Objective: to observe the effectiveness of scene simulation teaching method in surgical nursing practice. Methods: in September of 1950s, the residents of our hospital were randomly divided into two groups. The contro...Objective: to observe the effectiveness of scene simulation teaching method in surgical nursing practice. Methods: in September of 1950s, the residents of our hospital were randomly divided into two groups. The control group (n30) used traditional teaching method, while the research group (n30) used simulated situational teaching method. Results: the theoretical score of the research group was (87.58-5.78) and that of the control group was (73.12-4.86). The scores of professional skills and comprehensive accomplishment of the research group were higher than those of the control group, with statistical significance (p 0.05). The satisfaction of the study group and the control group was 96.7% and 73.3% respectively, with significant difference between the two groups (p 0.05). Conclusion: scene simulation teaching method in surgical nursing practice can effectively improve students assessment results, help students to master the corresponding nursing skills, and has the value of popularization and application.展开更多
Objective: explore the significance of MDT combined with scenario simulation teaching in the training and teaching of intensive care medicine residents. Method: experimental control method was used in this study. Eigh...Objective: explore the significance of MDT combined with scenario simulation teaching in the training and teaching of intensive care medicine residents. Method: experimental control method was used in this study. Eighty-one physicians who received standardized resident training in the department of critical care medicine of our hospital from September 2019 to December 2020 were selected as the research subjects. Among them, 46 physicians who participated in the standardized training of critical care medicine from September to December 2020 were assigned to the experimental group. MDT combined with scenario simulation teaching mode was used for teaching, including cardiopulmonary resuscitation, shock management process and dyspnea management process. Thirty-five physicians who participated in the training from September to December 2019 served as the control group, and compared with the same period of the previous year, the teaching effect was evaluated. Results: the reorganized students were better than the control group in clinical operation assessment, after-school active learning, satisfaction and teamwork ability, with statistical significance (P < 0.05). Conclusion: MDT combined with scenario simulation teaching mode has positive significance in the cultivation of operation ability, learning enthusiasm and teamwork ability of critical medicine residents.展开更多
The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.T...The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.This study presents practical experiences in applying AI to programming courses.First,the global trends in AI-powered teaching and learning are analyzed.Key challenges in programming education that can be addressed by AI are then identified.Focusing on common teaching problems,an introductory programming course is used to demonstrate the construction of a course engine powered by large language models.This engine enables the creation of intelligent courses,driving innovation in teaching scenes,and transforming both teaching and learning methods.The exploration then extends to the design of AI-enhanced teaching and learning environments,featuring AI teaching assistants and AI learning companions.These tools provide scalable,differentiated,and personalized support for teachers.They also enable one-on-one,adaptive,and customized learning experiences for students.An integrated learning support system is proposed,which combines courses,training,competitions,testing,evaluation,and certification.The goal is to build a smart teaching ecosystem with knowledge services,personalized learning,and instructional support,as well as to realize the entire teaching process of“course–training–competition–testing–evaluation”empowered by AI for all elements and all time periods.Furthermore,the intelligent&interactive virtual massive open online courses(IMOOCs)for C programming is developed.A new hybrid teaching model based on IMOOC,which integrates virtual and real elements and promotes crossdomain collaboration,has also been explored.Potential risks of overreliance on AI tools are discussed,together with strategies to address them.Finally,future trends and challenges in“AI+Higher Education”are examined.The study argues that AI will unlock new possibilities for reshaping how higher education is delivered and experienced.展开更多
文摘Objective: to observe the effectiveness of scene simulation teaching method in surgical nursing practice. Methods: in September of 1950s, the residents of our hospital were randomly divided into two groups. The control group (n30) used traditional teaching method, while the research group (n30) used simulated situational teaching method. Results: the theoretical score of the research group was (87.58-5.78) and that of the control group was (73.12-4.86). The scores of professional skills and comprehensive accomplishment of the research group were higher than those of the control group, with statistical significance (p 0.05). The satisfaction of the study group and the control group was 96.7% and 73.3% respectively, with significant difference between the two groups (p 0.05). Conclusion: scene simulation teaching method in surgical nursing practice can effectively improve students assessment results, help students to master the corresponding nursing skills, and has the value of popularization and application.
文摘Objective: explore the significance of MDT combined with scenario simulation teaching in the training and teaching of intensive care medicine residents. Method: experimental control method was used in this study. Eighty-one physicians who received standardized resident training in the department of critical care medicine of our hospital from September 2019 to December 2020 were selected as the research subjects. Among them, 46 physicians who participated in the standardized training of critical care medicine from September to December 2020 were assigned to the experimental group. MDT combined with scenario simulation teaching mode was used for teaching, including cardiopulmonary resuscitation, shock management process and dyspnea management process. Thirty-five physicians who participated in the training from September to December 2019 served as the control group, and compared with the same period of the previous year, the teaching effect was evaluated. Results: the reorganized students were better than the control group in clinical operation assessment, after-school active learning, satisfaction and teamwork ability, with statistical significance (P < 0.05). Conclusion: MDT combined with scenario simulation teaching mode has positive significance in the cultivation of operation ability, learning enthusiasm and teamwork ability of critical medicine residents.
基金supported by Key Project of Higher Education Teaching Reform Research in Heilongjiang Province,China(Undergraduate Education)(Grant No.SJGZB2024028).
文摘The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.This study presents practical experiences in applying AI to programming courses.First,the global trends in AI-powered teaching and learning are analyzed.Key challenges in programming education that can be addressed by AI are then identified.Focusing on common teaching problems,an introductory programming course is used to demonstrate the construction of a course engine powered by large language models.This engine enables the creation of intelligent courses,driving innovation in teaching scenes,and transforming both teaching and learning methods.The exploration then extends to the design of AI-enhanced teaching and learning environments,featuring AI teaching assistants and AI learning companions.These tools provide scalable,differentiated,and personalized support for teachers.They also enable one-on-one,adaptive,and customized learning experiences for students.An integrated learning support system is proposed,which combines courses,training,competitions,testing,evaluation,and certification.The goal is to build a smart teaching ecosystem with knowledge services,personalized learning,and instructional support,as well as to realize the entire teaching process of“course–training–competition–testing–evaluation”empowered by AI for all elements and all time periods.Furthermore,the intelligent&interactive virtual massive open online courses(IMOOCs)for C programming is developed.A new hybrid teaching model based on IMOOC,which integrates virtual and real elements and promotes crossdomain collaboration,has also been explored.Potential risks of overreliance on AI tools are discussed,together with strategies to address them.Finally,future trends and challenges in“AI+Higher Education”are examined.The study argues that AI will unlock new possibilities for reshaping how higher education is delivered and experienced.
