摘要：
An instructor's gestures have an effect not only on students' learning but also on teaching itself. In two experiments, this study tested whether instructors' use of gestures while recording video lectures affected their teaching performance, stress, and cognitive load. In Experiment 1, participants recorded video lectures with gestures or without gestures. As hypothesized, t tests showed that participants in the gestures condition had better teaching performance and lower cognitive load than participants in the no-gestures condition, whereas there was no effect on stress level. In Experiment 2, participants recorded video lectures with either pointing gestures or representational gestures. The t tests indicated that participants in the pointing gestures condition showed better teaching performance and experienced lower stress than those in the representational gestures condition, but there was no difference in cognitive load. Overall, our findings suggest that in the new educational environment of video lectures, instructors should consider using gestures, especially pointing gestures, to improve their teaching and their experience of teaching.
What is already known about this topic
What this paper adds
Implications for practice and/or policy
作者：
Ni Zhang;Qingtang Liu;Jiaojiao Zhu;Qiyun Wang;Kui Xie
期刊：
Technology, Knowledge and Learning,2020年25(2):323-336 ISSN：2211-1662
通讯作者：
Ni Zhang<&wdkj&>Qingtang Liu
作者机构：
[Ni Zhang; Qingtang Liu; Jiaojiao Zhu] School of Educational Information Technology, Central China Normal University, Wuhan, China;[Qiyun Wang] National Institute of Education, Nanyang Technological University, 50 Nanyang Avenue, Singapore;[Kui Xie] Department of Educational Studies, The Ohio State University, Columbus, USA
通讯机构：
[Ni Zhang; Qingtang Liu] S;School of Educational Information Technology, Central China Normal University, Wuhan, China<&wdkj&>School of Educational Information Technology, Central China Normal University, Wuhan, China
摘要：
Teacher workshops attract teachers with common goals; they wish to improve their teaching practices and subject and information technology knowledge. The asynchronous online discussion is the main activity in teacher workshops. An analytical model was developed in this study to examine the temporal characteristics of collaborative knowledge construction in teacher workshops. Specifically, 664 posts were analyzed from an asynchronous online discussion—involving 91 teachers—on the topic, “How to Make a Language Course Interesting?” The aim of this paper is to present the changes in knowledge construction levels and teachers’ social interactive characteristics resulting from participation in teacher workshops. From the findings of this study, advances in theory, methodology and pedagogical practice are indicated. The findings also indicate that knowledge construction levels and teachers’ social interactive characteristics change at different stages of discussions. Suggestions for improving the effects of online teacher workshops are provided.
期刊：
Mathematical Problems in Engineering,2020年2020 ISSN：1024-123X
通讯作者：
Wei, Yantao
作者机构：
[Yao, Huang; Wei, Yantao; Tian, Yuan; Zhang, Yu] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Peoples R China.;[Wei, Yantao] Cent China Normal Univ, Educ Informatizat Res Ctr Hubei, Wuhan 430079, Peoples R China.
通讯机构：
[Wei, Yantao] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Educ Informatizat Res Ctr Hubei, Wuhan 430079, Peoples R China.
摘要：
In this paper, we propose a new method for hyperspectral images (HSI) classification, aiming to take advantage of both manifold learning-based feature extraction and neural networks by stacking layers applying locality sensitive discriminant analysis (LSDA) to broad learning system (BLS). BLS has been proven to be a successful model for various machine learning tasks due to its high feature representative capacity introduced by numerous randomly mapped features. However, it also produces redundancy, which is indiscriminate and finally lowers its performance and causes heavy computing demand, especially in cases of the input data bearing high dimensionality. In our work, a manifold learning method is integrated into the BLS by inserting two LSDA layers before the input layer and output layer separate, so the spectral-spatial HSI features are fully utilized to acquire the state-of-the-art classification accuracy. The extensive experiments have shown our method's superiority.
期刊：
Mathematical Problems in Engineering,2020年2020 ISSN：1024-123X
通讯作者：
Chen, Jia
作者机构：
[Wu, Dongli; Wei, Yantao; Wei, Yangyu; Luo, Heng; Chen, Jia; Deng, Wei] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Wu, Dongli; Wei, Yantao; Wei, Yangyu; Luo, Heng; Chen, Jia; Deng, Wei] Hubei Res Ctr Educ Informationizat, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Chen, Jia] C;[Chen, Jia] H;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;Hubei Res Ctr Educ Informationizat, Wuhan 430079, Hubei, Peoples R China.
摘要：
Teaching reflection based on videos is the main method in teacher education and professional development. However, it takes a long time to analyse videos, and teachers are easy to fall into the state of information overload. With the development of "AI + education," automatic recognition of teacher behavior to support teaching reflection has become an important research topic. In this paper, taking online open classroom teaching video as the data source, we collected and constructed a teacher behavior dataset. Using this dataset, we explored the behavior recognition methods based on RGB video and skeleton information, and the information fusion between them is carried out to improve the recognition accuracy. The experimental results show that the fusion of RGB information and skeleton information can improve the recognition accuracy, and the early-fusion effect is better than the late-fusion effect. This study helps to solve the problems of time-consumption and information overload in teaching reflection and then helps teachers to optimize the teaching strategies and improve the teaching efficiency.
期刊：
Technology, Knowledge and Learning,2020年25(4):811-833 ISSN：2211-1662
通讯作者：
Linjing Wu
作者机构：
[Linjing Wu; Qingtang Liu; Gang Mao; Jingxiu Huang] School of Educational Information Technology, Central China Normal University, Wuhan, China;[Wanlei Zhou] School of Information Technology, Deakin University, Melbourne, Australia;[Huan Huang] School of Education, South-Central University for Nationalities, Wuhan, China
通讯机构：
[Linjing Wu] S;School of Educational Information Technology, Central China Normal University, Wuhan, China
摘要：
A big challenge in educational resources construction is the intelligent and personalized resource recommendation for learners. This paper proposes a semantic recommendation framework of educational resources based on semantic web and pedagogics. In this framework, a domain ontology is constructed to describe the knowledge structure of the domain. All the resources and user portfolio are described with ontology technology and resource description framework to support semantic inference. Based on the semantic resource organization, we made a set of reasoning rules based on pedagogics. These rules are made from the synthesis of the type of the knowledge, the internal structure of knowledge and learner’s learning performance. A case study was implemented on the course “theory and practice of database”. In this case, learners are recommended different learning materials according to the different knowledge structure and different learning performance. Three typical learning modes are proposed to describe the personalized learning experience. This framework can be used as a guide for teachers and resource designers.
作者：
Yang, Yuqin*;Chen, Qianqian;Yu, Yawen;Feng, Xueqi*;van Aalst, Jan
期刊：
British Journal of Educational Technology,2020年51(4):1136-1154 ISSN：0007-1013
通讯作者：
Yang, Yuqin;Feng, Xueqi
作者机构：
[Yang, Yuqin] Cent China Normal Univ, Learning Sci, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Yang, Yuqin; Chen, Qianqian] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;[Feng, Xueqi; Yu, Yawen] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.;[van Aalst, Jan] Univ Twente, Dept Teacher Educ, Fac Behav Management & Social Sci, Enschede, Netherlands.
通讯机构：
[Yang, Yuqin] C;[Feng, Xueqi] U;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.
作者：
Jui-Long Hung;Kerry Rice;Jennifer Kepka;Juan Yang
期刊：
Information Discovery and Delivery,2020年48(4):199-212 ISSN：2398-6247
通讯作者：
Yang, J.
作者机构：
Department of Educational Technology, Boise State University College of Education, Boise, Idaho, USA and National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, China;Department of Educational Technology, Boise State University, Boise, Idaho, USA;[Yang J.] National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China;[Kepka J.; Rice K.] Department of Educational Technology, Boise State University, Boise, ID, United States;[Hung J.-L.] Department of Educational Technology, Boise State University College of Education, Boise, ID, United States, National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, China
通讯机构：
[Yang, J.] N;National Engineering Research Center for E-Learning, China
关键词：
Deep learning;Early warning;Educational data mining;Educational text mining;Optimal threshold;Performance prediction
