Generators Bots And Tutors Creative Approaches To Human Ai Synergy In Classroom Instruction
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Generators, Bots, and Tutors: Creative Approaches to Human-AI Synergy in Classroom Instruction
Emerging technologies are transforming education. By incorporating gamification into the curriculum, teachers are having an impact on the engagement of their students, leading to optimized learning experiences that still encourage human creativity. Additionally, with the use of virtual tutors, students have better access to educational resources that further their academic achievement. As a result, teachers are equipped to manage the individual learning needs and enhance the cognitive development of their students. Thus, it is important to refine these tools and products to achieve greater effectiveness in diverse educational settings. Generators, Bots, and Tutors: Creative Approaches to Human-AI Synergy in Classroom Instruction aims to significantly contribute to the ongoing discourse on the integration of technology in education by presenting cutting-edge research that addresses both the theoretical frameworks and practical applications of digital learning tools. It introduces new perspectives on the role of artificial intelligence (AI), immersive technologies, and gamification in education, and how these can be harnessed to optimize learning experiences. Covering topics such as non-player characters (NPCs), emotional connections, and classroom instructions, this book is an excellent resource for educators, instructional designers, educational administrators, policymakers, technology developers, educational technology entrepreneurs, professionals, researchers, scholars, academicians, and more.
Creative Applications of Artificial Intelligence in Education
This open access book explores the synergy between AI and education, highlighting its potential impact on pedagogical practices. It navigates the evolving landscape of AI-powered educational technologies and suggests practical ways to personalise instruction, nurture human-AI co-creativity, and transform the learning experience. Spanning from primary to higher education, this short and engaging volume proposes concrete examples of how educational stakeholders can be empowered in their AI literacy to foster creativity, inspire critical thinking, and promote problem-solving by embracing AI as a tool for expansive learning. Structured in three parts, the book starts developing the creative engagement perspective for learning and teaching to then present practical applications of AI in K-12 and higher education, covering different fields (teacher education, professional education, business education) as well as different types of AI supported tools (games, chatbots, and AI assisted assessment). It also delves into the ethical considerations, policy implications, and the central role educators play in harnessing the power of an AI informed educational experience.
Robot Learning from Human Teachers
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.