还原论
认识论
认知科学
计算机科学
发散思维
数据科学
管理科学
心理学
神经科学
工程类
认知
哲学
作者
Glory Emmanuel Aviña,Christian D. Schunn,Austin R. Silva,Travis Bauer,G. W. Crabtree,Curtis M. Johnson,Toluwalogo Odumosu,S. T. Picraux,R. Keith Sawyer,Richard Schneider,Rickson Sun,Gregory J. Feist,V. Narayanamurti,Jeffrey Y. Tsao
标识
DOI:10.1007/978-3-319-91134-2_14
摘要
Applying science to the current art of producing engineering and research knowledge has proven difficult, in large part because of its seeming complexity. We posit that the microscopic processes underlying research are not so complex, but instead are iterative and interacting cycles of divergent (generation of ideas) and convergent (testing and selecting of ideas) thinking processes. This reductionist framework coherently organizes a wide range of previously disparate microscopic mechanisms which inhibit these processes. We give examples of such inhibitory mechanisms and discuss how deeper scientific understanding of these mechanisms might lead to dis-inhibitory interventions for individuals, networks and institutional levels.
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