AI-assisted concept mapping enhances orthopaedic nursing students’ critical thinking: A quasi-experimental study

IF 1.8 Q3 NURSING

International Journal of Orthopaedic and Trauma Nursing Pub Date : 2026-08-01 Epub Date: 2026-07-21 DOI:10.1016/j.ijotn.2026.101305

Satik Sutthiviriwan, Nuntawat Pinyo, Khwanchit Kuptanont, Arrisara Sukwatjanee

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引用次数: 0

Abstract

Background

Critical thinking (CT) is essential in orthopaedic nursing practice, where nurses must accurately assess fractures, identify complications, plan mobility strategies, and support postoperative recovery. Concept mapping (CMAP) can facilitate structured clinical reasoning, while artificial intelligence (AI) may further support conceptual organization and reflective learning processes. However, evidence regarding AI-assisted CMAP in orthopaedic nursing education remains limited.

Aim

To evaluate the effectiveness of an AI-assisted CMAP program in improving CT among undergraduate students enrolled in an orthopaedic nursing course.

Methods

A two-group quasi-experimental pretest–posttest design was employed. Participants were allocated to either an experimental group receiving AI-assisted CMAP using ChatGPT (OpenAI) during a structured workshop or a control group receiving standard instructional activities. CT was evaluated using a validated 12-item CMAP-based assessment tool administered before and after the intervention. Data were analyzed using mixed-design ANOVA and ANCOVA.

Results

CT scores improved significantly over time, with greater improvement observed in the experimental group. Mean CT scores in the experimental group increased from 2.40 ± 0.50 at pretest to 2.97 ± 0.72 at posttest, whereas scores in the control group increased from 2.43 ± 0.68 to 2.57 ± 0.63. A significant interaction effect between time and group was identified (F(1,58) = 9.705, p = .003, partial η² = 0.143). Students in the experimental group also reported high satisfaction with the AI-assisted CMAP program.

Conclusions

AI-assisted CMAP may support CT development and structured clinical reasoning in orthopaedic nursing education. Integrating AI-assisted reflective support into concept-mapping activities may provide an effective pedagogical approach for helping nursing students organize and integrate complex clinical information.

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人工智能辅助概念映射增强骨科护理学生批判性思维：一项准实验研究

背景：批判性思维（CT）在骨科护理实践中是必不可少的，护士必须准确评估骨折，识别并发症，计划活动策略，并支持术后恢复。概念映射（CMAP）可以促进结构化临床推理，而人工智能（AI）可以进一步支持概念组织和反思性学习过程。然而，关于人工智能辅助CMAP在骨科护理教育中的应用的证据仍然有限。目的：评价人工智能辅助CMAP项目在骨科护理专业本科学生中提高CT水平的有效性。方法：采用两组准实验前测后测设计。参与者被分配到实验组，实验组在结构化研讨会期间使用ChatGPT （OpenAI）接受人工智能辅助的CMAP，对照组接受标准的教学活动。在干预前后使用经过验证的基于cmap的12项评估工具评估CT。数据分析采用混合设计方差分析和方差分析。结果：CT评分随时间明显提高，实验组改善更大。对实验组的平均CT评分从2.40增加 ±0.50  预备考试2.97 ±0.72  后续测试,而在对照组增加分数2.43 ± 0.68到2.57 ±0.63 。时间与组间存在显著交互作用（F（1,58） = 9.705,p = ）。003，偏η2 = 0.143)。实验组的学生对人工智能辅助的CMAP项目也有很高的满意度。结论：人工智能辅助的CMAP可以支持CT的发展和骨科护理教育中的结构化临床推理。将人工智能辅助的反思支持整合到概念映射活动中，可以为帮助护理学生组织和整合复杂的临床信息提供有效的教学方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Orthopaedic and Trauma Nursing NURSING-

CiteScore

2.60

自引率

14.30%

发文量