Evidence map›Paper›PMID 42052052›Full record

ArticleFrontiers in psychology2026

Beyond personality traits: a motivation-self-regulation model of mathematical problem-solving through self-efficacy and mathematical thinking.

Jie Wang, Lin Guo

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jie WangFaculty of Education, Languages, Psychology & Music, SEGi University Kota Damansara, Petaling Jaya, Malaysia.
Lin GuoFaculty of Education, Languages, Psychology & Music, SEGi University Kota Damansara, Petaling Jaya, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to understand how learning-related traits and process variables collectively influence high school students' mathematical problem-solving ability; and to verify the mediating roles of mathematical self-efficacy and mathematical thinking. Methods: Based on questionnaire and mathematical performance test data from 1,183 high school students in Shanghai, the study employs partial least squares structural equation modeling (PLS-SEM) for analysis. Results: The results show that the model has high explanatory power for mathematical self-efficacy, mathematical thinking, and mathematical problem-solving ability; motivation to math and self-regulated learning are core upstream predictors of problem-solving performance, while mathematical self-efficacy and mathematical thinking serve as the closest direct predictors of problem-solving and significantly mediate the effects of motivation and self-regulated learning on problem-solving ability. In contrast, personality traits exhibit relatively weak direct and mediating effects after controlling for prior academic performance and the aforementioned learning variables. Implications: The contribution of this study lies not only in integrating motivation, self-regulation, affective beliefs, and higher-order mathematical thinking into a unified structural framework, but also in clarifying the relative explanatory roles of distal personality traits and proximal learning processes, showing that mathematical problem-solving is shaped through both affective-belief and cognitive pathways, and demonstrating that the explanatory advantage within the present model lies primarily in domain-specific, modifiable learning processes rather than broad personality dispositions.

Indexed as

Big Five frameworkhigh schoollearning motivationmath educationmathematical thinking

Identifiers

PMID42052052
PMCPMC13111107

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.