Experts from a range of disciplines explore how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. Humans are not limited to a fixed set of innate or preprogrammed tasks. We learn quickly through language and other forms of natural interaction, and we improve our performance and teach others what we have learned. Understanding the mechanisms that underlie the acquisition of new tasks through natural interaction is an ongoing challenge. Advances in artificial intelligence, cognitive science, and robotics are leading us to future systems with human-like capabilities. A huge gap exists, however, between the highly specialized niche capabilities of current machine learning systems and the generality, flexibility, and in situ robustness of human instruction and learning. Drawing on expertise from multiple disciplines, this Strüngmann Forum Report explores how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. The contributors consider functional knowledge requirements, the ontology of interactive task learning, and the representation of task knowledge at multiple levels of abstraction. They explore natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex, dynamic environments. They discuss research challenges and opportunities, including ethical considerations, and make proposals to further understanding of interactive task learning and create new capabilities in assistive robotics, healthcare, education, training, and gaming. Contributors Tony Belpaeme, Katrien Beuls, Maya Cakmak, Joyce Y. Chai, Franklin Chang, Ropafadzo Denga, Marc Destefano, Mark d'Inverno, Kenneth D. Forbus, Simon Garrod, Kevin A. Gluck, Wayne D. Gray, James Kirk, Kenneth R. Koedinger, Parisa Kordjamshidi, John E. Laird, Christian Lebiere, Stephen C. Levinson, Elena Lieven, John K. Lindstedt, Aaron Mininger, Tom Mitchell, Shiwali Mohan, Ana Paiva, Katerina Pastra, Peter Pirolli, Roussell Rahman, Charles Rich, Katharina J. Rohlfing, Paul S. Rosenbloom, Nele Russwinkel, Dario D. Salvucci, Matthew-Donald D. Sangster, Matthias Scheutz, Julie A. Shah, Candace L. Sidner, Catherine Sibert, Michael Spranger, Luc Steels, Suzanne Stevenson, Terrence C. Stewart, Arthur Still, Andrea Stocco, Niels Taatgen, Andrea L. Thomaz, J. Gregory Trafton, Han L. J. van der Maas, Paul Van Eecke, Kurt VanLehn, Anna-Lisa Vollmer, Janet Wiles, Robert E. Wray III, Matthew Yee-King

Experts from a range of disciplines explore how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. Humans are not limited to a fixed set of innate or preprogrammed tasks. We learn quickly through language and other forms of natural interaction, and we improve our performance and teach others what we have learned. Understanding the mechanisms that underlie the acquisition of new tasks through natural interaction is an ongoing challenge. Advances in artificial intelligence, cognitive science, and robotics are leading us to future systems with human-like capabilities. A huge gap exists, however, between the highly specialized niche capabilities of current machine learning systems and the generality, flexibility, and in situ robustness of human instruction and learning. Drawing on expertise from multiple disciplines, this Strüngmann Forum Report explores how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. The contributors consider functional knowledge requirements, the ontology of interactive task learning, and the representation of task knowledge at multiple levels of abstraction. They explore natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex, dynamic environments. They discuss research challenges and opportunities, including ethical considerations, and make proposals to further understanding of interactive task learning and create new capabilities in assistive robotics, healthcare, education, training, and gaming. Contributors Tony Belpaeme, Katrien Beuls, Maya Cakmak, Joyce Y. Chai, Franklin Chang, Ropafadzo Denga, Marc Destefano, Mark d'Inverno, Kenneth D. Forbus, Simon Garrod, Kevin A. Gluck, Wayne D. Gray, James Kirk, Kenneth R. Koedinger, Parisa Kordjamshidi, John E. Laird, Christian Lebiere, Stephen C. Levinson, Elena Lieven, John K. Lindstedt, Aaron Mininger, Tom Mitchell, Shiwali Mohan, Ana Paiva, Katerina Pastra, Peter Pirolli, Roussell Rahman, Charles Rich, Katharina J. Rohlfing, Paul S. Rosenbloom, Nele Russwinkel, Dario D. Salvucci, Matthew-Donald D. Sangster, Matthias Scheutz, Julie A. Shah, Candace L. Sidner, Catherine Sibert, Michael Spranger, Luc Steels, Suzanne Stevenson, Terrence C. Stewart, Arthur Still, Andrea Stocco, Niels Taatgen, Andrea L. Thomaz, J. Gregory Trafton, Han L. J. van der Maas, Paul Van Eecke, Kurt VanLehn, Anna-Lisa Vollmer, Janet Wiles, Robert E. Wray III, Matthew Yee-King

With clear guides and specific examples, this book makes methodology accessible to those working within L2 interaction and task research.

This module on interactive tasks provides teachers with an overview of the nature of communication and explores the ways in which interactive tasks can promote communicative exchanges among students and teachers. The module provides guidelines for developing tasks, along with examples and options for their use in various types of language courses, including beginning level language classes, as well as more advanced language courses focusing culture, linguistics, literature, and film. Please visit the series companion website for more information: http://routledgetextbooks.com/textbooks/9781315679594/

Be a more effective teacher by using this simple, yet transformative, technique for teaching essential academic and social skills, routines, and behaviors. Through Interactive Modeling, your students actively observe, model, and practice skills that can lead to higher, lasting achievements and kinder classrooms. You'll save time; they'll gain mastery!, You can use Interactive Modeling to help your students achieve success in: math, reading, writing, social studies, science, working in groups, making smooth transitions, using supplies carefully, test-taking, and more! Book jacket.

3D technology is not new; research on 3D started back in early 1960s. But unlike in previous times, 3D technology has now rapidly entered our daily life from cinema to office to home. Using 3D for education is a new yet challenging task. This book will present several innovative efforts using 3D for immersive and interactive learning covering a wide spectrum of education including gifted program, normal (technical) stream, and special needs education. The book will also share experience on curriculum-based 3D learning in classroom setting and co-curriculum-based 3D student research projects. The book is organized as follows. Chapter 1 introduces the fundamentals of 3D educational technology and their applications in immersive and interactive learning. Chapter 2 discusses the use of virtual reality in teaching and learning of Molecular Biology. Chapter 3 presents the daVinci Lab @ River Valley High School. Chapter 4 describes the 3D education development process. Chapter 5 studies the adaption 3D system for learning gains in lower secondary normal (technical) stream. Chapter 6 investigates the effects of virtual reality technology on spatial visualization skills. Chapter 7 showcases a sabbatical program for students to use 3D for Science, Technology, Engineering and Mathematics (STEM) learning. Chapter 8 shares the use of 3D virtual pink dolphin to assist special education. The foreword of this book is written by Dr Cheah Horn Mun, Director, Education Technology Division, Ministry of Education, Singapore.

Shift Students’ Roles from Passive Observers to Active Participants. Preparing students for a world that did not exist when they were students themselves can be challenging for many teachers. Engaging students, particularly disinterested ones, in the learning process is no easy task, especially when easy access to information is at an all-time high. How then do educators simultaneously ensure knowledge acquisition and engagement? Ron Nash encourages teachers to embrace an interactive classroom by rethinking their role as information givers. The Interactive Classroom provides a framework for how to influence the learning process and increase student participation by sharing • Proven strategies for improving presentation and facilitation skills • Kinesthetic, interpersonal, and classroom management methods • Brain-based teaching strategies that promote active learning • Project-based learning and formative assessment techniques that promote a robust learning environment Intended to cultivate an interactive classroom in which students take an active role in learning, this book provides a blueprint for educators seeking to amplify student engagement while imparting critical twenty-first century skills.