|
Showing 1 - 2 of
2 matches in All Departments
While laboratory research is the backbone of collecting
experimental data in cognitive science, a rapidly increasing amount
of research is now capitalizing on large-scale and real-world
digital data. Each piece of data is a trace of human behavior and
offers us a potential clue to understanding basic cognitive
principles. However, we have to be able to put the pieces together
in a reasonable way, which necessitates both advances in our
theoretical models and development of new methodological
techniques. The primary goal of this volume is to present
cutting-edge examples of mining large-scale and naturalistic data
to discover important principles of cognition and evaluate theories
that would not be possible without such a scale. This book also has
a mission to stimulate cognitive scientists to consider new ways to
harness big data in order to enhance our understanding of
fundamental cognitive processes. Finally, this book aims to warn of
the potential pitfalls of using, or being over-reliant on, big data
and to show how big data can work alongside traditional, rigorously
gathered experimental data rather than simply supersede it. In sum,
this groundbreaking volume presents cognitive scientists and those
in related fields with an exciting, detailed, stimulating, and
realistic introduction to big data - and to show how it may greatly
advance our understanding of the principles of human memory,
perception, categorization, decision-making, language,
problem-solving, and representation.
While laboratory research is the backbone of collecting
experimental data in cognitive science, a rapidly increasing amount
of research is now capitalizing on large-scale and real-world
digital data. Each piece of data is a trace of human behavior and
offers us a potential clue to understanding basic cognitive
principles. However, we have to be able to put the pieces together
in a reasonable way, which necessitates both advances in our
theoretical models and development of new methodological
techniques. The primary goal of this volume is to present
cutting-edge examples of mining large-scale and naturalistic data
to discover important principles of cognition and evaluate theories
that would not be possible without such a scale. This book also has
a mission to stimulate cognitive scientists to consider new ways to
harness big data in order to enhance our understanding of
fundamental cognitive processes. Finally, this book aims to warn of
the potential pitfalls of using, or being over-reliant on, big data
and to show how big data can work alongside traditional, rigorously
gathered experimental data rather than simply supersede it. In sum,
this groundbreaking volume presents cognitive scientists and those
in related fields with an exciting, detailed, stimulating, and
realistic introduction to big data - and to show how it may greatly
advance our understanding of the principles of human memory,
perception, categorization, decision-making, language,
problem-solving, and representation.
|
|