This study constructs a theoretical model integrating traditional cultural ecological wisdom into STEAM education,exploring a new interpretation of the“unity of knowledge and action”concept in modern education.Resea...This study constructs a theoretical model integrating traditional cultural ecological wisdom into STEAM education,exploring a new interpretation of the“unity of knowledge and action”concept in modern education.Research shows that incorporating traditional ecological wisdom,such as the harmony between humanity and nature and following the laws of nature,into STEAM education’s curriculum,teaching methods,and practical activities can significantly enhance students’interdisciplinary knowledge,practical abilities,and environmental awareness.Through data simulation and empirical analysis,the model’s effectiveness is confirmed,demonstrating its significant advantages in improving students’overall quality and cultivating talents with global perspectives and local sentiments.Innovatively,this study bridges traditional cultural ecological wisdom and STEAM education with“unity of knowledge and action,”offering new insights for educational reform.展开更多
Wang Yangming disagreed with the Cheng-Zhu School's idea of knowledge before action and instead proposed the theory of the unity of knowledge and action.By answering three questions--why did Wang come up with such...Wang Yangming disagreed with the Cheng-Zhu School's idea of knowledge before action and instead proposed the theory of the unity of knowledge and action.By answering three questions--why did Wang come up with such theory,what is knowledge and what is action,and what is the unity of knowledge and action--this article will conclude that Wang's theory significantly affects our understanding of how to construct morality.First,it denies that the heart can hide any trace of non-good,and thus assures the goodness of the motivation of moral practice.Second,on a theoretical level,it refutes the possible obstacles to moral practice suggested by the ideas to know is easy while to act is difficult and knowledge before action.Wang emphasizes the inevitable unity of moral action,practice,and moral knowledge,and thus deepens the Confucian ethical theory that has always put more emphasis on practice.展开更多
To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user...To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.展开更多
This paper conducts a systematic analysis of the pathways for integrating excellent traditional culture into ideological and political education in higher education institutions,exploring four dimensions:incorporating...This paper conducts a systematic analysis of the pathways for integrating excellent traditional culture into ideological and political education in higher education institutions,exploring four dimensions:incorporating classical content into the curriculum system,enhancing teachers’cultural literacy,implementing practice-oriented teaching that integrates knowledge and action,and fostering a campus cultural environment conducive to such integration.The study proposes a“three-tier screening-multi-dimensional integration-dynamic update”mechanism for textbook integration,a“theoretical foundation-practical refinement-reflective enhancement”model for teacher development,a“goal-oriented-activity design-effect evaluation”system for practical teaching,and a“spatial renovation-activity planning-digital empowerment”strategy for cultural environment creation.By establishing a systematic operational process and a closed-loop training mechanism,the integration of traditional culture and ideological and political education is achieved,effectively enhancing the cultural depth and educational effectiveness of ideological and political teaching,and laying a solid foundation for universities to fulfill their fundamental mission of cultivating virtue and fostering talent.展开更多
Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the result...Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the resulting models. How- ever, in many applications such as advertisement, recommen- dation systems, social networks, customer relationship man- agement, and clinical prediction, the users need not only ac- curate prediction, but also suggestions on actions to achieve a desirable goal （e.g., high ads hit rates） or avert an unde- sirable predicted result （e.g., clinical deterioration）. Existing works for extracting such actionability are few and limited to simple models such as a decision tree. The dilemma is that those models with high accuracy are often more complex and harder to extract actionability from. In this paper, we propose an effective method to extract ac- tionable knowledge from additive tree models （ATMs）, one of the most widely used and best off-the-shelf classifiers. We rigorously formulate the optimal actionable planning （OAP） problem for a given ATM, which is to extract an action- able plan for a given input so that it can achieve a desirable output while maximizing the net profit. Based on a state space graph formulation, we first propose an optimal heuris- tic search method which intends to find an optimal solution. Then, we also present a sub-optimal heuristic search with an admissible and consistent heuristic function which can re- markably improve the efficiency of the algorithm. Our exper- imental results demonstrate the effectiveness and efficiency of the proposed algorithms on several real datasets in the application domain of personal credit and banking.展开更多
A main focus of machine learning research has been improving the generalization accuracy and efficiency of prediction models. However, what emerges as missing in many applications is actionability, i.e., the ability t...A main focus of machine learning research has been improving the generalization accuracy and efficiency of prediction models. However, what emerges as missing in many applications is actionability, i.e., the ability to turn prediction results into actions. Existing effort in deriving such actionable knowledge is few and limited to simple action models while in many real applications those models are often more complex and harder to extract an optimal solution. In this paper, we propose a novel approach that achieves actionability by combining learning with planning, two core areas of AI. In particular, we propose a framework to extract actionable knowledge from random forest, one of the most widely used and best off-the-shelf classifiers. We formulate the actionability problem to a sub-optimal action planning （SOAP） problem, which is to find a plan to alter certain features of a given input so that the random forest would yield a desirable output, while minimizing the total costs of actions. Technically, the SOAP problem is formulated in the SAS＋ planning formalism, and solved using a Max-SAT based ap- proach. Our experimental results demonstrate the effectiveness and efficiency of the proposed approach on a personal credit dataset and other benchmarks. Our work represents a new application of automated planning on an emerging and challenging machine learning paradigm.展开更多
Cyclone Idai in Zimbabwe exposed deficiencies in the country's disaster management system.This study uses a phenomenological case exploration of the experiences of local residents in Rusitu Valley following cyclon...Cyclone Idai in Zimbabwe exposed deficiencies in the country's disaster management system.This study uses a phenomenological case exploration of the experiences of local residents in Rusitu Valley following cyclone-induced floods that affected the area in March 2019.Through capturing narratives of participants who were recruited through chain referrals,the research intends to understand how local actors,utilizing their local-based response systems,managed to fill in the voids that characterize disaster management practice in Zimbabwe.Results show that the participation of local"heroes"and"Samaritans,"by deploying their social networks,norms,relationships,practices,and modest ingenuity,helped to speed up response times and minimize threats to lives and livelihoods.Documentation of the stories of local actors about their disaster experiences also gives a richer picture of the Cyclone Idai disaster.Although the community response system also facilitated the operation of external disaster management agencies,their premature withdrawal tended to weaken the trust and values existing in the area,and created tensions between the disaster-affected people and other villagers.Given the delays in formal responses by the government and other external relief agencies,the practices of local actors,although spontaneous and largely uncoordinated,offer rich insights into the design and development of disaster management regimes.展开更多
基金Interim Research Findings of the 2024 Major Project on Jiayou Culture Construction at Minzu Normal University of Xingyi:“Igniting the Flame of Motivation in the Intelligent Era:An Interdisciplinary Research Integrating Jiaoyou Culture with Artificial Intelligence Technology”(Project No.24JYZDA01)Guizhou Provincial Philosophy and Social Science Innovation Team:Xingyi Normal University for Nationalities’Research on Ecological Education System under the Grand Ecological Strategy(Project No.CXTD2023075):Interim Research Achievement.
文摘This study constructs a theoretical model integrating traditional cultural ecological wisdom into STEAM education,exploring a new interpretation of the“unity of knowledge and action”concept in modern education.Research shows that incorporating traditional ecological wisdom,such as the harmony between humanity and nature and following the laws of nature,into STEAM education’s curriculum,teaching methods,and practical activities can significantly enhance students’interdisciplinary knowledge,practical abilities,and environmental awareness.Through data simulation and empirical analysis,the model’s effectiveness is confirmed,demonstrating its significant advantages in improving students’overall quality and cultivating talents with global perspectives and local sentiments.Innovatively,this study bridges traditional cultural ecological wisdom and STEAM education with“unity of knowledge and action,”offering new insights for educational reform.
文摘Wang Yangming disagreed with the Cheng-Zhu School's idea of knowledge before action and instead proposed the theory of the unity of knowledge and action.By answering three questions--why did Wang come up with such theory,what is knowledge and what is action,and what is the unity of knowledge and action--this article will conclude that Wang's theory significantly affects our understanding of how to construct morality.First,it denies that the heart can hide any trace of non-good,and thus assures the goodness of the motivation of moral practice.Second,on a theoretical level,it refutes the possible obstacles to moral practice suggested by the ideas to know is easy while to act is difficult and knowledge before action.Wang emphasizes the inevitable unity of moral action,practice,and moral knowledge,and thus deepens the Confucian ethical theory that has always put more emphasis on practice.
基金Supported by the National Natural Science Foundation of China(51375049)National Defense Basic Scientific Research(A222011A222013)
文摘To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.
文摘This paper conducts a systematic analysis of the pathways for integrating excellent traditional culture into ideological and political education in higher education institutions,exploring four dimensions:incorporating classical content into the curriculum system,enhancing teachers’cultural literacy,implementing practice-oriented teaching that integrates knowledge and action,and fostering a campus cultural environment conducive to such integration.The study proposes a“three-tier screening-multi-dimensional integration-dynamic update”mechanism for textbook integration,a“theoretical foundation-practical refinement-reflective enhancement”model for teacher development,a“goal-oriented-activity design-effect evaluation”system for practical teaching,and a“spatial renovation-activity planning-digital empowerment”strategy for cultural environment creation.By establishing a systematic operational process and a closed-loop training mechanism,the integration of traditional culture and ideological and political education is achieved,effectively enhancing the cultural depth and educational effectiveness of ideological and political teaching,and laying a solid foundation for universities to fulfill their fundamental mission of cultivating virtue and fostering talent.
基金This work was supported in part by China Postdoctoral Science Foundation （2013M531527）, the Fundamental Research Funds for the Central Universities （0110000037）, the National Natural Science Foun- dation of China （Grant Nos. 61502412, 61033009, and 61175057）, Natural Science Foundation of the Jiangsu Province （BK20150459）, Natural Science Foundation of the Jiangsu Higher Education Institutions （15KJB520036）, National Science Foundation, United States （IIS-0534699, IIS-0713109, CNS-1017701）, and a Microsoft Research New Faculty Fellowship.
文摘Although amazing progress has been made in ma- chine learning to achieve high generalization accuracy and ef- ficiency, there is still very limited work on deriving meaning- ful decision-making actions from the resulting models. How- ever, in many applications such as advertisement, recommen- dation systems, social networks, customer relationship man- agement, and clinical prediction, the users need not only ac- curate prediction, but also suggestions on actions to achieve a desirable goal （e.g., high ads hit rates） or avert an unde- sirable predicted result （e.g., clinical deterioration）. Existing works for extracting such actionability are few and limited to simple models such as a decision tree. The dilemma is that those models with high accuracy are often more complex and harder to extract actionability from. In this paper, we propose an effective method to extract ac- tionable knowledge from additive tree models （ATMs）, one of the most widely used and best off-the-shelf classifiers. We rigorously formulate the optimal actionable planning （OAP） problem for a given ATM, which is to extract an action- able plan for a given input so that it can achieve a desirable output while maximizing the net profit. Based on a state space graph formulation, we first propose an optimal heuris- tic search method which intends to find an optimal solution. Then, we also present a sub-optimal heuristic search with an admissible and consistent heuristic function which can re- markably improve the efficiency of the algorithm. Our exper- imental results demonstrate the effectiveness and efficiency of the proposed algorithms on several real datasets in the application domain of personal credit and banking.
基金This work was supported in part by the National Natural Science Foundation of China （Grant Nos. 61502412, 61379066, and 61402395）, Natural Science Foundation of the Jiangsu Province （BK20150459, BK20151314, and BK20140492）, Natural Science Foundation of the Jiangsu Higher Education Institutions （15KJB520036）, United States NSF grants （IIS-0534699, IIS-0713109, CNS-1017701）, Microsoft Research New Faculty Fellowship, and the Research Innovation Program for Graduate Student in Jiangsu Province （KYLX16 1390）.
文摘A main focus of machine learning research has been improving the generalization accuracy and efficiency of prediction models. However, what emerges as missing in many applications is actionability, i.e., the ability to turn prediction results into actions. Existing effort in deriving such actionable knowledge is few and limited to simple action models while in many real applications those models are often more complex and harder to extract an optimal solution. In this paper, we propose a novel approach that achieves actionability by combining learning with planning, two core areas of AI. In particular, we propose a framework to extract actionable knowledge from random forest, one of the most widely used and best off-the-shelf classifiers. We formulate the actionability problem to a sub-optimal action planning （SOAP） problem, which is to find a plan to alter certain features of a given input so that the random forest would yield a desirable output, while minimizing the total costs of actions. Technically, the SOAP problem is formulated in the SAS＋ planning formalism, and solved using a Max-SAT based ap- proach. Our experimental results demonstrate the effectiveness and efficiency of the proposed approach on a personal credit dataset and other benchmarks. Our work represents a new application of automated planning on an emerging and challenging machine learning paradigm.
文摘Cyclone Idai in Zimbabwe exposed deficiencies in the country's disaster management system.This study uses a phenomenological case exploration of the experiences of local residents in Rusitu Valley following cyclone-induced floods that affected the area in March 2019.Through capturing narratives of participants who were recruited through chain referrals,the research intends to understand how local actors,utilizing their local-based response systems,managed to fill in the voids that characterize disaster management practice in Zimbabwe.Results show that the participation of local"heroes"and"Samaritans,"by deploying their social networks,norms,relationships,practices,and modest ingenuity,helped to speed up response times and minimize threats to lives and livelihoods.Documentation of the stories of local actors about their disaster experiences also gives a richer picture of the Cyclone Idai disaster.Although the community response system also facilitated the operation of external disaster management agencies,their premature withdrawal tended to weaken the trust and values existing in the area,and created tensions between the disaster-affected people and other villagers.Given the delays in formal responses by the government and other external relief agencies,the practices of local actors,although spontaneous and largely uncoordinated,offer rich insights into the design and development of disaster management regimes.
