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• W2399848439 abstract "Knowledge Monitoring Calibration: Sensitivity and Specificity as Unique Cognitive Constructs Francis X. Smith (francis-smith@uiowa.edu) Department of Psychology, E11 Seashore Hall, Iowa City, IA 52242 USA Christopher A. Was (cwas@kent.edu) Lifespan Development and Educational Sciences, 405 White Hall Kent, OH 44242, USA Abstract Knowledge monitoring is an important metacognitive process which can help students improve study habits and thereby increase academic performance. Which is more useful in predicting test performance: knowing what you know, or knowing what you do not know? Two distinct constructs of knowledge monitoring calibration, sensitivity and specificity, were used along with the more traditional Gamma to predict performance on tests in an undergraduate educational psychology course. It was found that sensitivity, a measure of correctly identifying known items, was the most useful in predicting overall test scores as well as final exam scores. Specificity, on the other hand, had no significant impact on exam performance. Results suggest that sensitivity and specificity may be more meaningful measures of knowledge monitoring calibration when it comes to predicting academic achievement, as well as being better adapted for missing values in any one cell of the data. Keywords: calibration knowledge monitoring, metacognition, Introduction In the course of preparing for an examination a student must make several judgments of their knowledge. The student must decide if studying outside of lecture time is necessary to achieve the level of success desired. If studying seems appropriate the student needs to decide which materials to study and for how long. All of these decisions are based on a student's judgment of how much of the material they truly know, and will be able to recall during the exam, and how well they know it. It is, therefore, crucial that a student be able to make accurate judgments of their knowledge in order to appropriately and efficiently allocate study time and other methods of preparation. The ability to identify what information is known and what is unknown is referred to as knowledge monitoring accuracy. It is logically reasonable to claim that for any higher-order self-regulation of learning to be effective, accurate knowledge monitoring is essential. In fact, models of self-regulated learning often include definitions such as “the setting of one’s own goals in relation to learning and ensuring that the goals set are attained” (Efklides, 2011). While it may be possible to set goals without knowledge monitoring, it would certainly be difficult to assess attainment of those goals prior to the actual evaluation without some kind of monitoring process. A number of theories hold a similar position, arguing that effective monitoring leads to better regulation during learning (Metcalfe, 2009; Nelson & Narens, 1990). Indeed, recent evidence has supported this theoretical relationship. Nietfeld, Cao, and Osborne (2006) for example demonstrated that active practice with self-assessment throughout a semester resulted in improvements to both overall calibration (accuracy of performance predictions) as well as performance relative to another group not given the self-assessment tasks. In another recent study, it was found that effective knowledge monitoring predicted academic achievement even when the materials used to test knowledge monitoring abilities were unrelated to the material on the exams (Hartwig, Was, Isaacson, & Dunlosky, 2012). There is also some evidence that it may be possible to teach students to better monitor their knowledge (e.g., Isaacson & Was, 2010). It seems uncontroversial to point out that these processes of monitoring one's own knowledge are only effective and beneficial if they are accurate. Research into calibration of knowledge monitoring has largely involved the use of knowledge monitoring assessments (KMA) similar to that developed by Tobias and Everson (2002). One adaptation of the format for the KMA used in prior research by Isaacson and Was (2010) is to present a series of words for the subject to identify as either known or unknown. At this point no other response is given. Importantly, the subject is not told how to process the words they are simply instructed to state if they know the meaning of the word or not. After responding to the entire list of words, subjects are then given a test to see if they can identify the meanings of each of the words out of a list of possible choices. Effective knowledge monitoring techniques should allow an individual to successfully identify which items they know the meanings of and which items are not known. It is worth noting that, for the purposes of the KMA, the amount of items responded to correctly is not directly relevant. Rather than relying on the proportion of correct responses the results of the KMA are typically interpreted based on the proportion of items correctly identified as known or unknown. For example, if an item is identified as unknown during the initial phase and is responded to incorrectly" @default.
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• W2399848439 title "Knowledge Monitoring Calibration: Sensitivity and Specificity as Unique Cognitive Constructs" @default.
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