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Data · dataset · 2026

Dataset for Chinese Mathematical Resilience Scale Validation

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Dataset for Chinese Mathematical Resilience Scale ValidationThis dataset originates from a quasi-experimental study investigating the effectiveness of a structured intervention module designed to cultivate mathematical resilience among Chinese university students.Mathematical resilience refers to learners‘ capacity to persevere, cope constructively, and overcome difficulties when encountering setbacks, frustration, or pressure in mathematical learning.

Previous research indicates that Chinese students exhibit notably low levels of mathematical resilience, largely attributed to high-stakes examination systems and prevalent mathematics anxiety—approximately 21.1% of fourth-graders and 35.0% of eighth-graders reported mathematics anxiety, while 69% of secondary school students demonstrated moderate-to-severe anxiety symptoms.Drawing upon Sidek’s resilience framework, the intervention comprised a 12-week structured program integrating resilience-building strategies into regular STEM coursework.

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A quasi-experimental pretest–posttest–follow-up design was employed to capture both immediate and sustained effects of the intervention.Ethical Statement: This study adhered to the American Psychological Association (APA) ethical guidelines for research with human participants. The research protocol was approved by the Ethics Committees of Universiti Malaysia Sarawak and Anhui Business and Technology College.

All participants provided written informed consent prior to data collection.The Chinese version of the Mathematical Resilience Scale (MRS) was used. This scale was adapted and validated among Chinese upper-primary students by Wei et al., demonstrating good model fit for its three-factor structure (χ²/df = 1.56, CFI = 0.96, TLI = 0.95, RMSEA = 0.04), with an overall Cronbach‘s α of 0.85 and a 4-week test-retest reliability of 0.68.

Subsequent studies have further confirmed its construct, discriminant, and convergent validity among Chinese young adult populations.

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ScienceDB10.57760/sciencedb.3583310 d agoJSON v1
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