Objective:To explore the application effect of flipped classroom combined with case-based learning teaching methods in pharmacoeconomics teaching.Methods:The students majoring in clinical pharmacy in 2019 were selecte...Objective:To explore the application effect of flipped classroom combined with case-based learning teaching methods in pharmacoeconomics teaching.Methods:The students majoring in clinical pharmacy in 2019 were selected as the study subjects,and the cost-effectiveness analysis of different dosage forms of Yinzhihuang in the treatment of neonatal jaundice was selected as the teaching case.The flipped classroom combined with case-based learning teaching method was used to carry out theoretical teaching to the students.After the course,questionnaires were distributed through the Sojump platform to evaluate the teaching effect.Results:The results of the questionnaire showed that 85.71%of the students believed that the flipped classroom combined with case-based learning teaching method was helpful in mobilizing the learning enthusiasm and initiative,and improving the comprehensive application ability of the knowledge of pharmacoeconomics.92.86%of the students think that it is conducive to the understanding and memorization of learning content,as well as the cultivation of teamwork,communication,etc.Conclusion:Flipped classroom combined with case-based learning teaching method can improve students’knowledge mastery,thinking skills,and practical application skills,as well as optimize and improve teachers’teaching levels.展开更多
Objective:The integration of training in theory and practice across the medical education spectrum is being encouraged to increase student understanding and skills in the sciences.This study aimed to determine the dec...Objective:The integration of training in theory and practice across the medical education spectrum is being encouraged to increase student understanding and skills in the sciences.This study aimed to determine the deciding factors that drive students'perceived advantages in class to improve precision education and the teaching model.Methods:A mixed strategy of an existing flipped classroom(FC)and a case-based learning(CBL)model was conducted in a medical morphology curriculum for 575 postgraduate students.The subjective learning evaluation of the individuals(learning time,engagement,study interest and concentration,and professional integration)was collected and analyzed after FC-CBL model learning.Results:The results from the general evaluation showed promising results of the medical morphology in the FC-CBL model.Students felt more engaged by instructors in person and benefited in terms of time-saving,flexible arrangements,and professional improvement.Our study contributed to the FC-CBL model in Research Design in postgraduate training in 4 categories:1)advancing a guideline of precision teaching according to individual characteristics;2)revealing whether a learning background is needed for a Research Design course to guide setting up a preliminary course;3)understanding the perceived advantages and their interfaces;and 4)barriers and/or improvement to implement the FC-CBL model in the Research Design class,such as a richer description of e-learning and hands-on practice.Conclusion:Undertaking a FC-CBL combined model could be a useful addition to pedagogy for medical morphology learning in postgraduate training.展开更多
This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are ...This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.展开更多
目的研究以案例为基础的教学法(case based learning,CBL)和以团队为基础的教学法(team based learning,TBL)的联合教学法在儿科学教学中的应用效果。方法2021年12月—2022年1月,选择在佳木斯大学附属第一医院实习的2018级卓越医生班学...目的研究以案例为基础的教学法(case based learning,CBL)和以团队为基础的教学法(team based learning,TBL)的联合教学法在儿科学教学中的应用效果。方法2021年12月—2022年1月,选择在佳木斯大学附属第一医院实习的2018级卓越医生班学生60名,根据教学方法的不同分为对照组和观察组,每组30名学生,对照组施以传统教学法,观察组施以CBL和TBL联合教学法。对比2组的教学效果。结果观察组自主学习评分中课前预习、查阅资料、知识理解、各学科联系、知识扩展、巩固与复习的分值分别为(4.20±0.61)分、(4.38±0.54)分、(4.40±0.47)分、(4.30±0.51)分、(4.13±0.55)分、(4.30±0.59)分,课堂教学效果评价项目中课堂氛围、参与主动性及积极性、与老师交流、与同学交流、课堂注意力分别为(4.01±0.66)分、(4.33±0.57)分、(4.18±0.60)分、(4.09±0.52)分、(3.87±0.64)分,均高于对照组,差异有统计学意义(P<0.05);观察组学生的SEGUE项目中沟通启动、信息收集、信息给予、理解患儿、沟通结束的分值依次为(4.50±0.39)分、(6.90±1.29)分、(3.20±0.67)分、(3.68±0.70)分、(3.70±0.58)分,对教学模式的评价条目中学习兴趣、文献查阅能力、参与的主动性、学习效率、处理分析能力、掌握重难点情况、表达和沟通能力、总结能力、师生互动、组织课堂合理性的得分依次为(9.00±0.64)分、(9.29±0.54)分、(8.88±0.68)分、(9.04±0.70)分、(9.32±0.48)分、(9.42±0.50)分、(9.11±0.73)分、(8.79±0.86)分、(8.56±1.10)分、(8.60±1.23)分,出科成绩总分为(93.31±4.32)分,均高于对照组,差异有统计学意义(P<0.05)。结论在儿科学教学中应用CBL和TBL联合教学法能够改善学生的自主学习能力,提升课堂教学效果、学生医患沟通能力,还有助于提高学生对教学模式的认可度。展开更多
With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning te...With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.展开更多
In European higher education,application of information technology,concentration on the learning-processes,consistent implementation,transfer learning,case-based learning,autonomous learning has been extensively studi...In European higher education,application of information technology,concentration on the learning-processes,consistent implementation,transfer learning,case-based learning,autonomous learning has been extensively studied in the last decade.Educational sciences based on neuroscientific findings use brain-based learning and teaching,including integrated thematic instructions and emotion-theory.Elements essential to this strategy,such as theory and methods for learning,competencies,attitudes,social reality,and a metadiscourse are described herein.Research on learning tends to focus on declarative knowledge,associative learning with conditional stimuli,and procedural knowledge with polythematic/crosslinking thinking.Research on competencies:In research on competencies(e.g.,for clinical reasoning,decision-making),intuitive and analytical components are studied.As repeated presentation and exercising of clinical cases is crucial for an efficient learning process,the implementation of interactive scenarios including affectively involving didactics is considered.For competence-development observational methods,questionnaires/item sets or factors have to be targeted and empirically validated.Attitudes and social reality:Clinical decision-making,identification processes and attitudes(“Hidden curriculum”),as well as secondary socialization processes(integration of social norms,values,preparation of role-acquisition,occupational role)are studied via process research,conceptual research,and observational methods.With respect to social reality research,conscious and unconscious bargaining processes have to be taken into account.Methodology:Neuroscience-memory,neuronal,molecular biology,and computer science(Neurocircuits)are integrated into observational process research(e.g.,affective-cognitive interface,identification processes)and conceptual research is added and studied on the meta-level,including discussion of research paradigms.This discussion provides ongoing feedback to projects in a hermeneutic circle.展开更多
Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts...Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical eases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learning environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastrneture is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool （ICBFLT）, which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students＇ and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students＇ academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.展开更多
Case-based learning(CBL) is gradually replacing the traditional lecturing-based learning in nursing English teaching.In the process of CBL, selecting and compiling a good case is key to the success of CBL. In the mean...Case-based learning(CBL) is gradually replacing the traditional lecturing-based learning in nursing English teaching.In the process of CBL, selecting and compiling a good case is key to the success of CBL. In the meantime, designing questions is an important factor for successful CBL. In this article, we discuss how to select and compile cases and how to design questions in CBL used in Medical-nursing English Teaching.展开更多
The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such...The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such as matching attributes selection, similarity measure calculation, weights learning and training evaluation policies are carefully studied. The testing applications illustrate that an accuracy of 74.67 % can be achieved with 75 balanced-distributed failure cases covering 3 failure modes, and that the resulting learning weight vector can be well applied to the other 2 failure modes, achieving 73.3 % of recognition accuracy. It is also proved that its popularizing capability is good to the recognition of even more mixed failure modes.展开更多
With the prosperity of the Intemet, e-learning has been greatly improved. By supporting multiple learners and multiple roles in a learning activity, the IMS Leaming Design （LD） specification provides a collaborative...With the prosperity of the Intemet, e-learning has been greatly improved. By supporting multiple learners and multiple roles in a learning activity, the IMS Leaming Design （LD） specification provides a collaborative scenario for participants. However, IMS LD provides insufficient support for interaction among learning activities and can not dynamically integrate learning resources to meet the continually changing service requirements. In this paper, a Business Process Execution Language （BPEL） enhanced requirement driven learning management architecture to address the issues of personalize adaptive learning was proposed. It models the learning activity by combining IMS LD with BPEL and matches optimal learning sequence based on Case-based reasoning （CBR） method. By providing expandable secure learning sequences flexibly, it satisfies the different actual demands for personalize learning展开更多
基金2022 Medical Innovation and Development Project of Lanzhou University(lzuyxcx-2022-40)2022 Education and Teaching Reform Research Project of Lanzhou University General Project(202201)The Foundation of the First Hospital of Lanzhou University(ldyyyn 2021-92)。
文摘Objective:To explore the application effect of flipped classroom combined with case-based learning teaching methods in pharmacoeconomics teaching.Methods:The students majoring in clinical pharmacy in 2019 were selected as the study subjects,and the cost-effectiveness analysis of different dosage forms of Yinzhihuang in the treatment of neonatal jaundice was selected as the teaching case.The flipped classroom combined with case-based learning teaching method was used to carry out theoretical teaching to the students.After the course,questionnaires were distributed through the Sojump platform to evaluate the teaching effect.Results:The results of the questionnaire showed that 85.71%of the students believed that the flipped classroom combined with case-based learning teaching method was helpful in mobilizing the learning enthusiasm and initiative,and improving the comprehensive application ability of the knowledge of pharmacoeconomics.92.86%of the students think that it is conducive to the understanding and memorization of learning content,as well as the cultivation of teamwork,communication,etc.Conclusion:Flipped classroom combined with case-based learning teaching method can improve students’knowledge mastery,thinking skills,and practical application skills,as well as optimize and improve teachers’teaching levels.
基金supported by grants from the Hunan Province Academic Degree and Graduate Education Reform Project(No.2020JGYB028)the National Natural Science Foundation of China(No.81971891,No.82172196,No.81772134)+1 种基金the Key Laboratory of Emergency and Trauma(Hainan Medical University)of the Ministry of Education(No.KLET-202108)the College Students'Innovation and Entrepreneurship Project(No.S20210026020013).
文摘Objective:The integration of training in theory and practice across the medical education spectrum is being encouraged to increase student understanding and skills in the sciences.This study aimed to determine the deciding factors that drive students'perceived advantages in class to improve precision education and the teaching model.Methods:A mixed strategy of an existing flipped classroom(FC)and a case-based learning(CBL)model was conducted in a medical morphology curriculum for 575 postgraduate students.The subjective learning evaluation of the individuals(learning time,engagement,study interest and concentration,and professional integration)was collected and analyzed after FC-CBL model learning.Results:The results from the general evaluation showed promising results of the medical morphology in the FC-CBL model.Students felt more engaged by instructors in person and benefited in terms of time-saving,flexible arrangements,and professional improvement.Our study contributed to the FC-CBL model in Research Design in postgraduate training in 4 categories:1)advancing a guideline of precision teaching according to individual characteristics;2)revealing whether a learning background is needed for a Research Design course to guide setting up a preliminary course;3)understanding the perceived advantages and their interfaces;and 4)barriers and/or improvement to implement the FC-CBL model in the Research Design class,such as a richer description of e-learning and hands-on practice.Conclusion:Undertaking a FC-CBL combined model could be a useful addition to pedagogy for medical morphology learning in postgraduate training.
文摘This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.
文摘目的研究以案例为基础的教学法(case based learning,CBL)和以团队为基础的教学法(team based learning,TBL)的联合教学法在儿科学教学中的应用效果。方法2021年12月—2022年1月,选择在佳木斯大学附属第一医院实习的2018级卓越医生班学生60名,根据教学方法的不同分为对照组和观察组,每组30名学生,对照组施以传统教学法,观察组施以CBL和TBL联合教学法。对比2组的教学效果。结果观察组自主学习评分中课前预习、查阅资料、知识理解、各学科联系、知识扩展、巩固与复习的分值分别为(4.20±0.61)分、(4.38±0.54)分、(4.40±0.47)分、(4.30±0.51)分、(4.13±0.55)分、(4.30±0.59)分,课堂教学效果评价项目中课堂氛围、参与主动性及积极性、与老师交流、与同学交流、课堂注意力分别为(4.01±0.66)分、(4.33±0.57)分、(4.18±0.60)分、(4.09±0.52)分、(3.87±0.64)分,均高于对照组,差异有统计学意义(P<0.05);观察组学生的SEGUE项目中沟通启动、信息收集、信息给予、理解患儿、沟通结束的分值依次为(4.50±0.39)分、(6.90±1.29)分、(3.20±0.67)分、(3.68±0.70)分、(3.70±0.58)分,对教学模式的评价条目中学习兴趣、文献查阅能力、参与的主动性、学习效率、处理分析能力、掌握重难点情况、表达和沟通能力、总结能力、师生互动、组织课堂合理性的得分依次为(9.00±0.64)分、(9.29±0.54)分、(8.88±0.68)分、(9.04±0.70)分、(9.32±0.48)分、(9.42±0.50)分、(9.11±0.73)分、(8.79±0.86)分、(8.56±1.10)分、(8.60±1.23)分,出科成绩总分为(93.31±4.32)分,均高于对照组,差异有统计学意义(P<0.05)。结论在儿科学教学中应用CBL和TBL联合教学法能够改善学生的自主学习能力,提升课堂教学效果、学生医患沟通能力,还有助于提高学生对教学模式的认可度。
基金supported by the National Natural Science Foundation of China(No.U1960202)。
文摘With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.
文摘In European higher education,application of information technology,concentration on the learning-processes,consistent implementation,transfer learning,case-based learning,autonomous learning has been extensively studied in the last decade.Educational sciences based on neuroscientific findings use brain-based learning and teaching,including integrated thematic instructions and emotion-theory.Elements essential to this strategy,such as theory and methods for learning,competencies,attitudes,social reality,and a metadiscourse are described herein.Research on learning tends to focus on declarative knowledge,associative learning with conditional stimuli,and procedural knowledge with polythematic/crosslinking thinking.Research on competencies:In research on competencies(e.g.,for clinical reasoning,decision-making),intuitive and analytical components are studied.As repeated presentation and exercising of clinical cases is crucial for an efficient learning process,the implementation of interactive scenarios including affectively involving didactics is considered.For competence-development observational methods,questionnaires/item sets or factors have to be targeted and empirically validated.Attitudes and social reality:Clinical decision-making,identification processes and attitudes(“Hidden curriculum”),as well as secondary socialization processes(integration of social norms,values,preparation of role-acquisition,occupational role)are studied via process research,conceptual research,and observational methods.With respect to social reality research,conscious and unconscious bargaining processes have to be taken into account.Methodology:Neuroscience-memory,neuronal,molecular biology,and computer science(Neurocircuits)are integrated into observational process research(e.g.,affective-cognitive interface,identification processes)and conceptual research is added and studied on the meta-level,including discussion of research paradigms.This discussion provides ongoing feedback to projects in a hermeneutic circle.
文摘Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical eases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learning environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastrneture is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool （ICBFLT）, which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students＇ and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students＇ academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.
文摘Case-based learning(CBL) is gradually replacing the traditional lecturing-based learning in nursing English teaching.In the process of CBL, selecting and compiling a good case is key to the success of CBL. In the meantime, designing questions is an important factor for successful CBL. In this article, we discuss how to select and compile cases and how to design questions in CBL used in Medical-nursing English Teaching.
文摘The combination of case-based reasoning （CBR） and genetic algorithm （GA） is considered in the problem of failure mode identification in aeronautical component failure analysis. Several imple- mentation issues such as matching attributes selection, similarity measure calculation, weights learning and training evaluation policies are carefully studied. The testing applications illustrate that an accuracy of 74.67 % can be achieved with 75 balanced-distributed failure cases covering 3 failure modes, and that the resulting learning weight vector can be well applied to the other 2 failure modes, achieving 73.3 % of recognition accuracy. It is also proved that its popularizing capability is good to the recognition of even more mixed failure modes.
基金National Natural Science Foundation of China (No.60673010)Natural Science Foundation of Hubei Province ofChina (No.2009CDA135)
文摘With the prosperity of the Intemet, e-learning has been greatly improved. By supporting multiple learners and multiple roles in a learning activity, the IMS Leaming Design （LD） specification provides a collaborative scenario for participants. However, IMS LD provides insufficient support for interaction among learning activities and can not dynamically integrate learning resources to meet the continually changing service requirements. In this paper, a Business Process Execution Language （BPEL） enhanced requirement driven learning management architecture to address the issues of personalize adaptive learning was proposed. It models the learning activity by combining IMS LD with BPEL and matches optimal learning sequence based on Case-based reasoning （CBR） method. By providing expandable secure learning sequences flexibly, it satisfies the different actual demands for personalize learning
