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.

The Influence of Parent-Child Relationship on Pupils’ Learning Motivation: The Mediating Role of Teacher-Student Relationship

Objective:The study is to analyze the influence of parent-child relationship on pupils’learning motivation,and to explore the mediating mechanism of teacher-student relationship in parent-child relationship and learning motivation.Method:This study conducted a questionnaire survey on 213 pupils in Grades 5 and 6 in two schools in Beijing using Pianta’s teacher-student relationship scale revised by Qu,Dornbush’s parent-child intimacy scale revised by Zhang and the learning motivation scale adapted by Hu.Results:Gender,grade,whether they are the only child and to be a class cadre or not show significant differences in some dimensions of parent-child relationship,teacher-student relationship and learning motivation.The total scores of parent-child relationship,teacher-student relationship and learning motivation are positively correlated,and some sub dimensions are also significantly correlated.Parent-child relationship and teacher-student relationship have a significant positive predictive effect on learning motivation,and parent-child relationship has a significant positive predictive effect on teacher-student relationship.Teacher-student relationship plays a mediating role in the influence of parent-child relationship on learning motivation.Conclusions:Parent-child relationship can promote the relationship between teachers and students,and then enhance pupils’learning motivation.

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.

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.

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.

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.

Expert Recommendation in Community Question Answering via Heterogeneous Content Network Embedding

ExpertRecommendation(ER)aims to identify domain experts with high expertise and willingness to provide answers to questions in Community Question Answering(CQA)web services.How to model questions and users in the heterogeneous content network is critical to this task.Most traditional methods focus on modeling questions and users based on the textual content left in the community while ignoring the structural properties of heterogeneous CQA networks and always suffering from textual data sparsity issues.Recent approaches take advantage of structural proximities between nodes and attempt to fuse the textual content of nodes for modeling.However,they often fail to distinguish the nodes’personalized preferences and only consider the textual content of a part of the nodes in network embedding learning,while ignoring the semantic relevance of nodes.In this paper,we propose a novel framework that jointly considers the structural proximity relations and textual semantic relevance to model users and questions more comprehensively.Specifically,we learn topology-based embeddings through a hierarchical attentive network learning strategy,in which the proximity information and the personalized preference of nodes are encoded and preserved.Meanwhile,we utilize the node’s textual content and the text correlation between adjacent nodes to build the content-based embedding through a meta-context-aware skip-gram model.In addition,the user’s relative answer quality is incorporated to promote the ranking performance.Experimental results show that our proposed framework consistently and significantly outperforms the state-of-the-art baselines on three real-world datasets by taking the deep semantic understanding and structural feature learning together.The performance of the proposed work is analyzed in terms of MRR,P@K,and MAP and is proven to be more advanced than the existing methodologies.

Use of Social Networks to Affect the Teaching and Learning Effectiveness of 3D Design

In recent years, with the rapid development of technologies, information technological software and social networks have been widely accepted. Therefore, social networks can be integrated with information technologies for teaching purposes. In addition, the sharing of learning outcomes via social networks can improve students’ learning effectiveness. This study used an information technology teaching environment to teach students 3D skills, and used 3D SketchUp to enable students to explore, operate, and complete their personal works by themselves. Moreover, this study used Facebook as the media of a WBI (web-based instruction) community, and used the discussions and sharing between students and students, and students and teachers, to improve learning effectiveness and reduce learning disabilities. The research results showed that, proper use of social networks to provide students with opportunities to discuss and share outcomes can help improve students’ learning effectiveness and reduce learning disabilities.

Professional Learning Communities in Private Schools in Bahrain and Oman:Reflection on Two Cases

Highlights•This study explores features of professional learning community(PLC)models in the educational contexts in Bahrain and Oman.•Findings based on the case studies of PLCs in two private schools in Bahrain and Oman,and theoretical input from international PLC literature has implications for policy and practice.•Study recommends promoting PLC approaches in the Bahraini and Omani educational systems in pre-and in-service teacher training programs,adapting best international PLC practices to the specific educational contexts of Bahrain and Oman,preparing school principals to lead PLC in their schools,providing human and financial support to these communities,and making school cultures more collaborative.•This study highlights the importance of the PLC approach,expands the existing conceptual/analytical framework,demonstrates how this approach is being used in two schools,and encourages other practitioners and researchers to embrace PLC.