'Someday we expect that computers will be able to keep us informed about the news. People have imagined being able to ask their home computers questions such as "What's going on in the world?"...'. Originally published in 1984, this book is a fascinating look at the world of memory and computers before the internet became the mainstream phenomenon it is today. It looks at the early development of a computer system that could keep us informed in a way that we now take for granted. Presenting a theory of remembering, based on human information processing, it begins to address many of the hard problems implicated in the quest to make computers remember. The book had two purposes in presenting this theory of remembering. First, to be used in implementing intelligent computer systems, including fact retrieval systems and intelligent systems in general. Any intelligent program needs to use and store and use a great deal of knowledge. The strategies and structures in the book were designed to be used for that purpose. Second, the theory attempts to explain how people's memories work and makes predictions about the organization of human memory.

The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a rigorous and fast-emerging discipline that synthesizes the learning sciences, instructional design, engineering design, and other methodologies to support learners. As learning engineering becomes an increasingly formalized discipline and practice, new insights and tools are needed to help education, training, design, and data analytics professionals iteratively develop, test, and improve complex systems for engaging and effective learning. Written in a colloquial style and full of collaborative, actionable strategies, this book explores the essential foundations, approaches, and real-world challenges inherent to ensuring participatory, data-driven, learning experiences across populations and contexts.

The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a rigorous and fast-emerging discipline that synthesizes the learning sciences, instructional design, engineering design, and other methodologies to support learners. As learning engineering becomes an increasingly formalized discipline and practice, new insights and tools are needed to help education, training, design, and data analytics professionals iteratively develop, test, and improve complex systems for engaging and effective learning. Written in a colloquial style and full of collaborative, actionable strategies, this book explores the essential foundations, approaches, and real-world challenges inherent to ensuring participatory, data-driven, learning experiences across populations and contexts.

'Someday we expect that computers will be able to keep us informed about the news. People have imagined being able to ask their home computers questions such as "What's going on in the world?"...'. Originally published in 1984, this book is a fascinating look at the world of memory and computers before the internet became the mainstream phenomenon it is today. It looks at the early development of a computer system that could keep us informed in a way that we now take for granted. Presenting a theory of remembering, based on human information processing, it begins to address many of the hard problems implicated in the quest to make computers remember. The book had two purposes in presenting this theory of remembering. First, to be used in implementing intelligent computer systems, including fact retrieval systems and intelligent systems in general. Any intelligent program needs to use and store and use a great deal of knowledge. The strategies and structures in the book were designed to be used for that purpose. Second, the theory attempts to explain how people's memories work and makes predictions about the organization of human memory.