Brief Overview of Intelligent Education

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.

Social Intelligence in Education: A Mediator Analysis of Attitude

This article reports on a study of social intelligence in education.Authors surveyed approximately 1,188 students in the north of Vietnam to assess levels of social intelligence in education including awareness,attitude,and skills.Independent variables included region and the gender of students.Although there are no region and gender differences in social intelligence,correlations and mediating relationships are found.

Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for LatentSkill Discovering

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.

AIGC Scenario Analysis and Research on Technology Roadmap of Internet Industry Application

The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications.On the technical line,the cross-modal AI generation application based on human feedback system is accelerated.In the business model,the scenes to realize interactive functions are constantly enriched.This paper reviews the evolution process of AIGC,closely follows the current situation of the coexistence of business acceleration and technical worries in the application of artificial intelligence education,analyzes the application of AIGC education in 7 subdivided fields,and analyzes the optimization direction of application cases from the perspective of perception-cognition-creation technology maturity matrix.The 3 recommendations and 2 follow-up research directions will promote the scientific application of artificial intelligence education in the AIGC period.

5G and Smart Education:Educational Reform Based on Intelligent Technology

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.

A Study on Human-Computer Interaction Mechanism in an Intelligent Tutoring System

Discussion is a common and important learning process.Involvement of a virtual agent can provide adaptive support for the discussion process.Argumen-tative knowledge construction is beneficial to learners’acquisition of knowledge,but the effectiveness of argumentative scaffolding in existing studies is not consistent.Based on an intelligent discussion system,a total of 47 undergraduate students took part in the experiment and they were assigned to three different conditions:content-related plus content-independent scaffolding condition,content-related scaffolding condition,and the control condition.Under the content-related and content-independent scaffolding condition,the computer agent provided an idea from semantically different categories(content-related scaffolding)according to the automatic categorization of the current contributions,and further inquired the participants about their attitudes and reasons(content-independent scaffolding).Under the condition of content-related scaffolding condition,the virtual agent only provided semantically different viewpoints.Under the control condition,the subjects expressed their opinion independently without the participation of the virtual agent.Findings revealed that compared with the control group,when the virtual agent provided semantically different ideas(content-related scaffolding),the discussion breadth(number of categories)was improved and the subjects felt that they had a more comprehensive understanding of the problem.Compared with the content-related scaffolding condition,when the virtual agent provided semantically different ideas and further asked about the attitudes and reasons,the subjects expressed more agreement with these views,but mentioned fewer categories during the discussion.This study suggests that the content-related scaffolding can facilitate the cognitive processing effect relevant to the topic of discussion.When the content independent scaffolding is added,it can promote the argumentative processing,but may have a negative effect on the cognitive processing related to the topic discussed.

A Construction Method of Online Course Portrait Based on Feature Engineering

With the emergence of massive online courses,how to evaluate the quality of courses with different qualities to improve the discrimination between courses and recommend personalized online course learning resources for learners needs to be evaluated from all aspects.In this paper,a method of constructing an online course portrait based on feature engineering is proposed.Firstly,the framework of online course portrait is established,the related features of the portrait are extracted by feature engineering method,and then the indicator weights of the portrait are calculated by entropy weight method.Finally,experiments are designed to evaluate the performance of the algorithms,and an example of the course portrait is given.

The Effectiveness of Mobile-Assisted Language Learning(MALL)Applications on the Spoken English Assessments in China’s Universities

The increased ownership of mobile phone users and the advancement of mobile applications enlarge the practicality and popularity of use for learning purposes among Chinese university students.However,even if innovative functions of these applications are increasingly reported in relevant research in the education field,little research has been in the application of spoken English language.This paper examined the effect of using a Mobile-Assisted Language Learning(MALL)application“IELTS Liulishuo”(speaking English fluently in the IELTS test)as a unit of analysis to improve the English-speaking production of university students in China.The measurement of this mobile application in its effectiveness of validity and reliability is through the use of seven dimensional criteria.Although some technical and pedagogical issues challenge adoptions of MALL in some less-developed regions in China,the study showed positive effects of using a MALL oral English assessment application characterised with Automatic Speech Recognition(ASR)system on the improvement of complexity,accuracy,and fluency of English learners in China’s colleges.

Learning Behavior-Aware Cognitive Diagnosis for Online Education Systems

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.