Explanation and Prior Knowledge Running Head: Explanation and Prior Knowledge Explanation and Prior Knowledge Interact to Guide Learning Explanation and Prior Knowledge Interact to Guide Learning

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Citations in the corpus

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “(Andriessen, 2002; Bjork et al., 2013; Doumas and Hummel, 2005; Falkenhainer, 1990; Facione and Gittens, 2015; Lombrozo, 2016; Rehder, 2003; Selfridge, Daniell, and Simmons, 1985; Williams, Lombrozo, and Rehder, 2012; Williams and Lombrozo, 2013; Feltovich, Coulson, and Spiro, 2001).”
Inference to the Best Explanation (IBE) Versus Explaining for the Best Inference (EBI) (2015, background): “…these criteria in turn constrain learning and inference, in part by leading people to discover and generalize the ‘‘best’’ explanation (for evidence, see Bonawitz and Lombrozo 2012; Legare and Lombrozo 2014; Lombrozo 2007; Walker et al. 2014; Williams and Lombrozo 2010, 2013; Williams et al. 2013).”
What Do We Want From Explainable Artificial Intelligence (XAI)? - A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research (2021, background): “For instance, explanatory information including technical details might increase an expert developer’s degree of understanding while technical details can hamper understanding for novice developers or other (non-expert) stakeholders [175].”
Contrastive Constraints Guide Explanation-Based Category Learning (2017, methodology): “Thus, in addition to the presence of a contrast category, the establishment of the contrast class can be influenced by prior knowledge (e.g., Williams & Lombrozo, 2013; Wisniewski & Medin, 1994) and goals (e.g., Love, 2005) of the learner.”