Cognitive and Linguistic Predictors of Mathematical Word Problems With and Without Irrelevant Information.
By Amber Y. Wang, Lynn S. Fuchs, Douglas Fuchs. 2016
57 citations recorded by the source corpus.
The purpose of this study was to identify cognitive and linguistic predictors of word problems with versus without irrelevant information. The sample was 701 2nd-grade students who received no specialized intervention on word problems. In the fall, they were assessed on initial arithmetic and word-problem skill as well as language ability, working memory capacity, and processing speed; in the spring, they were tested on a word-problem measure that included items with versus without irrelevant information. Significant predictors common to both forms of word problems were initial arithmetic and word problem-solving skill as well as language and working memory. Nonverbal reasoning predicted word problems with irrelevant information, but not word problems without irrelevant information. Findings are discussed in terms of implications for intervention and future research.
Subfields: Developmental and Educational Psychology, Education, Statistics and Probability, Natural Language Processing, Linguistics
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In Natural Language Processing
- Mateusz Malinowski
- Piotr Pikekos
- Henryk Michalewski
- Christopher Kanan
- Kushal Kafle
- Anton van den Hengel
- Devi Parikh
- Qi Wu
Citations in the corpus
- Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning. (2021, background): “Such the emphasize is often motivated by that solving them is among the best predictors of employability, and is considered as a distinct area of mathematical competence (Murnane et al., 2001; Wang et al., 2016).”