Training metacognition in the classroom: the influence of incentives and feedback on exam predictions
By Tyler Miller, Lisa Geraci. 2011
179 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Cognitive Neuroscience, Developmental and Educational Psychology
View Paper: https://www.semanticscholar.org/paper/62ee9c65ae1d5d702c034a951dab8a6409044c49
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Cognitive Neuroscience
In Developmental and Educational Psychology
- Gavin T. L. Brown
- Fei Chen
- Ernesto Panadero
- Heidi L. Andrade
- D. Dunning
- A. Efklides
- A. Jonsson
- Adar Ben-Eliyahu
Citations in the corpus
- How unaware are the unskilled? Empirical tests of the “signal extraction” counterexplanation for the Dunning–Kruger effect in self-evaluation of performance (2013, background): “A similar study has suggested that the Dunning–Kruger effect evaporates with experience, but that feedback and incentives are needed in combination to produce better estimates (Miller & Geraci, 2011).”
- How Does Metacognition Contribute to the Regulation of Learning? An Integrative Approach (2014, background): “Miller and Geraci (2011) found that even with feedback on the accuracy of their current performance students' predictions of their future learning were overconfident.”
- A Critical Review of Research on Student Self-Assessment (2019, result): “One experiment on summative selfassessment (Miller and Geraci, 2011), in contrast, resulted in no improvements in exam scores, while the other one did (Raaijmakers et al.”
- Accuracy in student self-assessment: directions and cautions for research (2015, background): “For example, Miller and Geraci (2011) examined the relation between the accuracy of 81 undergraduate students’ predictions of their performance on four exams and (1) extra-credit incentives and (2) explicit, concrete feedback.”