Whilst Deductive and Inductive inferences focus on movements, between specific and general ideas in learning, standard accounts of deduction and induction tend to draw examples from the formally published parts of what researchers’ actually learn. In particular, academic journal papers, funders’ reports, etc. tend to present highly sanitised versions, of the day to day learning from researchers’ professional lives and work. Treated as descriptive accounts of research-reality, such published accounts usually miss the various hunches, clues, metaphors, possible patterns, and informal explanations interacting with research practices.

As inquisitive learners, people like to try to explain things that surprise us. Abductive learning recognises that we do this through spontaneously generating explanatory ideas which come to hand, as we try to informally explain the surprising data or evidence. This in essence seeks to turn the challenge (of the surprise!) to our currently held beliefs, into a more plausible thing – when the surprising data or evidence is viewed as a concrete example of one or more of the explanatory ideas we spontaneously generate. In relation to Deduction/Hypothetico-deductive inference, new ideas are not so much developed based on those already accepted as certain (Deductive) or most likely (hypothetico-deductive) by a knowledge community. Instead the focus of reasoning is on developing abstract ideas (and sharing accounts of them) so as to minimise surprise for the learner.

We all spontaneously generate ideas to explain what we encounter, as we live. These are ‘informal’, in the sense that the ideas we explain by are not necessary already part of current published research literature. Some qualitative research experts link such Abductive inferences to the idea of qualitative research being the systematic empirical inquiry towards meaning (e.g. for both the researcher + researched). In another words, evolving our systems of thoughts and evidence in such a way as to make the new evidence (e.g. from primary data collection) meaningful – within the evolved (i.e. ‘more educated’ 🙂 system of thought. There are of course limits in practice however, in the extent to which the ideal of making all new evidence meaningful within the same system of thought, actually happens during 1 research project. In helping us to make sense of each others’ everyday social and human experiences, an academic qualitative research interest is to help readers discover and come to terms with the alternative or multiple meanings for any significant life event.

Gilbert Harman’s characterization of abduction as “reasoning to the best explanation.” is a common experience of qualitative researchers who try to explain their data. Professor Robert Miller in his 2003 A-Z of Social Research (https://uk.sagepub.com/en-gb/eur/the-a-z-of-social-research/book211452), characterises this ongoing process of reasoning to the best explanation by analogy from the Darwinian idea of survival of the fittest, based on a foundation of reality being a singular thing accessible equally to all. The population in his case is not so much a biological one, but referring to the ‘population’ of one or more explanatory ideas spontaneously generated, as we learn about some data/evidence. As more interviews are done for example, some of a research team’s earlier explanatory ideas might be dismissed as ‘less fit’, in light of the current pool of qualitative research data (and therefore not followed up as a study progresses).

In summary, Abductive inferences try to build explanatory patterns that turn a set of data or evidence, into one of least surprise/highest predictability to the knower. Abductive accounts of reasoning largely forego the historical issue of how particular explanatory schemas have come about, instead focusing on the utility of explanations in making our future predictable.

As scientist go about their professional lives, abductive inferences (in the sense of hunches, clues, etc.) only become visible as one zooms down from a high level view, into the experiences recorded in specific project or personal journals, lab books, and so on. The messy world of near misses, inspirational moments, and the confusions set aside, are an all too often unpublicized part of the research world. Yet these are human experiences we all share. Due to the experiential and conceptual worlds typically accessed through qualitative research data, the world of abductive reasoning is all too familiar to the qualitative research experience. The human project of evolving our thinking towards a more consistently meaningful and therefore predictable world within our systems of thought (abduction), can progress without necessarily focusing on whether we are moving from smaller to bigger ideas (induction), or wider to narrower ideas (deduction).