期刊：
ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT,2024年:1-32 ISSN：1042-1629
通讯作者：
Long, TT
作者机构：
[Long, Taotao] Cent China Normal Univ, Fac Fac Artificial Intelligence Educ, Dept Sci Commun & Sci Educ, 382 Xiongchu Rd, Wuhan 430079, Hubei, Peoples R China.;[Zheng, Zhixia] Expt Primary Sch Ind Technol Dev Area, Longquanyi Dist,3 Taodu Ave, Chengdu 610100, Sichuan, Peoples R China.;[Shi, Yu] Suzhou Ind Pk Xinghai Expt Sr High Sch, Ind Pk Dist,168 Shenhu Rd, Suzhou 215021, Jiangsu, Peoples R China.;[Tong, Mingwen] Cent China Normal Univ, Fac Fac Artificial Intelligence Educ, Dept Educ Technol, 382 Xiongchu Rd, Wuhan 430079, Hubei, Peoples R China.;[Liu, Zhi] Cent China Normal Univ, Fac Fac Artificial Intelligence Educ, Natl Engn Res Ctr Educ Big Data, 382 Xiongchu Rd, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Long, TT ] C;Cent China Normal Univ, Fac Fac Artificial Intelligence Educ, Dept Sci Commun & Sci Educ, 382 Xiongchu Rd, Wuhan 430079, Hubei, Peoples R China.
摘要：
Inquiry-based instruction has played an important role in science education, and been recognized as a critical approach to improve students' scientific learning effectiveness. However, current research revealed that it is a challenge for teacher education programs to improve pre-service science teachers' inquiry-based instructional activity design competency. Due to the dynamic and complicated process of the instructional design competency improvement, there is a strong need for new methods that could trace this process. Considering the Knowledge Integration (KI) theory has been demonstrated to be able to help science teachers design their inquiry-based instructional activities in a large amount of existing research, in this study, a KI-based collaborative learning environment was designed to support 19 pre-service science teachers' inquiry-based instructional activity design. Epistemic network analysis (ENA) was applied to trace the development process of their inquiry-based instructional activity design e behaviour patterns. Data analysis results revealed that the pre-service science teachers demonstrated gradually more active in "guiding students to design exploratory activities" and "guiding students to communicate and cooperate" in their instructional designs during the process of using the KI-based collaborative learning environment. Through identifying and comparing the design patterns of the high-performing and low-performing groups, the results showed that the low-performing groups demonstrated more active on "posing inquiry questions" and "guiding students to formulate scientific explanation," while the high performing groups demonstrated more active in "guiding students to design exploratory activities" and "guiding students to communicate and cooperate." Furthermore, the semi-structured interview results demonstrated that the KI-based collaborative learning environment not only provided the pre-service science teachers a convenient way on online collaboration, but also helped them form more normative and integrated understandings on inquiry-based instruction. However, this study demonstrated that quite a few pre-service science teachers still had misconceptions on inquiry-based instruction. Suggestions are provided for improving pre-service science teachers' inquiry-based instructional design competency in a technology-enhanced learning environment.
摘要：
Object co-segmentation is a challenging task, which aims to segment common objects in multiple images at the same time. Generally, common information of the same object needs to be found to solve this problem. For various scenarios, common objects in different images only have the same semantic information. In this paper, we propose a deep object co-segmentation method based on channel and spatial attention, which combines the attention mechanism with a deep neural network to enhance the common semantic information. Siamese encoder and decoder structure are used for this task. Firstly, the encoder network is employed to extract low-level and high-level features of image pairs. Secondly, we introduce an improved attention mechanism in the channel and spatial domain to enhance the multi-level semantic features of common objects. Then, the decoder module accepts the enhanced feature maps and generates the masks of both images. Finally, we evaluate our approach on the commonly used datasets for the co-segmentation task. And the experimental results show that our approach achieves competitive performance. (C) 2020 Elsevier B.V. All rights reserved.
期刊：
ACM International Conference Proceeding Series,2021年:51-59
作者机构：
[Yu Shi; Qing Zhou; Ming Wen Tong; Qi Cheng; Xiao Xiao Cui; Pan Cao; Ya Fei Shi] School of Educational Information Technology, Central China Normal University, Wuhan, China
会议论文集名称：
ICFET '21: Proceedings of the 7th International Conference on Frontiers of Educational Technologies
期刊：
ACM International Conference Proceeding Series,2020年:145-149
作者机构：
[Ling Zhong; Yantao Wei; Wei Deng] Educational Information Research Center of Hubei, Central China Normal University, Wuhan, China;[Huang Yao; Zhifeng Wang; Mingwen Tong] School of Educational Information Technology, Central China Normal University, Wuhan, China
会议论文集名称：
IC4E '20: Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning
期刊：
ACM International Conference Proceeding Series,2020年:5-9
作者机构：
[Yafei Shi; Mingwen Tong; Jia Sun; Taotao Long; Xin Long] School of Educational Information Technology, Central China Normal University, Wuhan, China;[Hongbin Dai] Co-innovation Center of Informatization and Balanced Development of Basic Education, Central China Normal University, Wuhan, China
会议论文集名称：
IC4E '20: Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning
期刊：
International Journal of Wavelets, Multiresolution and Information Processing,2019年17(1):1950001 ISSN：0219-6913
通讯作者：
Wei, Yantao
作者机构：
[Yao, Huang; Shi, Yafei; Wei, Yantao; Tong, Mingwen; Liu, Qingtang; Chen, Tiantian; Deng, Wei; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Pan, Donghui] Anhui Univ, Sch Math Sci, Hefei 230601, Anhui, Peoples R China.
通讯机构：
[Wei, Yantao] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.
关键词：
Student body gesture recognition;fisher broad learning system;learning analytics
摘要：
<jats:p> Observing student body gesture has been widely used to assess teaching effectiveness over the past few decades. However, manual observation is not suitable for the automatic data analysis in the field of learning analytics. Consequently, a student body gesture recognition method based on Fisher Broad Learning System (FBLS) and Local Log-Euclidean Multivariate Gaussian (L<jats:sup>2</jats:sup>EMG) is proposed in this paper. FBLS is designed by introducing the discriminative information into the hidden layer of Broad Learning System (BLS) and reducing the dimensionality of hidden-layer representations. FBLS has superiorities in accuracy and speed. In addition, L<jats:sup>2</jats:sup>EMG, which is a highly distinctive descriptor, characterizes the local image with a multivariate Gaussian distribution. So L<jats:sup>2</jats:sup>EMG features are fed into the FBLS for recognition in this paper. Extensive experimental results on self-built dataset show that the proposed student body gesture recognition method obtains better results than other benchmarking methods. </jats:p>
期刊：
ACM International Conference Proceeding Series,2018年:63-68
作者机构：
[Ying Xia; Min Chen; Mingwen Tong; Chuang Zhou] School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China
会议论文集名称：
ICBDT '18: Proceedings of the 1st International Conference on Big Data Technologies
关键词：
Educational technology;Information analysis;Information systems;Information use;Social networking (online);Social sciences computing;Co-word analysis;High frequency HF;Hot spot;Hot topics;Hotspots;Network structures;Zhihu topics;Big data
摘要：
This research started with the topic of educational technology of Zhihu. In order to explore other hot topics associated with it and the hotspots and trends in the parent topics of the annual questions, this research used the method of co-word analysis, social network analysis. Through digging topics network structure to understand the relationship between topics topics location and roles in the network. This research found that there were two major hot topics under educational technology topic. One was a hot spot of other professional topics closely linked to educational technology. The second was hot topics of interest to users under this topic. Through social network analysis, it was found that the structure of high-frequency topics network was relatively close and the structure of the parent topics network was loose, forming a higher tendency of centripetalism with educational technology as the core, and the topic with the core position in the network also had strong intermediary. The hotspot for future parent topics will be those at the edge of the high-frequency parent topics network, but in line with the current research hotspots in the field of educational technology.
摘要：
Intelligent methods are needed to organize the large amount of teaching and learning resources, one important aspect is to plan the learning path. According to the existing research, ant colony algorithm showed great advantages in learning path planning. Different from the traditional ant colony algorithm, Mahalanobis distance was adopted to calculate the distance between the data in the improved ACO. This paper proposed a method to recommend learning path using an improved ant colony algorithm based on a novel coordinate system. Also, In order to transform the unmeasurable concept map and information in syllabus into measurable data, a novel coordinate system was built to draw points which represent the teaching or learning units in it. The experimental results showed that this method can recommend an efficient learning path.
