作者机构：
[Zhang, Kai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Zhang, Kai] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.;[Zhang, Kai] Univ Regina, Dept Comp Sci, Regina, SK, Canada.
通讯机构：
[Zhang, Kai] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
作者机构：
[Liu, Zhi; Yang, Chongyang; Liu, Sannyuya; Wang, Tai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China;[Liu, Zhi; Liu, Sannyuya; Zhao, Liang] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China;[Ruedian, Sylvio] Humboldt Univ, Dept Comp Sci, Berlin, Germany
通讯机构：
[Liu, Sannyuya] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China. Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.
关键词：
Discussion forum;learning analytics;temporal emotion-aspect model (TEAM);emotion-aspect evolution;emotional difference
作者：
MacLeod, Jason;Yang, Harrison Hao*;Shi, Yinghui
期刊：
Journal of Computing in Higher Education,2019年31(2):426-448 ISSN：1042-1726
通讯作者：
Yang, Harrison Hao
作者机构：
[MacLeod, Jason] DYouville Coll, Operat & Adm, Buffalo, NY USA.;[Shi, Yinghui; Yang, Harrison Hao] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Yang, Harrison Hao] SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
通讯机构：
[Yang, Harrison Hao] C;[Yang, Harrison Hao] S;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
会议名称：
International Conference on Hybrid Learning (ICHL)
会议时间：
JUL 31-AUG 02, 2018
会议地点：
Osaka, JAPAN
会议主办单位：
[MacLeod, Jason] DYouville Coll, Operat & Adm, Buffalo, NY USA.^[Yang, Harrison Hao;Shi, Yinghui] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.^[Yang, Harrison Hao] SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
摘要：
Student-to-student connectedness is promoted by active, student-centered learning processes. It is a socio-psychological result of interpersonal communication and behavior in the classroom, which emulates belonging, cohesiveness, and supportiveness among peers. Currently, two survey instruments exist—Dwyer et al.’s (Commun Res Rep 21(3):264–272, 2004.
https://doi.org/10.1080/08824090409359988
) Connected Classroom Climate Inventory and Johnson’s (Commun Res Rep 26(2):146–157, 2009.
https://doi.org/10.1080/08824090902861622
) amendment thereof, which have been used for nearly two decades to gain insight into instructional processes in face-to-face environments. However, research on student-to-student connectedness is relatively limited in the context of modern, technology-mediated learning environments. Arguably, where student-to-student connectedness is most urgently needed because of the decrease in face-to-face contact time between students and their instructors within online and hybrid learning environments. This study is a systematic literature review that presents a synthesis of twenty-four peer-reviewed journal articles, which empirically investigate student-to-student connectedness within face-to-face, hybrid, and online environments. The documentation of data is organized in accordance to the six aspects of activity theory (subjects, objects, mediating artifacts, rules, community, division of labor) to provide a basis for understanding the dynamics of each research report, as well as to assist identifying the trends and gaps in the literature, thereby expediting future research on this topic.
作者机构：
[Wu, Di; Zhou, Chi; Shi, Yinghui; Chen, Min; Yang, Wei] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
会议名称：
8th International Conference on Educational Innovation through Technology (EITT)
会议时间：
OCT 27-31, 2019
会议地点：
Univ Southern Mississippi, Biloxi, MS
会议主办单位：
Univ Southern Mississippi
会议论文集名称：
Proceedings of the International Conference of Educational Innovation through Technology
关键词：
technology integration;mathematic teachers;Information and Communication Technology (ICT) application;education informationization;differences
摘要：
The application of Information and Communication Technology (ICT) in teaching can improve the teaching quality and efficiency. Exploring the differences in mathematic teachers' ICT application level can not only better help us understand the status of overall mathematic teachers' ICT application level, but also promote the development of ICT-based teaching in mathematic by discovering the shortcomings. This study explored the differences of K-12 mathematic teachers' ICT application level from three aspects-teacher's attitude towards ICT (TAT), ICT instruction in classroom (IIC) and ICT effects (ICE). A survey research design was used for the study, and 918 K-12 mathematic teachers participated in the study. The ANOVA results showed that, there were significant differences in TAT and ICE between primary school teachers and secondary school teachers, while there were no significant differences between rural school teachers and urban school teachers. As for IIC, on the other hand, there was significant differences between primary school teachers and secondary school teachers and there were significant differences between rural school teachers and urban school teachers. According to the results, some implications were proposed to improve K-12 mathematic teachers' ICT application level.
作者机构：
[Chen Mao; Peng Xicheng; Zhang Jingzhong] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Zhang Jingzhong] Guangzhou Univ, Inst Computat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China.;[Zhang Jingzhong] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 610041, Peoples R China.
通讯机构：
[Chen Mao] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
关键词：
Geometry algebra;point geometry;proof method based on identical equations;vector geometry;Wu's method
摘要：
The algebraic methods represented by Wu's method have made significant breakthroughs in the field of geometric theorem proving. Algebraic proofs usually involve large amounts of calculations, thus making it difficult to understand intuitively. However, if the authors look at Wu's method from the perspective of identity,Wu's method can be understood easily and can be used to generate new geometric propositions. To make geometric reasoning simpler, more expressive, and richer in geometric meaning, the authors establish a geometric algebraic system (point geometry built on nearly 20 basic properties/formulas about operations on points) while maintaining the advantages of the coordinate method, vector method, and particle geometry method and avoiding their disadvantages. Geometric relations in the propositions and conclusions of a geometric problem are expressed as identical equations of vector polynomials according to point geometry. Thereafter, a proof method that maintains the essence of Wu's method is introduced to find the relationships between these equations. A test on more than 400 geometry statements shows that the proposed proof method, which is based on identical equations of vector polynomials, is simple and effective. Furthermore, when solving the original problem, this proof method can also help the authors recognize the relationship between the propositions of the problem and help the authors generate new geometric propositions.
作者机构：
[Liu, Leyuan; Gui, Wenting; Zhang, Li; Chen, Jingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Liu, Leyuan; Chen, Jingying] Cent China Normal Univ, Natl Engn Lab Technol Big Data Applicat Educ, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Chen, Jingying] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
关键词：
Conditional random regression forests;Head pose;Real-time;Smile detection
摘要：
Detecting spontaneous smile in unconstrained environment is a challenging problem mainly due to the large intra-class variations caused by head poses. This paper presents a real-time smile detection method based on conditional random regression forests. Since the relation between image patches and smile intensity is modelled conditional to head pose, the proposed smile detection method is not sensitive to head poses. To achieve high smile detection performance, techniques including regression forest, multiple-label dataset augmentation and non-informative patch removement are employed. Experimental results show that the proposed method achieves competitive performance to state-of-the-art deep neural network based methods on two challenging real-world datasets, although using hand-crafted features. A dynamical forest ensemble scheme is also presented to make a trade-off between smile detection performance and processing speed. In contrast to deep neural networks, the proposed method can run in real-time on general hardware without GPU.
作者机构：
[Changxin Gao] School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China;[Leyuan Liu; Yukang Zhang; Jingying Chen] National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China
会议名称：
2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)
会议时间：
December 2019
会议地点：
Xiamen, China
会议论文集名称：
2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)
关键词：
Semantic parts, Person re-ID, Multiple granu larities, Representations fusion
摘要：
A multiple granularities method for person re-identification (re-ID) is proposed in this paper, which fuses global and semantic-part representations. A prior guided human parsing method is employed to parse a human body into precise basic semantic parts from low-resolution images, and multiple granularities are generated by recombining the adjacent basic semantic parts. Then, convolutional neural networks that seam-lessly unify the Softmax and TriHard losses are proposed to learn and fuse the global-level and the part-level features in different granularities. The proposed method not only extracts precise part-level features, but also incorporates gradual cues between part-level and global-level features to boost a high performance of person re-ID. Extensive experimental results show our proposed SPMG model achieves state-of-the-art performance on three common datasets .
