Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Constructivist Learning Theory-Based Teaching Methods in Chinese Nursing Education: Protocol for a Systematic Review and Meta-analysis.

Created on 06 Jul 2026

Authors

Jun Yang, Jiejie Ge, Mengyuan Li, Chuanying Zhang, Sijing Peng

Published in

JMIR research protocols. Jul 06, 2026. Epub Jul 06, 2026.

Abstract

The cognitive paradigm in medical education is undergoing a transition from traditional knowledge transmission to learner-centered knowledge construction. In China, this shift is aligned with the Outline of the Plan for the Construction of China into an Education Powerhouse (2024-2035), which mandates high-quality, intrinsic development in nursing curricula. While Constructivist Learning Theory (CLT)-based teaching methods (eg, PBL, CBL, and situational simulation) have been widely explored across Chinese nursing institutions, the evidentiary base remains geographically fragmented and methodologically heterogeneous. A systematic synthesis is required to inform national evidence-based educational reforms.
This protocol describes a systematic review and meta-analysis designed to evaluate the effectiveness of constructivist learning theory (CLT)-based teaching methods versus traditional lecture-based models on Chinese nursing students' theoretical knowledge, practical skills, self-directed learning ability, and critical thinking disposition.
A comprehensive systematic search will be conducted across nine electronic databases: PubMed, Web of Science, the Cochrane Library, Embase, CINAHL, China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Database (Chinese Scientific and Technological Journal Database), and China Biology Medicine (CBM). The search period spans from database inception to September 27, 2025, with a planned update through June 11, 2026 before final synthesis. Randomized controlled trials and quasi-experimental studies involving Chinese nursing students will be included. Two independent reviewers will screen records, perform full-text assessment, extract data using standardized forms, and code composite CLT interventions, digital or technology-enhanced components, and cluster- or class-based designs using prespecified decision rules. Risk of bias will be assessed using the Cochrane Risk of Bias tool 2 (RoB 2) for randomized trials and the Joanna Briggs Institute (JBI) critical appraisal tools for quasi-experimental studies. Meta-analysis will be performed using Review Manager (RevMan) 5.4 and Stata 18.0, employing random-effects models and prespecified subgroup and sensitivity analyses.
This protocol was finalized in February 2026. A preliminary systematic search conducted on September 27, 2025 identified 990 records before deduplication. As of February 6, 2026, deduplication had been completed and title/abstract screening had been initiated. Data extraction, risk-of-bias assessment, and statistical synthesis had not yet started at the protocol stage and will be conducted only after completion of the updated search, final study selection, and full-text eligibility assessment. The final search update was scheduled through June 11, 2026 before data synthesis. The results manuscript will be submitted after completion of all prespecified review steps, with the timeline depending on the number and complexity of newly identified studies.
This review will provide a robust evidentiary foundation for the strategic deployment of constructivist methodologies in Chinese nursing education, specifically addressing the needs of vocational and undergraduate programs in the era of digital transformation.
https://www.crd.york.ac.uk/PROSPERO/view/CRD420251159499.

PMID:
42405558
Bibliographic data and abstract were imported from PubMed on 06 Jul 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 4
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement