Abstract
Belief Revision was conceived to model how humans do think, and has found application in machine learning. This paper argues that Peirce’s theory of inquiry conceives how we must think, if we want to keep improving our knowledge. Distinguishing between these two views, psychological (empirical) and pragmatic (normative), is crucial to our improvement of human learning methodology, especially as we develop interactive engagement methods for learning STEM concepts. Examining efforts to model Belief Revision in AI can reveal the limitations of this conceptualization for human learning, due to its misconception of Peirce’s pragmatic theory of inquiry.
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Keeler, M., Priss, U. (2013). Toward a Peircean Theory of Human Learning: Revealing the Misconception of Belief Revision . In: Pfeiffer, H.D., Ignatov, D.I., Poelmans, J., Gadiraju, N. (eds) Conceptual Structures for STEM Research and Education. ICCS 2013. Lecture Notes in Computer Science(), vol 7735. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35786-2_14
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