Chinese Journal of Nursing Education ›› 2026, Vol. 23 ›› Issue (11): 1318-1323.doi: 10.3761/j.issn.1672-9234.2026.11.006
• AI-empowered Nursing Education • Previous Articles Next Articles
ZHAO Chenglong1(
), YANG Qing2,*(
), AN Qi3, KONG Xiukun1, WU Ke1, LI Lin3
Received:2026-04-11
Online:2026-11-15
Published:2026-11-04
Contact:
*YANG Qing,E-mail:michy1224@163.com
Supported by:ZHAO Chenglong, YANG Qing, AN Qi, KONG Xiukun, WU Ke, LI Lin. Application progress of intelligent evaluation in the teaching of nursing majors[J].Chinese Journal of Nursing Education, 2026, 23(11): 1318-1323.
| [1] |
Alkhelaiwi WA, Traynor M, Rogers K, et al. Assessing the competence of nursing students in clinical practice:the clinical preceptors’ perspective[J]. Healthcare, 2024, 12(10):1031.
doi: 10.3390/healthcare12101031 |
| [2] |
Chan MMK, Wan AWH, Cheung DSK, et al. Integration of artificial intelligence in nursing simulation education:a scoping review[J]. Nurse Educ, 2025, 50(4):195-200.
doi: 10.1097/NNE.0000000000001851 |
| [3] | Johnsen HM, Nes AAG, Haddeland K. Experiences of using a digital guidance and assessment tool(the technology-optimized practice process in nursing application) during clinical practice in a nursing home:focus group study among nursing students[J]. JMIR Nurs, 2024, 7:e48810. |
| [4] |
Harmer B, Erickson J, Ross S, et al. Development and evaluation of a multimodal debriefing dashboard for virtual reality cardiac arrest simulation[J]. Simul Healthc, 2026, 21(1):48-56.
doi: 10.1097/SIH.0000000000000901 |
| [5] |
Yeo JY, Nam H, Park JI, et al. Multidisciplinary design-based multimodal virtual reality simulation in nursing education:mixed methods study[J]. JMIR Med Educ, 2024, 10:e53106.
doi: 10.2196/53106 |
| [6] |
Caspari-Sadeghi S. Artificial intelligence in technology-enhanced assessment:a survey of machine learning[J]. J Educ Technol Syst, 2023, 51(3):372-386.
doi: 10.1177/00472395221138791 |
| [7] |
Rezaei-Zadeh M, Cerbin-Koczorowska M. A research roadmap for AI opportunities in student assessment for medical education[J]. BMC Med Educ, 2025, 25(1):1653.
doi: 10.1186/s12909-025-08078-7 |
| [8] |
Wang XJ, Song LJ, Jiao XP, et al. Integration of artificial intelligence in nursing clinical education:enhancing the Mini-CEX model[J]. J Multidiscip Healthc, 2025, 18:7327-7337.
doi: 10.2147/JMDH.S550145 |
| [9] |
Xuto P, Prasitwattanaseree P, Chaiboonruang T, et al. Development and evaluation of an AI-assisted answer assessment(4A) for cognitive assessments in nursing education[J]. Nurs Rep, 2025, 15(3):80.
doi: 10.3390/nursrep15030080 |
| [10] |
Schwengel D, Villagrán I, Miller G, et al. Multimodal assessment in clinical simulations:a guide for moving towards precision education[J]. Med Sci Educ, 2025, 35(2):1025-1034.
doi: 10.1007/s40670-024-02221-7 pmid: 40353039 |
| [11] |
Mason ML, Vatral C, Cohn C, et al. Eye movements as predictors of student experiences during nursing simulation learning events[J]. Cogn Res Princ Implic, 2025, 10(1):37.
doi: 10.1186/s41235-025-00640-7 pmid: 40591191 |
| [12] |
Alizadeh M, Jafar Sameri M. Intelligent assessment systems in medical education:a systematic review[J]. J Adv Med Educ Prof, 2025, 13(3):173-190.
doi: 10.30476/jamp.2024.104560.2068 pmid: 40642143 |
| [13] | Janumpally RK. The role of natural language processing in graduate medical education:a scoping review[J]. Cureus, 2025, 17(3):e81078. |
| [14] |
Wong DC, Williams S. Artificial intelligence analysis of videos to augment clinical assessment:an overview[J]. Neural Regen Res, 2024, 19(4):717-718.
doi: 10.4103/1673-5374.382249 |
| [15] | Escobar-Castillejos D, Barrera-Animas AY, Noguez J, et al. Transforming surgical training with AI techniques for train-ing,assessment,and evaluation:scoping review[J]. J Med Inter-net Res, 2025, 27:e58966. |
| [16] | 刘邦奇, 聂小林, 王亚飞, 等. 生成式AI赋能教育:技术框架、应用场域及价值:2024智能教育发展研究报告[J]. 中国电化教育, 2025(3):61-70. |
| Liu BQ, Nie XL, Wang YF, et al. Generative AI empowering education:technical framework,application field and value:2024 intelligent education development research report[J]. China Educ Technol, 2025(3):61-70. | |
| [17] |
Kan CWY, Wong FMF. How students learn in small group through online mode during the coronavirus pandemic:descriptive narratives[J]. Teach Learn Nurs, 2023, 18(2):281-285.
doi: 10.1016/j.teln.2022.12.003 |
| [18] |
Stephen TC, Gierl MC, King S. Automated essay scoring(AES) of constructed responses in nursing examinations:an evaluation[J]. Nurse Educ Pract, 2021, 54:103085.
doi: 10.1016/j.nepr.2021.103085 |
| [19] | 毛翠, 周敏, 吴建军, 等. 基于“软硬技能并重”理念的高职临床护理综合实训课程改革与实践[J]. 中华护理教育, 2023, 20(12):1440-1446. |
| Mao C, Zhou M, Wu JJ, et al. Curriculum reform of Nursing Comprehensive Training in a higher vocational college based on the concept of “full integration of soft and hard skills”[J]. Chin J Nurs Educ, 2023, 20(12):1440-1446. | |
| [20] |
Fan SY, Wang SY, Zhao Y, et al. Nursing students’ perspectives on peer assessment in basic nursing procedures:a qualitative study[J]. Nurse Educ Today, 2024, 143:106348.
doi: 10.1016/j.nedt.2024.106348 |
| [21] |
Han X, Nishida N, Morita M, et al. Compensation method for missing and misidentified skeletons in nursing care action assessment by improving spatial temporal graph convolutional networks[J]. Bioengineering, 2024, 11(2):127.
doi: 10.3390/bioengineering11020127 |
| [22] |
Ji X, Guo XY, Soh KL, et al. Effectiveness of stress management interventions for nursing students:a systematic review and meta-analysis[J]. Nurs Health Sci, 2024, 26(2):e13113.
doi: 10.1111/nhs.v26.2 |
| [23] |
Fijačko N, Abella BS,Metli, Metličar Š, et al. Exploring the impact of home-based serious smartphone resuscitation gaming on stress among nursing students practicing simulated adult basic life support:randomized waitlist controlled trial[J]. JMIR Serious Games, 2025, 13:e67623.
doi: 10.2196/67623 |
| [24] |
Sepanloo K, Shevelev D, Son YJ, et al. Assessing physiological stress responses in student nurses using mixed reality training[J]. Sensors, 2025, 25(10):3222.
doi: 10.3390/s25103222 |
| [25] | García-Fernández B, González-Sanz P, Saiz-Navarro EM, et al. Impact of high-fidelity simulation and OSCE on stress,academic performance,and well-being in nursing students[J]. SAGE Open Nurs, 2025, 11:23779608251365805. |
| [26] |
Ismail NAS, Mageswaran N, Bujang SM, et al. Beyond words:analyzing non-verbal communication techniques in a medical communication skills course via synchronous online platform[J]. Front Med, 2024, 11:1375982.
doi: 10.3389/fmed.2024.1375982 |
| [27] |
Chen PJ. Effectiveness of integrating generative artificial intelligence with virtual reality for maternity communication simulation:a randomized controlled trial[J]. Clin Simul Nurs, 2025, 105:101786.
doi: 10.1016/j.ecns.2025.101786 |
| [28] |
Chen PJ. AI-enhanced virtual reality simulation for nursing students’ empathy:automated scoring and inter-rater reliability in a randomised controlled study[J]. Nurse Educ Today, 2026, 159:106968.
doi: 10.1016/j.nedt.2025.106968 |
| [29] |
Jin E, Kang H, Lee K, et al. Analysis of nursing students’ nonverbal communication patterns during simulation practice:a pilot study[J]. Healthcare, 2023, 11(16):2335.
doi: 10.3390/healthcare11162335 |
| [30] |
Mu S, Cui M, Huang XD. Multimodal data fusion in learning analytics:a systematic review[J]. Sensors, 2020, 20(23):6856.
doi: 10.3390/s20236856 |
| [31] |
Echeverria V, Nieto GF, Zhao LX, et al. A learning analytics dashboard to support students’ reflection on collaboration[J]. J Comput Assist Learn, 2025, 41(1):e13088.
doi: 10.1111/jcal.v41.1 |
| [32] |
Baldinger M, Reimer LM, Senner V. Influence of the camera viewing angle on OpenPose validity in motion analysis[J]. Sensors, 2025, 25(3):799.
doi: 10.3390/s25030799 |
| [33] |
Wang M, Li Z, Zhang QR, et al. Removal of motion artifacts in photoplethysmograph sensors during intensive exercise for accurate heart rate calculation based on frequency estimation and Notch filtering[J]. Sensors, 2019, 19(15):3312.
doi: 10.3390/s19153312 |
| [34] |
Malo MF, de Santé Publique Université de Montréal é, Bouhouita-Guermech S, et al. Using voice and speech data in healthcare:a scoping review of the ethical,legal and social implications[J]. Front Digit Health, 2026, 8:1750111.
doi: 10.3389/fdgth.2026.1750111 |
| [35] |
Jitwiriyanont S, Rawan R, Narajeenron K. Advancing politeness and assertive communication through tone of voice in crisis team situations:pre-post acoustic analysis study of team and strategies to enhance performance and patient safety(TeamSTEPPS) virtual simulation for interprofessional education in health care undergraduate students[J]. J Med Internet Res, 2025, 27:e66988.
doi: 10.2196/66988 |
| [36] |
Lee AR, Koo D, Kim IK, et al. Opportunities and challenges of a dynamic consent-based application:personalized options for personal health data sharing and utilization[J]. BMC Med Ethics, 2024, 25(1):92.
doi: 10.1186/s12910-024-01091-3 pmid: 39217356 |
| [37] |
Pati S, Kumar S, Varma A, et al. Privacy preservation for federated learning in health care[J]. Patterns, 2024, 5(7):100974.
doi: 10.1016/j.patter.2024.100974 |
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