Concreteness Fading in Mathematics and Science Instruction: a Systematic Review
By Emily R. Fyfe, Nicole M. McNeil, Ji Yeon Son, Robert L. Goldstone. 2014
301 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Education, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/ffb3ab8423e537ca202757efc00f8e331b03f379
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Developmental and Educational Psychology
- Logan Fiorella
- Richard E. Mayer
- James L. McClelland
- Dharshan Kumaran
- Andrew Kyle Lampinen
- Felix Hill
- Jane X. Wang
- Neil C. Rabinowitz
In Education
- Richard E. Mayer
- Logan Fiorella
- James L. McClelland
- Dharshan Kumaran
- Elida V. Laski
- Roxana Moreno
- Guido Makransky
- Olusola O. Adesope
In Experimental and Cognitive Psychology
- Richard E. Mayer
- Logan Fiorella
- Dharshan Kumaran
- Adam Santoro
- Felix Hill
- James L. McClelland
- Jane X. Wang
- Andrew Kyle Lampinen
Citations in the corpus
- What Makes Mathematics Manipulatives Effective? Lessons From Cognitive Science and Montessori Education (2015, background): “Recent studies indicate that a systematic fading of concreteness can increase children’s ability to transfer knowledge acquired through manipulatives to novel, unfamiliar problems (Fyfe et al., 2014).”
- Eight Ways to Promote Generative Learning (2016, background): “In math instruction, one promising remedy is to use concreteness fading (Fyfe et al. 2014; McNeil and Fyfe 2012).”
- Language models show human-like content effects on reasoning (2022, background): “Likewise, language model performance on the Wason tasks increases most when they are demonstrated with realistic examples; benefits of concrete examples have been found in cognitive and educational contexts (Sweller et al., 1998; Fyfe et al., 2014), but remain to be explored in the Wason problems.”
- Tell me why! - Explanations support learning of relational and causal structure (2021, background): “Explanations can also vary in abstraction (cf. Fyfe et al., 2014).”
- Tell me why! Explanations support learning relational and causal structure (2021, background): “Explanations can also vary in abstraction (cf. Fyfe et al., 2014; Watkins et al., 2021).”