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Using "Expectation Failures" to prompt "Failure Expectations"

Prof John Nychka | University of Alberta

Using "Expectation Failures" to prompt "Failure Expectations"

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Mental models (schemata) are some of the strongest builders of, and barriers to, our learning-our schemata shape and bias our ability to learn because they are "...knowledge structures that represent objects or events and provide default assumptions about their characteristics, relationships, and entailments under conditions of incomplete information." (DiMaggio, 1997; p.269). Because schemata are models of reality they are often incorrect in construction or in application to certain learning situations-our default thinking settings do not always work, and when they don’t a cognitive dissonance develops. To achieve deep learning, we can intellectually challenge our learners (Bain, 2004) by creating an "expectation failure" which is: "a situation in which existing mental models will lead to faulty expectations, causing [students] to realize the problems they face in believing whatever they believe." (Bain, 2004; p.28). "Expectation failures" motivate a learner to adjust their schema by memorably exposing a knowledge gap and stimulating meta-cognition. This presentation highlights case studies in which "expectation failures" were designed into a low-stakes materials failure analysis. Through Socratic questioning, learners came to realize their errors of impression, assumptions, hasty generalizations, unfounded conclusions, and misinterpretations. A post-inspection discussion prompted reflection and identification of the causes of the "expectation failures" and revealed the benefits of a shift to "failure expectation" mentality, wherein the learner embraces that their current schema might be flawed and a possible hindrance to a growth mentality. The shift to "failure expectation" can lower the risk of cognitive dissonance when encountering an "expectation failure", whilst also lowering the barrier for schemata adjustments. By embracing and expecting failure as a deep learning activity learners can be more comfortable in making mistakes, and become more flexible, and meta-cognitive, in adjusting their schemata.