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Machine Learning and Human Intelligence
Intelligence is at the heart of what makes us human, but the methods we use for identifying, talking about and valuing human intelligence are impoverished. We invest artificial intelligence (AI) with qualities it does not have and, in so doing, risk losing the capacity for education to pass on the emotional, collaborative, sensory and self-effective aspects of human intelligence that define us. To address this, Rosemary Luckin--leading expert in the application of AI in education - proposes a framework for understanding the complexity of human intelligence. She identifies the comparative limitation of AI when analyzed using the same framework, and offers clear-sighted recommendations for how educators can draw on what AI does best to nurture and expand our human capabilities.
AI for School Teachers
What is artificial intelligence? Can I realistically use it in my school? What’s best done by human intelligence vs. artificial intelligence, and how do I bring these strengths together? What would it look like for me, and my school, to be AI Ready? AI for School Teachers will help teachers and headteachers understand enough about AI to build a strategy for how it can be used in their school. Examining the needs of schools to ensure they are ready to leverage the power of AI and drawing examples from early years to high school students, this book outlines the educational implications and benefits that AI brings to school education in practical ways. It develops an understanding of what AI is and isn't and how we define and measure what we value and provides a framework which supports a step-by-step approach to developing an AI mindset, focusing on ways to improve educational opportunities for students with evidence-informed interventions.
Enhancing Learning and Teaching with Technology
The book brings together researchers, technologists and educators to explore and show how technology can be designed and used for learning and teaching to best effect.
Advances in Help-Seeking Research and Applications
Research on help seeking has primarily focused on classrooms interactions that consist primarily of students asking teachers and peers for help. The rapid emergence of information and communications technologies and interactive learning environments, however, requires expanding the help-seeking landscape and rethinking such critical theoretical issues as the distinction between help seeking and information search, and whether help seeking is inevitably a social self-regulated learning strategy. There is also the need to focus attention on help seeking in the broader learning enterprise, which includes its role in the collaboration process, how to support adaptive rather than the over- or und...
Artificial Intelligence in Education
This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Artificial Intelligence in Education
This book constitutes the refereed proceedings of the 18th International Conference on Artificial Intelligence in Education, AIED 2017, held in Wuhan, China, in June/July 2017. The 36 revised full papers presented together with 4 keynotes, 37 poster, presentations, 4 doctoral consortium papers, 5 industry papers, 4 workshop abstracts, and 2 tutorial abstracts were carefully reviewed and selected from 159 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Handbook of Design in Educational Technology
The Handbook of Design in Educational Technology provides up-to-date, comprehensive summaries and syntheses of recent research pertinent to the design of information and communication technologies to support learning. Readers can turn to this handbook for expert advice about each stage in the process of designing systems for use in educational settings; from theoretical foundations to the challenges of implementation, the process of evaluating the impact of the design and the manner in which it might be further developed and disseminated. The volume is organized into the following four sections: Theory, Design, Implementation, and Evaluation. The more than forty chapters reflect the international and interdisciplinary nature of the educational technology design research field.
Re-Designing Learning Contexts
What do we mean by the word ‘context’ in education and how does our context influence the way that we learn? What role can technology play in enhancing learning and what is the future of technology within learning? Re-Designing Learning Contexts seeks to re-dress the lack of attention that has traditionally been paid to a learner’s wider context and proposes a model to help educators and technologists develop more productive learning contexts. It defines context as the interactions between the learner and a set of inter-related resource elements that are not tied to a physical or virtual location. Context is something that belongs to an individual and that is created through their inte...
Artificial Intelligence in Education
This two-volume set LNCS 11625 and 11626 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Education, AIED 2019, held in Chicago, IL, USA, in June 2019. The 45 full papers presented together with 41 short, 10 doctoral consortium, 6 industry, and 10 workshop papers were carefully reviewed and selected from 177 submissions. AIED 2019 solicits empirical and theoretical papers particularly in the following lines of research and application: Intelligent and interactive technologies in an educational context; Modelling and representation; Models of teaching and learning; Learning contexts and informal learning; Evaluation; Innovative applications; Intelligent techniques to support disadvantaged schools and students, inequity and inequality in education.
