In cognitive science, artificial intelligence, psychology, and education, a growingbody of research supports the view that the learning process is strongly influenced by the learner'sgoals. The fundamental tenet of goal-driven learning is that learning is largely an active andstrategic process in which the learner, human or machine, attempts to identify and satisfy itsinformation needs in the context of its tasks and goals, its prior knowledge, its capabilities, andenvironmental opportunities for learning. This book brings together a diversity of research ongoal-driven learning to establish a broad, interdisciplinary framework that describes thegoal-driven learning process. It collects and solidifies existing results on this important issue inmachine and human learning and presents a theoretical framework for future investigations.The bookopens with an an overview of goal-driven learning research and computational and cognitive models ofthe goal-driven learning process. This introduction is followed by a collection of fourteen recentresearch articles addressing fundamental issues of the field, including psychological and functionalarguments for modeling learning as a deliberative, planful process; experimental evaluation of thebenefits of utility-based analysis to guide decisions about what to learn; case studies ofcomputational models in which learning is driven by reasoning about learning goals; psychologicalevidence for human goal-driven learning; and the ramifications of goal-driven learning ineducational contexts.The second part of the book presents six position papers reflecting ongoingresearch and current issues in goal-driven learning. Issues discussed include methods for pursuingpsychological studies of goal-driven learning, frameworks for the design of active and multistrategylearning systems, and methods for selecting and balancing the goals that drive learning.A BradfordBook
In cognitive science, artificial intelligence, psychology and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities and environmental opportunities for learning. This book brings together a diversity of research on goal-driven learning to establish an interdisciplinary framework that describes the goal-driven learning process. It collects and solidifies existing results on this issue in machine and human learning and presents a theoretical framework for future investigations. The book opens with an overview of goal-driven learning research and computational and cognitive models of the process.
The introduction is followed by a collection of 14 recent research articles addressing fundamental issues in the field, including: psychological and functional arguments for modelling learning as a deliberative, panned process; experimental evaluation of the benefits of utility-based analysis to guide decisions about what to learn; case studies of computational models in which learning is driven by reasoning about learning goals; psychological evidence for human goal-driven learning; and the ramifications of goal-driven learning in educational contexts. The second part of the book presents six position papers reflecting ongoing research and current issues in goal-driven learning. Issues discussed include methods for pursuing psychological studies of goal-driven learning, frameworks for the design of active and multi-strategy learning systems and methods for selecting and balancing the goals that drive learning.
