Designing Cognitive Complexity in Mathematical Problem-Solving Items

By R. Daniel, S. Embretson. 2010

52 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5601290b29ea596399fb196e99d0adee0467ca8b

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

1. Samuel Greiff
2. Gyöngyvér Molnár
3. S. Embretson
4. Beno Csapó

In Experimental and Cognitive Psychology

1. R. Daniel
2. Samuel Greiff
3. Gyöngyvér Molnár
4. S. Embretson
5. Beno Csapó

In Statistics and Probability

1. Samuel Greiff
2. R. Daniel
3. S. Embretson

Citations in the corpus

• Inductive reasoning, domain specific and complex problem solving: Relations and development (2013, background): “…either in connection with specific national school curricula (e.g. Mullis et al., 2009), or explicitly in a specific domain such as mathematical (Daniel & Embretson, 2010), technical (Baumert, Evans, & Geiser, 1999), or scientific (Dunbar & Fugelsang, 2005) problem solving or problem solving in…”
• Understanding and Quantifying Cognitive Complexity Level in Mathematical Problem Solving Items (2008, background): “That is, Embretson and Daniel (2008) found that controlled manipulations of several variables in the cognitive model impacted item difficulty.”