A Meta-Analytic Reliability Generalization Study of the Computational Thinking Scale

Kiyici, Gülbin; Kahraman, Nurcan

doi:10.15354/sief.22.ma011

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…In this issue, topics such as reliability generalization study of the computational thinking scale (Kiyici & Kahraman, 2022), scientific reasoning skills of pre-service science teachers (Sahin & Sasmaz Oren, 2022), challenges of future education (Hua, 2022), mobile game addiction among schoolchildren (Feng, 2022), reading behavior of primary and secondary school students (Zhou, 2022) are discussed. Looking to the coming New Year, the journal will, as always, adhere to its focus on promoting the development of education, resolving educational problems, and driving educational innovation.…”

Section: Longjun Zhoumentioning

confidence: 99%

Confronting Educational Challenges and Reshaping Future Education

Zhou

2022

Sci Insights Educ Front

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Education is more complicated and difficult than many other human activities because it involves the complexity and diversity of mankind. For centuries, numerous educational practitioners and researchers have devoted themselves to the exploration of educational practice and theories and have achieved remarkable accomplishments. However, humans are still plagued by a multitude of educational complications.

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Section: Longjun Zhoumentioning

confidence: 99%

Confronting Educational Challenges and Reshaping Future Education

Zhou

2022

Sci Insights Educ Front

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Evaluation of reliability generalization of Conner-Davison Resilience Scale (CD-RISC-10 and CD-RISC-25): A Meta-analysis

Wojujutari,

Idemudia,

Ugwu

2024

PLoS ONE

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Background Resilience, a critical multi-faceted construct in psychological research, is often measured using Conner-Davison Resilience Scale (CD-RISC-10 and CD-RISC-25). This reliability generalization (RG) meta-analysis delves into evaluate the level of reliability generalization estimate of both CD-RISC-10 and CD-RISC-25 in assessing resilience across diverse populations and settings. Methods A reliability generalization meta-analysis on the psychometric properties of CD-RISC-10 and CD-RISC-25 was conducted, encompassing 27 studies. The original versions’ psychometric properties were systematically retrieved from databases including PubMed, PsycINFO, Google Scholar, Web of Science, Science Direct, and Scopus, with a focus on studies published between 2018 and 2023. The study protocol, including the specific methods for the reliability generalization meta-analysis, was pre-registered in the Prospero database (registration number CRD42023479052). This pre-registration ensures transparency and minimizes the risk of bias in the study design and analysis. Results The analysis revealed a combined estimated overall estimate of Cronbach’s Alpha of 0.89 (95% CI [0.87, 0.91], z = 77.20, p < 0.05), indicating a high level of reliability for CD-RISC-10 and CD-RISC-25. CD-RISC-10 exhibited an overall estimate of Cronbach’s Alpha of 0.8732 (95% CI [0.85, 0.10], z = 69.81, p < 0.05), indicating a high level of reliability, while CD-RISC-25 also demonstrated an overall estimate of Cronbach’s Alpha of 0.8922 (95% CI [0.87, 0.91], z = 77.20, p < 0.001), indicating a high level of reliability. Furthermore, CD-RISC-10 displayed commendable reliability (ωα+ = 0.86), slightly lower compared to the impressive reliability of CD-RISC-25 (ωα+ = 0.89), with a significant difference (t = 0.1159, p > 0.001). The mixed-effects model revealed a non-significant moderating effect of the CD-RISC language version on reliability estimates (coefficient = -0.0017, p <0.05). Conclusion The results affirm the high overall reliability of both CD-RISC-10 and CD-RISC-25, with CD-RISC-25 exhibiting a slightly superior level. The non-significant moderating effect of language version suggests that the psychometric properties of these scales remain robust across different linguistic adaptations. These findings enhance our understanding of the CD-RISC scales, providing practitioners, researchers, and clinicians valuable insights for informed scale selection in diverse contexts. The commendable reliability of both scales underscores their utility in assessing and promoting resilience across varied populations and settings. Future research should explore specific contexts, demographics, and applications, enhancing their utility for diverse populations and settings.

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A Meta-Analytic Reliability Generalization Study of the Computational Thinking Scale

Cited by 2 publications

References 25 publications

Confronting Educational Challenges and Reshaping Future Education

Confronting Educational Challenges and Reshaping Future Education

Evaluation of reliability generalization of Conner-Davison Resilience Scale (CD-RISC-10 and CD-RISC-25): A Meta-analysis

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