作者机构：
[Chen, Zijian; Zhu, Xiaoliang] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Chen, Zijian] Guizhou Univ Finance & Econ, Sch Informat, Guiyang, Peoples R China.
通讯机构：
[Chen, Zijian] C;[Chen, Zijian] G;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;Guizhou Univ Finance & Econ, Sch Informat, Guiyang, Peoples R China.
作者机构：
[Yang, Jiumin; Xu, Ke; Pi, Zhongling] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Liu, Caixia] Cent China Normal Univ, Collaborat Innovat Ctr Informat Technol & Balance, Wuhan 430079, Hubei, Peoples R China.;[Yang, Jiumin] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Yang, Jiumin] Cent China Normal Univ, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Yang, Jiumin] C;Cent China Normal Univ, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.
摘要：
Purpose Social coding platforms (SCPs) have been adopted by scores of developers in building, testing and managing their codes collaboratively. Accordingly, this type of platform (site) enables collaboration between enterprises and universities (c-EU) at a lower cost in the form of online team-building projects (repositories). This paper investigates the open collaboration patterns between these two parties on GitHub by measuring their online behaviours. The purpose of this investigation is to identify the most attractive collaboration features that enterprises can offer to increase university students' participation intentions. Design/methodology/approach The research process is divided into four steps. First, the authors crawled for numerical data for each interactive repository feature created by employees of Alibaba on GitHub and identified the student accounts associated with these repositories. Second, a categorisation schema of feature classification was proposed on a behavioural basis. Third, the authors clustered the aforementioned repositories based on feature data and recognised four types of repositories (popular, formal, normal and obsolete) to represent four open collaboration patterns. The effects of the four repository types on university students' collaboration behaviour were measured using a multiple linear regression model. An ANOVA test was implemented to examine the robustness of research results. Finally, the authors proposed some practical suggestions to enhance collaboration between both sides of SCPs. Findings Several counterintuitive but reasonable findings were revealed, for example, those based on the "star" repository feature. The actual coding contribution of the repositories had a negative correlation with student attention. This result indicates that students were inclined to imitate rather than innovate. Originality/value This research explores the open collaboration patterns between enterprises and universities on GitHub and their impact on student coding behaviour. According to the research analysis, both parties benefit from open collaboration on SCPs, and the allocation or customisation of online repository features may affect students' participation in coding. This research brings a new perspective to the measurement of users' collaboration behaviour with output rates on SCPs.
作者机构：
[Yuan, Shuai] Cent China Normal Univ, Natl Engn Res Ctr E Leaming, Wuhan 430079, Peoples R China.;[He, Tingting] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;[He, Tingting] Cent China Normal Univ, Informat Retrieval & Knowledge Management Res Lab, Wuhan 430079, Peoples R China.;[Huang, Huan] South Cent Univ Nationalities, Sch Educ, Wuhan 430074, Peoples R China.;[Hou, Rui] South Cent Univ Nationalities, Coll Comp Sci, Wuhan 430074, Peoples R China.
通讯机构：
[He, Tingting] C;Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Informat Retrieval & Knowledge Management Res Lab, Wuhan 430079, Peoples R China.
作者：
Wu, Di（吴砥）;Yu, Liqin;Yang, Harrison Hao;Zhu, Sha*;Tsai, Chin-Chung
期刊：
British Journal of Educational Technology,2020年51(6):2268-2285 ISSN：0007-1013
通讯作者：
Zhu, Sha
作者机构：
[Wu, Di; Zhu, Sha; Yu, Liqin; Yang, Harrison Hao] Cent China Normal Univ China, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Yang, Harrison Hao] SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.;[Tsai, Chin-Chung] Natl Taiwan Normal Univ, Program Learning Sci, Taipei, Taiwan.
通讯机构：
[Zhu, Sha] C;Cent China Normal Univ China, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
摘要：
Given the pivotal role of parents in their children's educational development, numerous studies have examined the impacts of parents' information and communications technology (ICT) proficiency on adolescents' information literacy. However, previous research has tended to treat parents as a holistic unit, ignoring the individual uniqueness of each parent in analyses. Thus, the first aim of this study was to explore the parent profiles in terms of ICT proficiency, which were developed through a person-centered approach employing latent profile analysis. Three distinct parent profiles were identified: quiescent users, compliant users and active users. The second aim of this study was to investigate the relationship between the parents' profile memberships and adolescents' information literacy. The results showed that, in general, adolescents whose parents were identified as active users and compliant users tended to perform better on an information literacy test than those of parents categorized as quiescent users. More specifically, those adolescents whose parents were classified as active users achieved significantly higher scores in the information literacy test than those of parents who fit within the profiles of compliant users and quiescent users. Based on the findings, this paper discusses several implications and strategies for enhancing the adolescents' information literacy.
What is already known about this topic
What this paper adds
Implications for practice and/or policy
期刊：
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES,2020年13(3):617-630 ISSN：1939-1382
通讯作者：
Hung, Jui-Long
作者机构：
[Yang, Zongkai; Yang, Juan; Du, Xu] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.;[Hung, Jui-Long; Rice, Kerry] Boise State Univ, Dept Educ Technol, Boise, ID 83725 USA.;[Hung, Jui-Long] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
通讯机构：
[Hung, Jui-Long] B;Boise State Univ, Dept Educ Technol, Boise, ID 83725 USA.
作者机构：
[Liu, Sannyuya; Guo, Dongpo] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.;[Sun, Jianwen; Zhou, Dongbo] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.;[Yu, Jie] Wuhan Univ, Off Sci Res & Dev, Wuhan 490070, Peoples R China.
通讯机构：
[Zhou, Dongbo] C;Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
作者机构：
[Niu, Gengfeng] Xi An Jiao Tong Univ, Inst Social Psychol, Sch Humanities & Social Sci, Xian, Peoples R China.;[Sun, Lijun] Xinxiang Med Univ, Sch Psychol, Xinxiang, Henan, Peoples R China.;[Sun, Xiaojun; Sun, XJ; Zhou, Zongkui; Liu, Qingqi] Cent China Normal Univ, Sch Psychol, Wuhan, Peoples R China.;[Chai, Huanyou] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Sun, Xiaojun; Sun, XJ; Zhou, Zongkui] Cent China Normal Univ, Key Lab Adolescent Cyberpsychol & Behav CCNU, Wuhan, Peoples R China.
通讯机构：
[Sun, XJ; Zhou, ZK] C;Cent China Normal Univ, Sch Psychol, Wuhan, Peoples R China.;Cent China Normal Univ, Key Lab Adolescent Cyberpsychol & Behav CCNU, Wuhan, Peoples R China.
关键词：
Social networking site;Selfie-posting;Self-objectification;Commentary on appearance;Restrained eating
摘要：
Considering the prevalence of social networking sites (SNSs) and restrained eating among young adult women, the present study aimed to investigate the association between selfie-posting on an SNS (WeChat Moments, the most widely used SNS in China) and self-objectification among Chinese young adult women as well as the mediating effects of commentary on appearance and self-objectification from the perspective of self-perception theory and objectification theory. A sample of 886 female undergraduate students who had an active WeChat Moments account were recruited voluntarily to complete questionnaires on selfie-posting on SNS, general SNS use, commentary on appearance on SNSs, self-objectification, and restrained eating. The results indicated that after controlling for general SNS use, age, and BMI, selfie-posting on a SNS was positively associated with restrained eating. Commentary on appearance and self-objectification mediated this association, which contained three mediating paths: the separate mediating effects of commentary on appearance and self-objectification and the serial mediating effect of commentary on appearance and self-objectification. These results indicate that selfie-posting and commentary on appearance on a SNS rather than general SNS use are risk factors accounting for restrained eating, which has theoretical and practical implications in terms of SNS use and restrained eating.
期刊：
Journal of Cloud Computing,2020年9(1):1-17 ISSN：2192-113X
通讯作者：
Zhang, Hao
作者机构：
[Li, Jia; Liu, Sanya; Zhang, Hao; Huang, Tao; Xia, Yu; Yang, Huali] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.;[Li, Jia; Liu, Sanya; Zhang, Hao; Huang, Tao; Xia, Yu; Yang, Huali] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Yin, Hao] Shenyang Univ, Coll Informat Engn, Shenyang, Peoples R China.
通讯机构：
[Zhang, Hao] C;Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
作者：
Pan, Min;Huang, Jimmy Xiangji*;He, Tingting（何婷婷）;Mao, Zhiming;Ying, Zhiwei;...
期刊：
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY,2020年71(3):264-281 ISSN：2330-1635
通讯作者：
Huang, Jimmy Xiangji
作者机构：
[Pan, Min] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.;[Pan, Min; Mao, Zhiming] Hubei Normal Univ, Sch Comp & Informat Engn, Huangshi, Hubei, Peoples R China.;[Huang, Jimmy Xiangji; Pan, Min; Ying, Zhiwei] York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada.;[He, Tingting; Tu, Xinhui; Mao, Zhiming] Cent China Normal Univ, Sch Comp, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.;[Ying, Zhiwei] Cent China Normal Univ, Sch Informat Management, Informat Retrieval & Knowledge Management Res Lab, Wuhan, Peoples R China.
通讯机构：
[Huang, Jimmy Xiangji] Y;York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada.
摘要：
Pseudo-relevance feedback is a well-studied query expansion technique in which it is assumed that the top-ranked documents in an initial set of retrieval results are relevant and expansion terms are then extracted from those documents. When selecting expansion terms, most traditional models do not simultaneously consider term frequency and the co-occurrence relationships between candidate terms and query terms. Intuitively, however, a term that has a higher co-occurrence with a query term is more likely to be related to the query topic. In this article, we propose a kernel co-occurrence-based framework to enhance retrieval performance by integrating term co-occurrence information into the Rocchio model and a relevance language model (RM3). Specifically, a kernel co-occurrence-based Rocchio method (KRoc) and a kernel co-occurrence-based RM3 method (KRM3) are proposed. In our framework, co-occurrence information is incorporated into both the factor of the term discrimination power and the factor of the within-document term weight to boost retrieval performance. The results of a series of experiments show that our proposed methods significantly outperform the corresponding strong baselines over all data sets in terms of the mean average precision and over most data sets in terms of P@10. A direct comparison of standard Text Retrieval Conference data sets indicates that our proposed methods are at least comparable to state-of-the-art approaches.
期刊：
INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION,2020年17(1):1-13 ISSN：2365-9440
通讯作者：
Yang, Harrison H.
作者机构：
[Gong, Di] Cent China Normal Univ, Collaborat & Innovat Ctr Educ Technol, Wuhan, Peoples R China.;[Yang, Harrison H.] SUNY Coll Oswego, Sch Educ, 216D Hewitt Union, Oswego, NY 12306 USA.;[Yang, Harrison H.] Ctr China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Cai, Jin] Hubei Univ Educ, Sch Comp, Wuhan, Peoples R China.
通讯机构：
[Yang, Harrison H.] S;[Yang, Harrison H.] C;SUNY Coll Oswego, Sch Educ, 216D Hewitt Union, Oswego, NY 12306 USA.;Ctr China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
作者机构：
[Wu, Di; Wu, Lei; Zhou, Peng] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Palmer, Alexis] Univ North Texas, Dept Linguist, Denton, TX 76203 USA.;[Kinshuk] Univ North Texas, Coll Informat, Denton, TX 76203 USA.
通讯机构：
[Zhou, Peng] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
作者：
Shi, Yinghui;Yang, Huiyun;MacLeod, Jason;Zhang, Jingman;Yang, Harrison Hao*
期刊：
Journal of Educational Computing Research,2020年58(4):791-817 ISSN：0735-6331
通讯作者：
Yang, Harrison Hao
作者机构：
[Shi, Yinghui; Zhang, Jingman; Yang, Harrison Hao] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Yang, Huiyun] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.;[MacLeod, Jason] DYouville Coll, Operat & Adm, Buffalo, NY USA.;[Yang, Harrison Hao] SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
通讯机构：
[Yang, Harrison Hao] S;SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
关键词：
technology-enabled active learning;active learning environment;cognitive learning outcomes;meta-analyses;effect size
期刊：
Expert Systems with Applications,2020年158:113519 ISSN：0957-4174
通讯作者：
Su, Zhu;Liu, Sannyuya
作者机构：
[Yang, Zongkai; Liu, Sannyuya; Su, Zhu; Liu, SYY; Liu, Zhi; Ke, Wenxiang; Zhao, Liang] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.;[Yang, Zongkai; Liu, Sannyuya] Cent China Noma Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
通讯机构：
[Su, Z; Liu, SYY] C;Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
关键词：
Evolution feature;Behavior character;Friendship network;Percolation theory
摘要：
Analyzing and mining students' behaviors and interactions from big data is an essential part of education data mining. Based on the data of campus smart cards, which include not only static demographic information but also dynamic behavioral data from more than 30000 anonymous students, in this paper, the evolution features of friendship and the relations between behavior characters and student interactions are investigated. On the one hand, four different evolving friendship networks are constructed by means of the friend ties proposed in this paper, which are extracted from monthly consumption records. In addition, the features of the giant connected components (GCCs) of friendship networks are analyzed via social network analysis (SNA) and percolation theory. On the other hand, two high-level behavior characters, orderliness and diligence, are adopted to analyze their associations with student interactions. Our experiment/empirical results indicate that the sizes of friendship networks have declined with time growth and both the small-world effect and power-law degree distribution are found in friendship networks. Second, the results of the assortativity coefficient of both orderliness and diligence verify that there are strong peer effects among students. Finally, the percolation analysis of orderliness on friendship networks shows that a phase transition exists, which is enlightening in that swarm intelligence can be realized by intervening the key students near the transition point. (C)2020 Elsevier Ltd. All rights reserved.
作者机构：
[Yang, Juan; Du, Xu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Hung, Jui-Long] Boise State Univ, Dept Educ Technol, Boise, ID 83725 USA.;[Hung, Jui-Long] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
通讯机构：
[Yang, Juan] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
关键词：
deep neural network;early warning prediction;latent variational autoencoder;Performance prediction;resampling methods;t-SNE
作者机构：
[Ying, Zhiwei] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.;[Huang, Jimmy Xiangji; Ying, Zhiwei] York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON M3J 1P3, Canada.;[Zhou, Jie] East China Normal Univ, Dept Comp Sci & Technol, Shanghai 200062, Peoples R China.;[Jian, Fanghong] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[He, Tingting] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Huang, Jimmy Xiangji] Y;York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON M3J 1P3, Canada.
关键词：
digital signal processing;Information retrieval;probabilistic and statistical models
摘要：
Recently, researchers mainly focus on three categories of models in the field of Information Retrieval (IR), namely vector-space models, probabilistic models, and statistical language models. The existing studies have always developed IR models through refining or combining these traditional models. However, some new frameworks (e.g., digital signal processing (DSP)-based IR framework) have not been well-developed. In our research, we propose a new DSP-based IR Framework (DSPF) introducing the theories from the field of the DSP and present two corresponding DSP-based IR models, denoted as DSPF-BM25 and DSPF-DLM, which incorporate the term weighting schemes from two well-performed probabilistic IR models, the BM25, and the Dirichlet Language Model (DLM). In particular, first, we consider each query term as a spectrum with Gaussian form. Second, instead of transforming the signals from the time domain to frequency domain, we directly represent the query terms in the frequency domain. It is much more controllable and precise to adjust the values of the parameters for getting better performance of our proposed models. To testify the effectiveness of our proposed models, we conduct extensive experiments on seven standard datasets. The results show that in most cases our proposed models outperform the strong baselines in terms of MAP.
