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Cognitive Productivity: Can Cognitive Science Improve How Knowledge Workers Use IT to Learn from Source Material?

Authors/Contributors
Abstract
Society depends on knowledge workers (KWs) to identify, characterize and propose solutions to the many significant challenges it faces. KWs contend with ever changing information technology (IT) and bemoan "information overload." They commonly consult literature (e.g., Allen, 2001) and use productivity software that, regrettably, fail to leverage key findings in cognitive science. Can cognitive science help KWs process information and learn with technology? Yes, provided we directly address their problems. We present the Cognitive Productivity Research Project (Beaudoin, 2014) which is: characterizing information processing (IP) challenges KWs face (e.g., cognitive illusions, missing concepts and learning strategies); exploring gaps in cognitive science, including under-explored concepts (e.g., meta-effectiveness, monitors) and phenomena (e.g., KWs' self-regulated learning when using IT tools to draw on source material); marshaling an IP architecture and principles to address these issues; and proposing practical IP strategies for KWs that emphasize meta-documentation and productive practice.
Document
Description
This describes a research project based on Beaudoin, L. P. Cognitive Productivity: Using Knowledge to Become Profoundly Effective. https://leanpub.com/cognitiveproductivity/
Published as
Beaudoin, L. P., Gauthier, Geneviève & Winne, P. H. (2015, July). Cognitive productivity: Can cognitive science improve how knowledge workers' use IT to learn from source material? Poster presented at the 37th Annual Conference of the Cognitive Science Society. Pasadena, California USA.
Publication title
37th Annual Conference of the Cognitive Science Society
Document title
Cognitive productivity: Can cognitive science improve how knowledge workers' use IT to learn from source material?
Date
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You are free to copy, distribute and transmit this work under the following conditions: You must give attribution to the work (but not in any way that suggests that the author endorses you or your use of the work); You may not use this work for commercial purposes.
Scholarly level
Peer reviewed?
No
Language
English
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