Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students,which has attracted extensive attention from scholars at hom...Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students,which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress.To this end,we propose a noise-filtering enhanced deep cognitive diagno-sis method to improve the fitting ability of traditional models and obtain students’skill mastery status by mining the interaction between students and problems nonlinearly through neural networks.First,modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of the proposed model;second,the neural network is used to predict students’learning performance,diagnose students’skill mastery and provide immediate feedback;finally,by comparing the proposed model with several baseline models,extensive experimental results on real data sets demonstrate that the proposed Finally,by comparing the proposed model with several baseline models,the extensive experimental results on the actual data set demon-strate that the proposed model not only improves the accuracy of predicting students’learning performance but also enhances the interpretability of the neurocognitive diagnostic model.展开更多
Intelligent Education uses Al technology as a means in the education ecology to promote the automation and intelligence of education and teaching.It reshapes the education ecology,adding Al things to the traditional e...Intelligent Education uses Al technology as a means in the education ecology to promote the automation and intelligence of education and teaching.It reshapes the education ecology,adding Al things to the traditional education ecology that dominated by teachers and students.Although IE technology is widely used,there is little discussion about a comprehensive overview of IE.The goal and connotation of IE is discussed.Meanwhile,the emotional,ethical,Al technology as well as supervision and management perspectives in IE are discussed too.The core goal of IE is putted forward that is human-oriented and individualized development of students is.Finally,the education ecology with dual-teacher collaborative in intelligence education was proposed.展开更多
The 5G communication technology serving a wide range of vertical industries is maturing,which provides a possible boost for the development of smart education and lays a foundation for solving the principal contradict...The 5G communication technology serving a wide range of vertical industries is maturing,which provides a possible boost for the development of smart education and lays a foundation for solving the principal contradiction in current education.With the characteristics of ultra-high speed,low latency,low energy consumption,massive network capacity,and high reliability,the 5G technology is applied with other technologies like artificial intelligence(AI),internet of things(IoT),big data,and blockchain to promote the application upgrading of intelligent education technology.This paper analyzes the intelligent education technology and its eight typical applications in the 5G era,which include smart safe campus,integrated learning spaces,synchronous cyber classrooms,teachers’professional development,robot learning partners,mobile and ubiquitous learning,virtual simulation training,and smart e-textbooks.Then,it discusses how intelligent education technology promotes changes in the modes of learning and teaching in the 5G era from three dimensions:individual learning,collaborative group learning,and classroom-based collective teaching.At last,the framework of smart education in the 5G era is proposed from the perspectives of intelligent education technology and its typical applications,changes in learning and teaching,and the new ecosystem of smart education.展开更多
Cognitive diagnosis,which aims to diagnose students’knowledge proficiency,is crucial for numerous online education applications,such as personalized exercise recommendation.Existing methods in this area mainly exploi...Cognitive diagnosis,which aims to diagnose students’knowledge proficiency,is crucial for numerous online education applications,such as personalized exercise recommendation.Existing methods in this area mainly exploit students’exercising records,which ignores students’full learning process in online education systems.Besides,the latent relation of exercises with course structure and texts is still underexplored.In this paper,a learning behavior-aware cognitive diagnosis(LCD)framework is proposed for students’cognitive modeling with both learning behavior records and exercising records.The concept of LCD was first introduced to characterize students’knowledge proficiency more completely.Second,a course graph was designed to explore rich information existed in course texts and structures.Third,an interaction function was put forward to explore complex relationships between students,exercises and videos.Extensive experiments on a real-world dataset prove that LCD predicts student performance more effectively,the output of LCD is also interpretable.展开更多
Large language models(LLMs)have emerged as powerful tools in natural language processing(NLP),showing a promising future of artificial generated intelligence(AGI).Despite their notable performance in the general domai...Large language models(LLMs)have emerged as powerful tools in natural language processing(NLP),showing a promising future of artificial generated intelligence(AGI).Despite their notable performance in the general domain,LLMs have remained suboptimal in the field of education,owing to the unique challenges presented by this domain,such as the need for more specialized knowledge,the requirement for personalized learning experiences,and the necessity for concise explanations of complex concepts.To address these issues,this paper presents a novel LLM for education named WisdomBot,which combines the power of LLMs with educational theories,enabling their seamless integration into educational contexts.To be specific,we harness self-instructed knowledgeconceptsand instructions under the guidance of Bloom's Taxonomy as training data.To further enhance the accuracy and professionalism of model's response on factual questions,we introduce two key enhancements during inference,ie.,local knowledge base retrieval augmentation and search engine retrieval augmentation during inference.We substantiate the effectiveness of our approach by applying it to several Chinese LLMs,thereby showcasing that the fine-tuned models can generate more reliable and professional responses.展开更多
文摘Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students,which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress.To this end,we propose a noise-filtering enhanced deep cognitive diagno-sis method to improve the fitting ability of traditional models and obtain students’skill mastery status by mining the interaction between students and problems nonlinearly through neural networks.First,modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of the proposed model;second,the neural network is used to predict students’learning performance,diagnose students’skill mastery and provide immediate feedback;finally,by comparing the proposed model with several baseline models,extensive experimental results on real data sets demonstrate that the proposed Finally,by comparing the proposed model with several baseline models,the extensive experimental results on the actual data set demon-strate that the proposed model not only improves the accuracy of predicting students’learning performance but also enhances the interpretability of the neurocognitive diagnostic model.
基金This research was supported by the Chinese Ministry of Education-China Mobile Scientific Research Fund 2020 with the context of the MCM2020-4-2 project(Research on applications of the block-chain technology in education).
文摘Intelligent Education uses Al technology as a means in the education ecology to promote the automation and intelligence of education and teaching.It reshapes the education ecology,adding Al things to the traditional education ecology that dominated by teachers and students.Although IE technology is widely used,there is little discussion about a comprehensive overview of IE.The goal and connotation of IE is discussed.Meanwhile,the emotional,ethical,Al technology as well as supervision and management perspectives in IE are discussed too.The core goal of IE is putted forward that is human-oriented and individualized development of students is.Finally,the education ecology with dual-teacher collaborative in intelligence education was proposed.
基金supported by China National Social Sciences Key Project“Research on the Ethics and Limits of AI in Educution Scenarios”(No.ACA220027)the Ministry of Education’s“14th Five-Year Plan”Research Project“Research on New Opportunities and New Challenges for Education in the 5G Era”(No.SSW202018).
文摘The 5G communication technology serving a wide range of vertical industries is maturing,which provides a possible boost for the development of smart education and lays a foundation for solving the principal contradiction in current education.With the characteristics of ultra-high speed,low latency,low energy consumption,massive network capacity,and high reliability,the 5G technology is applied with other technologies like artificial intelligence(AI),internet of things(IoT),big data,and blockchain to promote the application upgrading of intelligent education technology.This paper analyzes the intelligent education technology and its eight typical applications in the 5G era,which include smart safe campus,integrated learning spaces,synchronous cyber classrooms,teachers’professional development,robot learning partners,mobile and ubiquitous learning,virtual simulation training,and smart e-textbooks.Then,it discusses how intelligent education technology promotes changes in the modes of learning and teaching in the 5G era from three dimensions:individual learning,collaborative group learning,and classroom-based collective teaching.At last,the framework of smart education in the 5G era is proposed from the perspectives of intelligent education technology and its typical applications,changes in learning and teaching,and the new ecosystem of smart education.
基金This work is supported by the National Key Research and Development Program of China(2018YFB1005100)It also got partial support from National Engineering Laboratory for Cyberlearning and Intelligent Technology,and Beijing Key Lab of Networked Multimedia.
文摘Cognitive diagnosis,which aims to diagnose students’knowledge proficiency,is crucial for numerous online education applications,such as personalized exercise recommendation.Existing methods in this area mainly exploit students’exercising records,which ignores students’full learning process in online education systems.Besides,the latent relation of exercises with course structure and texts is still underexplored.In this paper,a learning behavior-aware cognitive diagnosis(LCD)framework is proposed for students’cognitive modeling with both learning behavior records and exercising records.The concept of LCD was first introduced to characterize students’knowledge proficiency more completely.Second,a course graph was designed to explore rich information existed in course texts and structures.Third,an interaction function was put forward to explore complex relationships between students,exercises and videos.Extensive experiments on a real-world dataset prove that LCD predicts student performance more effectively,the output of LCD is also interpretable.
基金supported by the National Science and Technology Major Project,China(Grant No.2022ZD0117104)the National Natural Science Foundation of China(Grant Nos.62037001 and 62307032)the Starry Night Science Fund at Shanghai Institute for Advanced Study(SN-ZJU-SIAS-0010).
文摘Large language models(LLMs)have emerged as powerful tools in natural language processing(NLP),showing a promising future of artificial generated intelligence(AGI).Despite their notable performance in the general domain,LLMs have remained suboptimal in the field of education,owing to the unique challenges presented by this domain,such as the need for more specialized knowledge,the requirement for personalized learning experiences,and the necessity for concise explanations of complex concepts.To address these issues,this paper presents a novel LLM for education named WisdomBot,which combines the power of LLMs with educational theories,enabling their seamless integration into educational contexts.To be specific,we harness self-instructed knowledgeconceptsand instructions under the guidance of Bloom's Taxonomy as training data.To further enhance the accuracy and professionalism of model's response on factual questions,we introduce two key enhancements during inference,ie.,local knowledge base retrieval augmentation and search engine retrieval augmentation during inference.We substantiate the effectiveness of our approach by applying it to several Chinese LLMs,thereby showcasing that the fine-tuned models can generate more reliable and professional responses.