Nursing open · 2026
AI System Usability and Learning Engagement in Nursing Simulation: Cross-Sectional Statistical Indirect Associations Through Extraneous Cognitive Load and Flow Experience.
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Liu Mengjiao, Zhang Ping, Wu Yeqing, Pan Lu, Li Lan
Аннотация
INTRODUCTION: The association between artificial intelligence simulation-system usability and nursing students' learning engagement remains unclear.
AIM(S): To examine cross-sectional indirect associations linking system usability, extraneous cognitive load, flow, and learning engagement, and explore moderation by digital readiness among nursing students.
METHODOLOGY: The hospital research team conducted an online cross-sectional survey of 2016 nursing students. Teachers at 16 colleges provided only voluntary, public-interest assistance by forwarding the survey link; neither the colleges nor their personnel were participating research institutions. Established measures, structural equation modelling, bootstrap tests, and multi-group analysis were used.
RESULTS: Higher usability was associated with lower extraneous load and higher engagement; lower load with greater flow, and greater flow with engagement. The sequential indirect association was supported. The load-flow association was stronger at lower digital readiness. Concurrent measurement precludes causal inference.
CONCLUSION: Usability, extraneous cognitive load, flow, and engagement showed theoretically ordered cross-sectional associations. Longitudinal or experimental studies are needed to test temporal ordering.
REVIEW METHODS: Not applicable to this empirical cross-sectional study.
DATA SOURCES: From August to December 2025, the hospital research team conducted an online anonymous survey of 2016 nursing students. Teachers at 16 colleges only assisted in forwarding the questionnaire link and were not participating research institutions.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Accessible interfaces and differentiated support should be considered, especially for less digitally ready students.
IMPACT: The study addressed the gap in understanding the psychological pathways (cognitive load and flow) that link the usability of AI systems to nursing students' engagement in virtual simulation. Higher usability was associated with lower load, greater flow, and higher engagement; the load-flow association varied by digital readiness. The findings may inform accessible simulation-system design for diverse nursing students.
REPORTING METHOD: The Strengthening the Reporting of Observational Studies in Epidemiology checklist was followed.
NO PATIENT OR PUBLIC CONTRIBUTION: No patient or members of the public were involved because participants were nursing students.
AIM(S): To examine cross-sectional indirect associations linking system usability, extraneous cognitive load, flow, and learning engagement, and explore moderation by digital readiness among nursing students.
METHODOLOGY: The hospital research team conducted an online cross-sectional survey of 2016 nursing students. Teachers at 16 colleges provided only voluntary, public-interest assistance by forwarding the survey link; neither the colleges nor their personnel were participating research institutions. Established measures, structural equation modelling, bootstrap tests, and multi-group analysis were used.
RESULTS: Higher usability was associated with lower extraneous load and higher engagement; lower load with greater flow, and greater flow with engagement. The sequential indirect association was supported. The load-flow association was stronger at lower digital readiness. Concurrent measurement precludes causal inference.
CONCLUSION: Usability, extraneous cognitive load, flow, and engagement showed theoretically ordered cross-sectional associations. Longitudinal or experimental studies are needed to test temporal ordering.
REVIEW METHODS: Not applicable to this empirical cross-sectional study.
DATA SOURCES: From August to December 2025, the hospital research team conducted an online anonymous survey of 2016 nursing students. Teachers at 16 colleges only assisted in forwarding the questionnaire link and were not participating research institutions.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Accessible interfaces and differentiated support should be considered, especially for less digitally ready students.
IMPACT: The study addressed the gap in understanding the psychological pathways (cognitive load and flow) that link the usability of AI systems to nursing students' engagement in virtual simulation. Higher usability was associated with lower load, greater flow, and higher engagement; the load-flow association varied by digital readiness. The findings may inform accessible simulation-system design for diverse nursing students.
REPORTING METHOD: The Strengthening the Reporting of Observational Studies in Epidemiology checklist was followed.
NO PATIENT OR PUBLIC CONTRIBUTION: No patient or members of the public were involved because participants were nursing students.