.org. There are both Cloud and Downloadable version of GIFT. GIFT has been developed with multiple goals in mind including supporting ITS research, and simplified creation of ITSs and Adaptive Instructional Systems (AISs). Our fantastic team, and our program committee did a great job supporting the development of GIFTSym11, reviewing papers, and assisting with the facilitation of the event this year. We want to recognize them for their efforts: • Benjamin Goldberg • Gregory Goodwin • Michele Myers • Alexandra Lutz • Randall Spain • Lisa N. Townsend We were very pleased to have GIFTSym11 return to being an in-person event this year! Additionally, this was our first year offering a hybrid option for attendees. We are very happy that both modalities were well attended!

Welcome to the Proceedings of the 12th Annual GIFT User Symposium! This year we are celebrating 12 years of GIFT Symposiums and have accepted 12 papers for publication. All of the presentations and the papers in this volume show the versatility of the Generalized Intelligent Framework for Tutoring (GIFT), and the work that is being done with GIFT. GIFT is an open-source intelligent tutoring system (ITS) architecture that is freely available online at GIFTtutoring.org. There are both Cloud and Downloadable version of GIFT. GIFT has been developed with multiple goals in mind including supporting ITS research, and simplified creation of ITSs and Adaptive Instructional Systems (AISs). Our fantastic team, and our program committee did a great job supporting the development of GIFTSym12, reviewing papers, and assisting with the facilitation of the event this year. We want to recognize them for their efforts: • Benjamin Goldberg • Gregory Goodwin • Anne Sinatra • Michele Myers • Alexandra Lutz • Randall Spain • Lisa N. Townsend We were very pleased to have GIFTSym11 return to being an in-person event this year! Additionally, this was our first year offering a hybrid option for attendees. We are very happy that both modalities were well attended!

The Generalized Intelligent Framework for Tutoring (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 GIFT authors, researchers, and learners. The attached proceedings resulted from papers accepted for the 4th Annual GIFT Users Symposium.

This is the fifth year we have been able to capture the research and development efforts related to the Generalized Intelligent Framework for Tutoring (GIFT) community which at the writing of these proceedings has well over 1000 users in over 65 countries. We are proud of what we have been able to accomplish with the help of our user community. 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.

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.

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 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 constitutes late breaking papers from the 22nd International Conference on Human-Computer Interaction, HCII 2020, which was held in July 2020. The conference was planned to take place in Copenhagen, Denmark, but had to change to a virtual conference mode due to the COVID-19 pandemic. From a total of 6326 submissions, a total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings before the conference took place. In addition, a total of 333 papers and 144 posters are included in the volumes of the proceedings published after the conference as “Late Breaking Work” (papers and posters). These contributions address the latest research and development efforts in the field and highlight the human aspects of design and use of computing systems.

This book constitutes the refereed proceedings of the 19th International Conference on Augmented Intelligence and Intelligent Tutoring Systems, ITS 2023, held in Corfu, Greece, during June 2-5, 2023. The 41 full papers and 19 short papers presented in this book were carefully reviewed and selected from 84 submissions. The papers are divided into the following topical sections: augmented intelligence in tutoring systems; augmented intelligence in healthcare informatics; augmented intelligence in games, serious games and virtual reality; neural networks and data mining; augmented intelligence and metaverse; security, privacy and ethics in augmented intelligence; and applied natural language processing.