Abductive reasoning
Last updated: Wednesday, 13 November 2024
Abductive reasoning is a form of logical inference that seeks to find the simplest, most likely explanation or hypothesis for an observed phenomenon or set of data, based on the available information. Contrasting with inductive (identifying new cases of existing theories) and deductive reasoning (testing existing theories with new observations), it aims to produce new hypotheses and theories based on surprising or anomalous empirical findings.
Big argument here is that abductive reasoning is congruent with everyday forms of sensemaking and reasoning, based on incomplete or partial evidence?
One key aspect of abductive reasoning is the role of surprise and disconcertment.1 When we encounter unexpected or anomalous observations, it prompts us to question our existing assumptions. This process of embracing and working with anomalies is crucial for theorising and knowledge creation.
Abductive reasoning seeks to generate new hypotheses and explanations based on empirical observations. This is an iterative process. New hypotheses are continuously refined and tested against additional observations and evidence. This iterative nature supports a dynamic, evolving understanding of the phenomenon under investigation.
[?] How much of this is about cultivating and working with anomalies? [!] Need to link with the role of the researcher’s community of inquiry?2
Tags: epistemics
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