The True-False Test at Its Best: A (Not the) Treatise of Optimization with Competitive Construction
- Brabec, Jordan Andrew
- Advisor(s): Bjork, Elizabeth L.
Abstract
Few of us are unfamiliar with the basic nature of a true-false test. Whether within explicit assessments that we complete as part of our formal education or at the implicit core of the most banal of our daily decisions, we are frequently compelled to evaluate descriptive and prescriptive truth. The basic motivation of this dissertation, however, is that we do not yet fully understand the cognitive consequences of these true-false evaluations, much less how we might optimize them for practical purposes. While research of the past century has repeatedly revealed that tests of various formats can function as powerful learning events, the sparse, unsettled literature regarding the true-false test—in combination with the anecdotal sentiment that the true-false test is an instrument of dubious pedagogical value—might lead us to think that the true-false test is an exception to an otherwise generalizable, if underappreciated, rule. To evaluate the truth of the matter, and to explore how we, as learners, might begin to make the most of the moments in which we are true-false tested, this work presents a series of laboratory experiments across two chapters, each written as a discrete empirical article for (potential) publication. While the first chapter examines these memorial effects when true-false tests are administered after learners have studied the relevant information, the second chapter examines these memorial effects when true-false tests are administered before the relevant information is studied. Broadly, this work revealed that both true-false pretests and posttests can be more helpful than harmful, especially when constructed with competitive clauses (i.e., parenthetical clauses designed to contrast the primary referents of evaluation with highly confusable referents). Critically, these competitive clauses elicited comprehensive memorial benefits not just for explicitly tested information but also for related information, illustrating what could be a simple yet valuable method of optimization for the true-false test format in more practical contexts.