Repeated testing sessions and scholastic aptitude in college students’ metacognitive accuracy

Kelemen, William L.; Winningham, Robert G.; Weaver, Charles A.

doi:10.1080/09541440701326170

Cited by 44 publications

(49 citation statements)

References 38 publications

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“…The common result from both experiments was that students were overconfident, low-performing students even more so than high-performing students. As such, the current findings are consistent with the everexpanding literature showing that people are mostly overconfident in their self assessments (e.g., Dunning et al 2004;Kelemen et al 2007;Kruger & Dunning 1999). Experiment 1 showed that when students had the opportunity to earn extra credit for accurate predictions and were given feedback regarding their performance, they were not able to improve their metacognitive calibration.…”

Section: Discussionsupporting

confidence: 91%

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Training metacognition in the classroom: the influence of incentives and feedback on exam predictions

Miller

Geraci

2011

Metacognition Learning

151

132

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In two semester-long studies, we examined whether college students could improve their ability to accurately predict their own exam performance across multiple exams. We tested whether providing concrete feedback and incentives (i.e., extra credit) for accuracy would improve predictions by improving students' metacognition, or awareness of their own knowledge. Students' predictions were almost always higher than the grade they earned and this was particularly true for low-performing students. Experiment 1 demonstrated that providing incentives but minimal feedback failed to show improvement in students' metacognition or performance. However, Experiment 2 showed that when feedback was made more concrete, metacognition improved for low performing students although exam scores did not improve across exams, suggesting that feedback and incentives influenced metacognitive monitoring but not control.In an ideal world each one of us, when asked about the quality or efficiency with which we can accomplish goals, could provide a correct answer. As it is though, no one is immune to flawed self-assessment; doctors, nurses, business managers, and other trusted professionals routinely commit errors of self-assessment, which is one aspect of metacognition (Dunning et al. 2004). Metacognition refers to a person's "knowledge and cognition about cognitive phenomena" (Flavell 1979, p. 906). Three aspects of metacognition that have been researched extensively are metacognitive knowledge, metacognitive monitoring, and metacognitive control. In this paper, we focus on metacognitive monitoring, which is an individual's ability to assess the state of their cognitive activity, and metacognitive control, which is an individual's ability to regulate cognitive activity (Dunlosky & Metcalfe 2009). To illustrate these two aspects of metacognition, consider the following example: A student is studying for an anatomy exam and she asks herself how well she remembers the bones of the hand. When she answers this question about the current state of her learning, she has Metacognition Learning (2011) 6:303-314

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Section: Discussionsupporting

confidence: 91%

“…However, the findings are mixed. For example, in one lab study, repeated practice making performance predictions did improve calibration (Kelemen et al 2007). Participants were instructed to study different Swahili-English word pairs on five occasions and to indicate the likelihood that they would remember the English words.…”

mentioning

confidence: 99%

Training metacognition in the classroom: the influence of incentives and feedback on exam predictions

Miller

Geraci

2011

Metacognition Learning

151

132

View full text Add to dashboard Cite

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“…Moreover, the available evidence is often mixed. For instance, Kelemen, Winningham, and Weaver (2007) showed that the reliability of judgment accuracy was rather low. Thiede et al (2010) showed that for most participants, monitoring accuracy varied widely across different sets of texts; but, for a small subset of participants (approximately 5% of college students), who based their judgments on their ability to connect ideas in a text, accuracy was consistently high across the different sets of text.…”

Section: Reliability and Stabilitymentioning

confidence: 97%

Four cornerstones of calibration research: Why understanding students' judgments can improve their achievement

Dunlosky

Thiede

2013

Learning and Instruction

114

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“…These norms have also been used to examine metacognitive judgments of learning (Jang & Nelson, 2005;Keleman, Winningham, & Weaver, 2007;Keleman, Frost, & Weaver, 2000;Krueger & Sifuentes, 2014;Pyc & Rawson, 2012a;Pyc, Rawson, & Aschenbrenner, 2014;Scheck & Nelson, 2005), including how people make decisions about when to stop studying particular items (Karpicke, 2009;Kornell & Bjork, 2008;Pyc & Rawson, 2007, 2009a and how people choose to allocate their study time (Ariel, 2012;Dunlosky & Thiede, 1998;Krueger, 2012).…”

mentioning

confidence: 99%

Recall and response time norms for English–Swahili word pairs and facts about Kenya

Bangert

Heydarian

2016

Behav Res

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In the vast literature exploring learning, many studies have used paired-associate stimuli, despite the fact that real-world learning involves many different types of information. One of the most popular materials used in studies of learning has been a set of Swahili-English word pairs for which Nelson and Dunlosky (Memory 2; 325-335, 1994) published recall norms two decades ago. These norms involved use of the Swahili words as cues to facilitate recall of the English translation. It is unclear whether cueing in the opposite direction (from English to Swahili) would lead to symmetric recall performance. Bilingual research has suggested that translation in these two different directions involves asymmetric links that may differentially impact recall performance, depending on which language is used as the cue (Kroll & Stewart, Journal of Memory and Language 33; 1994). Moreover, the norms for these and many other learning stimuli have typically been gathered from college students. In the present study, we report recall accuracy and response time norms for Swahili words when they are cued by their English translations. We also report norms for a companion set of fact stimuli that may be used along with the SwahiliEnglish word pairs to assess learning on a broader scale across different stimulus materials. Data were collected using Amazon's Mechanical Turk to establish a sample that was diverse in both age and ethnicity. These different, but related, stimulus sets will be applicable to studies of learning, metacognition, and memory in diverse samples.

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Repeated testing sessions and scholastic aptitude in college students’ metacognitive accuracy

Cited by 44 publications

References 38 publications

Training metacognition in the classroom: the influence of incentives and feedback on exam predictions

Training metacognition in the classroom: the influence of incentives and feedback on exam predictions

Four cornerstones of calibration research: Why understanding students' judgments can improve their achievement

Recall and response time norms for English–Swahili word pairs and facts about Kenya

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