eISSN 2097-6054 ISSN 1672-9234 CN 11-5289/R
Responsible Institution:China Association for Science and Technology
Publishing:Chinese Nursing Journals Publishing House Co.,Ltd.
Sponsor:Chinese Nursing Association
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China Academic Journals Full-text Database
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Chinese Journal of Nursing Education ›› 2026, Vol. 23 ›› Issue (11): 1312-1317.doi: 10.3761/j.issn.1672-9234.2026.11.005

• AI-empowered Nursing Education • Previous Articles     Next Articles

Construction and usability evaluation of knowledge graph of the Nursing Research course

HUANG Xinghe1(), ZOU Haiou1, WU Liping1, CAO Jing2, LI Xiaoxue1, GUO Aimin1,*()   

  1. 1 School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China
    2 Department of Nursing, Peking Union Medical College Hospital,Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
  • Received:2026-03-17 Online:2026-11-15 Published:2026-11-04
  • Contact: *GUO Aimin,E-mail:guoaimin@hotmail.com
  • Supported by:
    Undergraduate Education and Teaching Reform Project of Peking Union Medical College(2023zlgl06)

Abstract:

Objective To construct a knowledge graph for the Nursing Research course,evaluate its usability,and assess students’ learning experiences. Methods Guided by constructivist learning theory,multiple knowledge sources,including textbooks and relevant literature in nursing research,were integrated. A knowledge graph specific to the Nursing Research course was designed and constructed. Usability was assessed by convenience sampling of 47 undergraduate nursing students. Additionally,10 students were sampled for semi-structured interviews to understand their learning experiences. Results The knowledge graph comprises 8 knowledge modules,encompassing 165 knowledge points,and is linked to 1 173 test questions and 112 learning resources. The total usability scale score for the knowledge graph platform was(66.81±14.42) points. Across the dimensions of satisfaction,learning attitude,learning ability,and support for learning resources,over 90% of respondents selected “agree” or “strongly agree” for most items. Interviews analysis identified major themes in students’ feedback:strong recognition for structured knowledge and logical visualization,improved learning efficiency,willingness to continue use,and an overall positive attitude. Conclusion The constructed knowledge graph exhibits strong usability. It helps nursing students master nursing research knowledge and facilitates autonomous learning.

Key words: Knowledge Graph, Nursing Research, Courses, Teaching Reform, Digital Intelligence