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Concept Science: Content and Structure of Labeled Patterns in Human Experience
Abstract
This chapter describe the evolution of Concept Science that gave rise to Concept Parsing Algorithms (CPA). Concept Science developed ways to clarify conceptual content encoded in unstructured text that communicate context-specific knowledge in a sublanguage within a discipline. It was developed and tested since the early 1990s at the University of Toronto and Ryerson University in Toronto (Shafrir and Etkind, 2010). Concept Science lead to Pedagogy for Conceptual Thinking with Meaning Equivalence Reusable Learning Objects (MERLO) that offer a powerful tool for engaging and motivating students, and enhancing learning outcomes. This chapter describe some of Concept Science-based tools that provide new ways to discover, encode, and manage knowledge in large digital libraries of unstructured text in educational, governmental, NGO, and business organizations.
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