Analysis of community question-answering issues via machine learning and deep learning:State-of-the-art review

Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.

LC-NPLA: Label and Community Information-Based Network Presentation Learning Algorithm

Many network presentation learning algorithms(NPLA)have originated from the process of the random walk between nodes in recent years.Despite these algorithms can obtain great embedding results,there may be also some limitations.For instance,only the structural information of nodes is considered when these kinds of algorithms are constructed.Aiming at this issue,a label and community information-based network presentation learning algorithm(LC-NPLA)is proposed in this paper.First of all,by using the community information and the label information of nodes,the first-order neighbors of nodes are reconstructed.In the next,the random walk strategy is improved by integrating the degree information and label information of nodes.Then,the node sequence obtained from random walk sampling is transformed into the node representation vector by the Skip-Gram model.At last,the experimental results on ten real-world networks demonstrate that the proposed algorithm has great advantages in the label classification,network reconstruction and link prediction tasks,compared with three benchmark algorithms.

The Practical Path to Cultivating Innovative Talents:Implementing Cross-Disciplinary Learning Communities in Environmental Design Education

In response to the national strategy of“vigorously cultivating interdisciplinary talents and actively promoting interdisciplinary integration,”this article focuses on the nationally recognized Environmental Design program at Hezhou University’s College of Design,leveraging local industry advantages to engage in interdisciplinary integration through educational practices.Using the“Construction of the Panoramic Virtual Nature Museum of the Guizhou Crocodile Lizard at Mount Dagui”as a case study,we aim to establish a professional and interdisciplinary learning community,incorporate student-centered interactive teaching methods,boost student motivation,enhance teaching quality,nurture forward-thinking versatile innovative talents,and provide a guideline for interdisciplinary educational reform.

从学习社区到学习共同体——教育技术学领域中的“learning community”辨析

"社区"一词在汉语中侧重于"地域性",而教育技术学领域中的"learning community"更强调"共同归属感",翻译为"学习共同体"更为合适。"学习共同体"应具备"活动场"、"一定数量固定的人群与频繁的互动"、"共同的社会心理基础"三个基本要素,根据不同的标准可以分为多种不同类型。

Learning Community视阈下地方师范院校教师资源整合

在对Learning Community介绍的基础上,分析了其在中国实现的可能性,在LearningCommunity视阈下,以创新的专门用途英语教学实现专业教师和外语教师的教师和教学资源整合为例,探讨地方师范院校教师资源整合。

An Introduction to Learning Community

Learning community, a theory that has gained popularity in the USA and many European countries over the past twenty years, has made a tremendous influence upon each aspect of education. There is no universal definition of it, but there is a general consensus that learning community develops through the cooperative efforts of the group members within the environment that al - lows all the members to achieve shared goals. Learning is not merely based on individual's efforts, but mainly on the collective ex- periences of learning community.

Applying Learning Community Theory to Oral English Teaching in Sport Institutes

Since traditional English teaching method, which merely focuses on language teaching but ignores communicative competence, severely impedes the development of students' oral ability. It is high time that English teachers took measures to find a workable and valuable teaching method which can improve students' speaking proficiency effectively. Learning community theory provides a broad space for this, for it regards learning as a process which takes place in a community where the learners are sharing their experience towards knowledge building in an interactive and cooperative way.

Delineation of an Urban Community Life Circle Based on a Machine-Learning Estimation of Spatiotemporal Behavioral Demand

Delineating life circles is an essential prerequisite for urban community life circle planning. Recent studies combined the environmental contexts with residents’ global positioning system(GPS) data to delineate the life circles. This method, however, is constrained by GPS data, and it can only be applied in the GPS surveyed communities. To address this limitation, this study developed a generalizable delineation method without the constraint of behavioral data. According to previous research, the community life circle consists of the walking-accessible range and internal structure. The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle, as the range can be delineated primarily based on environmental data. Therefore, behavioral demand estimation models were established through logistic regression and machine learning techniques, including decision trees and ensemble learning. The model with the lowest error rate was chosen as the final estimation model for each type of land. Finally, we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method. This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models, which learn the relationships between environmental contexts, population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data. Furthermore, the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning, and activity space estimation of the population in evaluating and improving the urban policies.

Topic Sentiment Analysis in Online Learning Community from College Students

Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To improve the accuracy of topic-sentiment analysis,a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.Methodology/approach:We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularitylevels.The proposed method comprised data preprocessing,topic detection,sentiment analysis,and visualization.Findings:The proposed model can effectively perceive students’sentiment tendencies on different topics,which provides powerful practical reference for improving the quality of information services in teaching practice.Research limitations:The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach,without considering the intensity of students’sentiments and their evolutionary trends.Practical implications:The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint,which can be utilized as a reference for enhancing the accuracy of learning content recommendation,and evaluating the quality of their services.Originality/value:The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics,which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses.

Improved Density Peaking Algorithm for Community Detection Based on Graph Representation Learning

There is a large amount of information in the network data that we canexploit. It is difficult for classical community detection algorithms to handle network data with sparse topology. Representation learning of network data is usually paired with clustering algorithms to solve the community detection problem.Meanwhile, there is always an unpredictable distribution of class clusters outputby graph representation learning. Therefore, we propose an improved densitypeak clustering algorithm (ILDPC) for the community detection problem, whichimproves the local density mechanism in the original algorithm and can betteraccommodate class clusters of different shapes. And we study the communitydetection in network data. The algorithm is paired with the benchmark modelGraph sample and aggregate (GraphSAGE) to show the adaptability of ILDPCfor community detection. The plotted decision diagram shows that the ILDPCalgorithm is more discriminative in selecting density peak points compared tothe original algorithm. Finally, the performance of K-means and other clusteringalgorithms on this benchmark model is compared, and the algorithm is proved tobe more suitable for community detection in sparse networks with the benchmarkmodel on the evaluation criterion F1-score. The sensitivity of the parameters ofthe ILDPC algorithm to the low-dimensional vector set output by the benchmarkmodel GraphSAGE is also analyzed.

Professional Learning Communities(PLCs)of Chemistry Teachers

The models of Professional Learning Communities(PLCs)are based on principles of learning that emphasize the co-construction of knowledge by learners,who in this case are the teachers themselves.Teachers in a PLC meet regularly to explore their practices and the learning outcomes of their students,analyze their teaching and their students’learning processes,draw conclusions,and make changes in order to improve their teaching and the learning of their students.It was found that participation in a PLC influences teaching practice,so teachers become more student-centered.Moreover,the teaching culture improves as the community increases the degree of cooperation among teachers,and focuses on the processes of learning rather than the accumulation of knowledge.This enables students to be innovative,creative,and critical.In addition,trust is developed among the participants,which enables them to discuss and analyze their students’cognitive and affective problems,misconceptions,and learning outcomes.

Service Learning at National Taipei College of Business, 2012-2013＂ New Perspectives on Community, Peer-Based Education

Service learning （also known as peer learning） has received increased attention in tertiary education. By linking learning with authentic volunteer work experience, service learning bridges the gap between theoretical study and practical reality. This practice can increase students＇ professional knowledge, educational development, self-esteem, and awareness of social responsibility. Service learning became a mandatory requirement for all students at National Taipei College of Business （NTCB; now National Taipei University of Business） in 2011, and this is the focus of this study, extending into the 2012 school year. This course-based program allows undergraduate language majors to put their language skills into practice by teaching peers, and also through other volunteer work. This program has greatly benefitted undergraduate students at the school. This study will examine course data, student reports, and interviews with student teachers. The researchers have documented the implementation of the peer-mentor program at NTCB, and the learning gains experienced among students and the professors who assisted in these processes.

Autonomous Development Strategies for College English Teachers in a Mixed-mode Learning Community

At present,the improvement of the quality of higher education and the improvement of the professional ability and comprehensive quality of college students all depend on the education level and discipline professional ability of teachers in colleges and universities.In the new era of educational reform and development,university teachers also need to continuously learn and progress in order to adapt to changes in the educational environment and the update of the knowledge system.Nowadays,the construction and development of the mixed-mode learning community environment is becoming one of the effective ways for college teachers to improve their learning.From the perspective of the significance of autonomous development of college English teachers in the context of mixed-mode learning community,the current situation and other issues,this article expounds the strategies that promote the autonomous development of college English teachers in the context of mixed-mode learning community to improve the professional quality of college English teachers.

Research on Application of Data Mining in Virtual Community of Foreign Language Learning

The construction of virtual community in foreign language learning is a comprehensive foreign language learning environment integrated with foreign language vocabulary database construction and vocabulary retrieval, combining the virtual reality technology to construct the language environment of foreign language learning. The virtual community of foreign language leaming can improve the sense of language authenticity in foreign language learning and improve the quality of foreign language teaching. A method of building a virtual community for foreign language learning is proposed based on data mining technology, data acquisition and feature preprocessing model for building semantic vocabulary of foreign language learning is constructed, the linguistic environment characteristics of the semantic vocabulary data of foreign language learning is analyzed, and the semantic noumenon structure model is obtained. Fuzzy clustering method is used for vocabulary clustering and comprehensive retrieval in the virtual community of foreign language learning, the performance of vocabulary classification in foreign language learning is improved, the adaptive semantic information fusion method is used to realize the vocabulary data mining in the virtual community of foreign language learning, information retrieval and access scheduling for virtual communities in foreign language learning are realized based on data mining results. The simulation results show that the accuracy of foreign language vocabulary retrieval is good, improve the efficiency of foreign language learning.

Integrating WeChat-based Autonomous Learning Community into Improving Speaking--An Action Research Study in EFL

The purpose of this paper is to share the findings of an action research aiming at helping college students to improve their speaking by applying a WeChat-based autonomous learning community.WeChat is the most wide-spread social media platform in China.In this 10-week action research,a total of 16 participants in a Chinese university were involved.After identifying the incentive of participating in this WeChat Group speaking activity,most of which were related with pronunciation and a lack of speaking fluency practice,an action plan was developed and implemented.In this WeChat group,the participants received weekly learning material about pronunciation and speaking assignments accordingly,then they had one week to learn the pronunciation independently and prepare the oral assignments.Following this,participants submitted their voice recording in the WeChat group and were given feedback by an instructor in this group.Observations,questionnaires,and surveys were used to collect data.The results show a positive feedback from the learners on a WeChat-based autonomous learning community.The study observes(1)college EFL learners have a strong motivation;intrinsic motivation especially has a positive relationship with participants’performance;(2)students have a positive attitude towards WeChat-based autonomous learning community;(3)timely feedback from instructors is highly valued by language learners.

Conversing in Spanish at a Seniors Center： A Brief Experience of Community-Based and Foreign-Language Learning

This pilot study explored the linguistic gains of intermediate level Spanish learners who completed community-based learning at a Spanish-speaking seniors center. Leamers had the opportunity, rare in foreign-language instruction, to discuss topics from their textbook in authentic native/non-native dyads. The interactions also allowed the seniors to fulfill an identified community needed by socializing in Spanish. Analyses of a post-service survey revealed that learners assessed the experience positively, because they spoke Spanish creatively. Seniors were described as cooperative and fun interlocutors, suggesting that age difference minimally affected the interactions. Direct observation revealed that learners managed to produce L2 Spanish output in connected speech for an extended period of time. Likewise, the seniors enjoyed a moment of socialization and first language use while sharing their views on the topics of discussion with the young visitors. Seniors＇ active participation likely encouraged learners to cope with sudden switches of topics that required negotiating for meaning and pushing the still limited interlanguages. A new service leaming study proposes to investigate the use of native/non-native dyads in Spanish in fulfilling a dual function： socialization and first language maintenance for the seniors at the center and language learning for the students.

Innovation in Adult Language Learning Programs: A Case Study of "Livemocha" Online Language Learning Community

Due to the increasing broadband Internet access, VOIP adoption as well as the Web 2.0 concepts, online language learning communities have gained great popularity among adult language learners. Based upon Malcolm Knowles' adult learning theory, this paper analyzes the innovation that online language learning communities have brought to adult language learning programs. At the same time, the limitations of such programs have been pointed out.

How English Virtual Learning Community Extending Communication Interaction

This thesis is based on English Virtual Learning Community playing a role in sharing information.Virtual Learning Community may help build up communication interaction and exploring online relations.The thesis is a focus on expressing identity in English Virtual Learning Community.

Developments of Professional Learning Communities and Challenges for Principals in Chinese Urban Middle Schools

Professional learning communities(PLCs)have seen a rapid spread all around the world over the past 30 years.Since then it has been proved that they can improve teaching quality and thereby the achievement of students,and so PLCs have attracted increasing attention especially from education systems.In China,PLCs have been developed vigorously within schools since the implementation of the‘New Curriculum Reform’in 2000.However,the west has paid scant attention to and were not familiar with them since most research in this field in China was published in Chinese.Furthermore,PLCs are influenced by contextual and cultural factors,and therefore PLCs in Chinese education systems are different from those in Anglo-American settings due to long-standing cultural differences,which require consideration.Therefore,this research will investigate the PLCs in China that may be of interest.Many recent studies have shown that,although PLCs have made significant progress in Chinese urban middle schools through the enthusiastic efforts of educators and scholars,there are still several barriers.The primary purpose of this research is to review the development of PLCs and additionally to analyse the challenges faced by the principals.

Visual evaluation of graph representation learning based on the presentation of community structures

Various graph representation learning models convert graph nodes into vectors using techniques like matrix factorization,random walk,and deep learning.However,choosing the right method for different tasks can be challenging.Communities within networks help reveal underlying structures and correlations.Investigating how different models preserve community properties is crucial for identifying the best graph representation for data analysis.This paper defines indicators to explore the perceptual quality of community properties in representation learning spaces,including the consistency of community structure,node distribution within and between communities,and central node distribution.A visualization system presents these indicators,allowing users to evaluate models based on community structures.Case studies demonstrate the effectiveness of the indicators for the visual evaluation of graph representation learning models.