Elementary students’ cognitive and affective responses to impasses during mathematics problem solving.
Bibliographic record
Abstract
We propose a model delineating the role of control, value, and cognitive disequilibrium in elementary students’ experience of emotions during mathematics problem solving. We tested this model across 2 studies. In Study 1, using an explanatory mixed-methods design, 136 students from Grades 3 to 6 worked on a complex mathematics problem appropriate for their grade level. A think-aloud protocol was used to capture cognitive processes, and trend analyses were applied to students’ transcriptions to assess convergence or divergence of the quantitative results and to provide a richer account of students’ experiences. Results revealed that cognitive disequilibrium mediated relations between control and emotions but not value. In addition, curiosity and frustration predicted enactment and metacognitive strategies, which directly predicted mathematics problem-solving achievement. Trend analyses revealed that confusion following a failed attempt at impasse resolution led to frustration for 33% of the instances of a failed attempt. Interestingly, 35% of those instances resulted in students seeking help, and 32% resulted in students trying again or moving on. Additionally, trend analyses provided evidence that curiosity following surprise was a function of high resolution expectancy, whereas confusion following surprise was because of low resolution expectancy or high complexity. In Study 2, a new sample of 80 Grade 5 students completed a multiday complex mathematics problem and self-reported their emotions and cognitive appraisals of control and value (pretest and posttest). Results revealed reciprocal relations between control and curiosity and control and frustration. No reciprocal effects were found for value. Theoretical and practical implications are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".