Metacomprehension A Brief History and How to Improve Its Accuracy

By John Dunlosky, Amanda R. Lipko. 2007

370 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/68f5cbea0e28799bf7c05d34f02483bac26ea3f7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Tamara van Gog
2. Jennifer Wiley
3. Richard E. Mayer
4. J. V. van Merriënboer
5. John Dunlosky
6. Anique B. H. de Bruin
7. Logan Fiorella
8. Robert A. Bjork

In Developmental and Educational Psychology

1. Tamara van Gog
2. J. V. van Merriënboer
3. Richard E. Mayer
4. Anique B. H. de Bruin
5. Jennifer Wiley
6. Logan Fiorella
7. Fred Paas
8. John Dunlosky

Citations in the corpus

• Enhancing students’ self-regulation and mathematics performance: the influence of feedback and self-evaluative standards (2010, background): “However, most empirical studies of performance calibration reveal that the vast majority of students lack skills to estimate their performance accurately: Findings suggest that many students are overconfident about their capability to perform on a certain task ( Dunlosky and Lipko 2007; Pajares and”
• Problem‐based Learning: Influence on Students' Learning in an Electrical Engineering Course (2011, background): “Research from psychology has suggested that students’ judgments of learning are not accurate predictors of their actual learning outcomes (Dunlosky & Lipko, 2007; Glenberg, Wilkinson, & Epstein, 1982).”
• Interleaving Helps Students Distinguish among Similar Concepts (2012, background): “These kinds of poor metacognitive judgments have been demonstrated many times (e.g., Dunlosky and Lipko 2007; McCabe 2011; Metcalfe 2000).”
• The assessment cycle: a model for learning through peer assessment (2016, background): “Individuals generally do a poor job of assessing their own understanding (Dunlosky and Lipko 2007), systematically overestimating their abilities (Dunning, Heath, and Suls 2004); even with limited information, peers are often able to assess the skills and characteristics of others better than of…”
• Activation of inaccurate prior knowledge affects primary-school students' metacognitive judgments and calibration (2013, background): “When judging the quality of recall of partially correct responses, learners often expect to receive full credit (Dunlosky & Lipko, 2007; Dunlosky et al., 2005).”
• Self-regulated learning: beliefs, techniques, and illusions. (2013, background): “F or p er so na l u se o nl y. EASE-OF-LEARNING JUDGMENTS JUDGMENTS OF LEARNING FEELING-OF-KNOWING JUDGMENTS SOURCE-MONITORING JUDGMENTS CONFIDENCE IN RETRIEVED ANSWERS ACQUISITION RETENTION RETRIEVAL SELECTION OF KIND OF PROCESSING”
• Do illustrations help or harm metacomprehension accuracy (2014, methodology): “Because relative accuracy is less affected by nonmetacognitive factors, it is this measure that has been most commonly used in studies of metacomprehension accuracy while learning from text following the tradition established in seminal work by Glenberg and Maki (Dunlosky & Lipko, 2007; Glenberg & E”
• Eight Ways to Promote Generative Learning (2016, background): “Research on metacognition and learning suggests that students are generally poor judges of their own learning (Dunlosky and Lipko 2007; Lin and Zabrucky 1998).”
• Concept mapping improves metacomprehension accuracy among 7th graders (2012, background): “Dunlosky and Lipko (2007) reviewed the metacomprehension literature and found themean accuracy across all the reviewed studies was no better.”
• Using strategy instruction and confidence judgments to improve metacognitive monitoring (2009, background): “In general individuals have been found to be inaccurate when making such judgments and the trend is toward being overconfident (see Markman 1985 and Dunlosky and Lipko 2007 for reviews).”
• Rethinking the Use of Tests: A Meta-Analysis of Practice Testing (2017, background): “As Dunlosky and Lipko’s (2007) review of their own extensive research programs showed, most students are remarkably poor at judging whether or not they have studied a piece of material well enough to have mastered it.”
• Poor Metacomprehension Accuracy as a Result of Inappropriate Cue Use (2010, background): “It is highly problematic, then, that the usual level of metacomprehension accuracy is generally quite dismal, with correlations between predicted test performance and actual performance hovering around 0.27 (Dunlosky & Lipko, 2007; Maki, 1998b).”