Chinese Journal of Nursing Education ›› 2026, Vol. 23 ›› Issue (3): 286-293.doi: 10.3761/j.issn.1672-9234.2026.03.005
• Simulated Teaching • Previous Articles Next Articles
YAN Xiaoqian(
), WANG Ziyu, CHEN Ou, LI Jing, GUO Yufang*(
)
Received:2025-09-29
Online:2026-03-15
Published:2026-03-17
Contact:
*GUO Yufang,E-mail:cdguoyufang@163.com
Supported by:YAN Xiaoqian, WANG Ziyu, CHEN Ou, LI Jing, GUO Yufang. A scoping review of multimodal learning analytics for students’ teamwork competence in nursing scenario simulation teaching[J].Chinese Journal of Nursing Education, 2026, 23(3): 286-293.
| [1] | Chen CY, Tang M, Yang AB. Progress in a multimodal learning evaluation based on artificial intelligence[J]. Front Educ Res, 2024, 7(7):22-27. |
| [2] |
Monsalves D, Cornide-Reyes H, Riquelme F. Relationships between social interactions and belbin role types in collaborative agile teams[J]. IEEE Access, 2023, 11:17002-17020.
doi: 10.1109/ACCESS.2023.3245325 |
| [3] | Blikstein P, Worsley M. Multimodal learning analytics and education data mining:using computational technologies to measure complex learning tasks[J]. J Learn Anal, 2016, 3(2):220-238. |
| [4] | Qushem UB, Christopoulos A, Laakso MJ. The value proposition of an integrated multimodal learning analytics framework[C]// Proceedings of the 45th Jubilee International Convention on Information,Communication and Electronic Technology(MIPRO). Opatija,Croatia:IEEE,2022:666-671. |
| [5] | Alwahaby H, Cukurova M, Papamitsiou Z, et al. The evidence of impact and ethical considerations of multimodal learning analytics:a systematic literature review[M]//The multimodal learning analytics handbook. Cham: Springer International Publishing,2022:289-325. |
| [6] | Ochoa X. Multimodal learning analytics:rationale,process,examples,and direction[M]//Lang C,Siemens G,Wise AF et al. Handbook of learning analytics. 2nd ed. Vancouver,BC:SoLAR,2022:54-65. |
| [7] |
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 |
| [8] |
Yürüm OR. Technology-enhanced multimodal learning analytics in higher education:a systematic literature review[J]. IEEE Access, 2025, 13:92057-92073.
doi: 10.1109/ACCESS.2025.3572467 |
| [9] |
Schwendimann BA, Rodríguez-Triana MJ, Vozniuk A, et al. Perceiving learning at a glance:a systematic literature review of learning dashboard research[J]. IEEE Trans Learn Technol, 2017, 10(1):30-41.
doi: 10.1109/TLT.2016.2599522 |
| [10] | Di Mitri D. Digital learning projection:learning performance estimation from multimodal learning experiences[C]//Proceedings of the 18th International Conference on Artificial Intelligence in Education. Cham:Springer International Publishing,2017:609-612. |
| [11] |
Cukurova M, Giannakos M, Martinez-Maldonado R. The promise and challenges of multimodal learning analytics[J]. Br J Educ Technol, 2020, 51(5):1441-1449.
doi: 10.1111/bjet.v51.5 |
| [12] | Wise AF, Knight S, Shum SB. Collaborative learning analy-tics[M]// International handbook of computer-supported collaborative learning. Cham: Springer International Publishing, 2021:425-443. |
| [13] |
Peters MDJ, Marnie C, Tricco AC, et al. Updated methodological guidance for the conduct of scoping reviews[J]. JBI Evid Synth, 2020, 18(10):2119-2126.
doi: 10.11124/JBIES-20-00167 pmid: 33038124 |
| [14] |
Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews(PRISMA-ScR):checklist and explanation[J]. Ann Intern Med, 2018, 169(7):467-473.
doi: 10.7326/M18-0850 |
| [15] | Alwahaby H, Cukurova M, Papamitsiou Z, et al. The evidence of impact and ethical considerations of multimodal learning analytics:a systematic literature review[M]//The multimodal learning analytics handbook. Cham: Springer International Publishing, 2022:289-325. |
| [16] | Matcha W, Uzir NA, Gašević D, et al. A systematic review of empirical studies on learning analytics dashboards:a self-regulated learning perspective[J]. IEEE Trans Learn Technol, 2020: 13(2):226-245. |
| [17] | Stevens MJ, Campion MA. Staffing work teams:development and validation of a selection test for teamwork settings[J]. J Manag, 1999, 25(2):207-228. |
| [18] |
Hairida H, Marmawi M, Kartono K. An analysis of students’ collaboration skills in science learning through inquiry and project-based learning[J]. Tadris:Jurnal Keguruan dan Ilmu Tarbiyah, 2021, 6(2):219-228.
doi: 10.24042/tadris.v6i2.9320 |
| [19] | Zhao LX, Echeverria V, Swiecki Z, et al. Epistemic network analysis for end-users:closing the loop in the context of multimodal analytics for collaborative team learning[C]//Proceedings of the 14th Learning Analytics and Knowledge Conference. March 18-22,2024,Kyoto,Japan:ACM,2024:90-100. |
| [20] | Martinez-Maldonado R, Echeverria V, Fernandez-Nieto G, et al. Lessons learnt from a multimodal learning analytics deployment in-the-wild[J]. TOCHI, 2023, 31(1):1-41. |
| [21] | Joshi V, Akiri S, Taherzadeh S, et al. Investigating differences in paramedic trainees’ multimodal interaction during low and high physiological synchrony[C]//Proceedings of the 27th International Conference on Multimodal Interaction. Canberra Australia:ACM,2025:526-534. |
| [22] | Sánchez D. Learning under stress:enhancing team-based simulation training with multimodal data[C]//Proceedings of the 17th International Conference on Computer-Supported Collaborative Learning. Buffalo,NY,USA:International Society of the Learning Sciences,2024:225-228. |
| [23] | Shah M, Tan YR, Eagan B, et al. A dual-method examination of nursing students’ teamwork in simulation-based learning:combining CORDTRA and ordered network analysis to reveal patterns and dynamics[C]//Proceedings of the 15th International Learning Analytics and Knowledge Conference. Dublin Ireland:ACM,2025:858-864. |
| [24] | Yan LX, Gasevic D, Echeverria V, et al. From complexity to parsimony:integrating latent class analysis to uncover multimodal learning patterns in collaborative learning[C]//Proceedings of the 15th International Learning Analytics and Knowledge Conference. Dublin,Ireland:ACM,2025:70-81. |
| [25] |
Echeverria V, Martinez-Maldonado R, Yan LX, et al. HuCETA:a framework for human-centered embodied teamwork analytics[J]. IEEE Pervasive Comput, 2023, 22(1):39-49.
doi: 10.1109/MPRV.2022.3217454 |
| [26] |
Fernandez-Nieto GM, Echeverria V, Shum SB, et al. Storytelling with learner data:guiding student reflection on multimodal team data[J]. IEEE Trans Learn Technol, 2021, 14(5):695-708.
doi: 10.1109/TLT.2021.3131842 |
| [27] | Echeverria V, Zhao LX, Alfredo R, et al. TeamVision:an AI-powered learning analytics system for supporting reflection in team-based healthcare simulation[C]//Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Yokohama,Japan:ACM,2025:1-22. |
| [28] | Ronda-Carracao MA, Santos OC, Fernandez-Nieto G, et al. Towards exploring stress reactions in teamwork using multimodal physiological data[C]//Proceedings of the First International Workshop on Multimodal Artificial Intelligence in Education(MAIED 2021):at the 22nd International Conference on Artificial Intelligence in Education(AIED 2021). Utrecht,Netherlands:CEUR-WS,2021:49-60. |
| [29] | Feng SH, Yan LX, Zhao LX, et al. Heterogenous network analytics of small group teamwork:using multimodal data to uncover individual behavioral engagement strategies[C]//Proceedings of the 14th Learning Analytics and Knowledge Conference. Kyoto,Japan:ACM,2024:587-597. |
| [30] | YAN LX, Gašević D, Echeverria V, et al. In sync or out of sync? Understanding stress and learning performance in collaborative healthcare simulations through physiological synchrony and arousal[J]. Int J Artif Intell Educ, 2025: 35(4):2421-2452. |
| [31] |
Vatral C, Biswas G, Cohn C, et al. Using the DiCoT framework for integrated multimodal analysis in mixed-reality training environments[J]. Front Artif Intell, 2022, 5:941825.
doi: 10.3389/frai.2022.941825 |
| [32] |
Meier A, Spada H, Rummel N. A rating scheme for assessing the quality of computer-supported collaboration processes[J]. Int J Comput Support Collab Learn, 2007, 2(1):63-86.
doi: 10.1007/s11412-006-9005-x |
| [33] | Echeverria V, Martinez-Maldonado R, Buckingham Shum S. Towards collaboration translucence:giving meaning to multimodal group data[C]//Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. Glasgow Scotland UK:ACM,2019:1-16. |
| [34] | Echeverria V, Yan LX, Zhao LX, et al. TeamSlides:a multimodal teamwork analytics dashboard for teacher-guided reflection in a physical learning space[C]//Proceedings of the 14th Learning Analytics and Knowledge Conference. Kyoto,Japan: ACM,2024:112-122. |
| [35] | Zhao LX, Swiecki Z, Gasevic D, et al. METS:multimodal learning analytics of embodied teamwork learning[C]//LAK23:13th International Learning Analytics and Knowledge Conference. Arlington,TX,USA:ACM,2023:186-196. |
| [36] | Kröger J. Unexpected inferences from sensor data:a hidden privacy threat in the Internet of Things[C]//Internet of Things. Information Processing in an Increasingly Connected World. Cham:Springer,2019:147-159. |
| [37] |
Prinsloo P, Slade S, Khalil M. Multimodal learning analytics:in-between student privacy and encroachment:a systematic review[J]. Br J Educ Technol, 2023, 54(6):1566-1586.
doi: 10.1111/bjet.v54.6 |
| [38] |
Martinez-Maldonado R, Kay J, Buckingham Shum S, et al. Collocated collaboration analytics:principles and dilemmas for mining multimodal interaction data[J]. Hum-Comput Interact, 2019, 34(1):1-50.
doi: 10.1080/07370024.2017.1338956 |
| [39] | Alwahaby H. The ethical implications of using Multimodal Learning Analytics:a framework for research and practice[D]. London: University College London, 2025. |
| [1] | LU Haixia, LI Huiling, YAO Yi, CHEN Hua, YUE Peng, WU Yanming, SUN Hongyu, CHEN Yongyi. Current status,problems and strategies of palliative care education in the nursing field in China [J]. Chinese Journal of Nursing Education, 2026, 23(6): 645-650. |
| [2] | CHEN Zhibing, GUO Yiqiang, ZHU Mingxia. Development of a conceptual framework for nursing life-and-death education centered on enhancing students’ self-life care [J]. Chinese Journal of Nursing Education, 2026, 23(6): 650-655. |
| [3] | ZHAO Jinglin, XIAO Yao, XU Lijie, YUE Peng. Development of a competency-based training program for life-and-death education course teachers in medical schools [J]. Chinese Journal of Nursing Education, 2026, 23(6): 656-662. |
| [4] | XU Hui, LU Meiling, ZHENG Rujun, ZHUANG Jiayuan, DONG Xue, WANG Juan, CHEN Yongyi. Construction of a core competency framework for advanced practice nurses in hospice care:a qualitative study from the perspective of multiple subjects [J]. Chinese Journal of Nursing Education, 2026, 23(6): 663-670. |
| [5] | ZHANG Yuhong, DONG Wei, WAN Yonghui, ZHANG Qing, ZHOU Wei, QIU Yanru. A qualitative study on the authentic experiences of trainees participating in a hospice care train-the-trainer program [J]. Chinese Journal of Nursing Education, 2026, 23(6): 670-675. |
| [6] | YUAN Fei, GU Haifeng, YIN Yu, XU Mei, DAI Qianyuan, XU Xiaowei. Implementation and effectiveness evaluation of a training program on palliative care core competencies for hematology nurses [J]. Chinese Journal of Nursing Education, 2026, 23(6): 676-682. |
| [7] | YE Lei, ZHUANG Mengyi, HE Ying, GUO Qiaohong, YU Huidan, LIANG Fang, LÜ Qin, YANG Bingxiang, GUO Jia. Construction and practice of an AI-empowered intelligent course in Nursing Ethics [J]. Chinese Journal of Nursing Education, 2026, 23(6): 683-689. |
| [8] | JIN Wentao, ZHAO Juanjuan, CAO Xi, BAI Yang, CHENG Li, ZHENG Jing, LI Kun. Analysis of the gap between nursing students’ acceptance and use behavior of artificial intelligence technology in courses and its causes [J]. Chinese Journal of Nursing Education, 2026, 23(6): 689-696. |
| [9] | CHEN Shuozhen, LI Yongtao, ZENG Fenlian, LUO Qian, CHEN Yao, TANG Weiwei, WU Xueshuang, KONG Lingna. Cross-cultural adaptation and psychometric testing of the Scale for the Assessment of Non-experts’ Artificial Intelligence Literacy among nursing students [J]. Chinese Journal of Nursing Education, 2026, 23(6): 697-704. |
| [10] | CAO Caiyi, LIU Xinyuan, WU Liping, XIE Wan, LU Hong, HAN Shuai, ZHANG Weichun. Artificial intelligence applications in undergraduate nursing education:a scoping review [J]. Chinese Journal of Nursing Education, 2026, 23(6): 704-712. |
| [11] | XIE Xiaofeng, LI Ka, YAO Liming, QING Ping, CUI Jinbo, ZHU Ling, ZHANG Fengying. Development and teaching implementation of an integrated nursing-management curriculum:practices and outcomes [J]. Chinese Journal of Nursing Education, 2026, 23(6): 713-718. |
| [12] | WANG Lin, ZHOU Ying, TAO Xingjuan. Designing and implementing ideological education in Geriatric Nursing:a scenario-based simulation approach [J]. Chinese Journal of Nursing Education, 2026, 23(6): 718-723. |
| [13] | GONG Yuanyuan, LI Qiong, HUANG Qi, OUYANG Linqi, GAO Bin. Practice and effect evaluation of integrating traditional Chinese medicine science popularization into the course of Traditional Chinese Medicine Nursing [J]. Chinese Journal of Nursing Education, 2026, 23(6): 724-731. |
| [14] | ZHANG Yunping, FAN Rong, XIA Liping. Effective pathways for cultivating empathy ability among nursing students:a systematic review [J]. Chinese Journal of Nursing Education, 2026, 23(6): 731-739. |
| [15] | ZHOU Yue, ZHENG Yan, CHEN Xiaochun, YUAN Ting, ZHANG Chuhao. Application effect of a chain health education program for type 1 diabetes in children [J]. Chinese Journal of Nursing Education, 2026, 23(6): 748-754. |
|
||