作者机构：
[Zhang, Lishan] National Engineering Research Center for E-learning, Central China Normal University, Wuhan, People’s Republic of China;[Zhang, Jing] School of Educational Technology, Faculty of education, Beijing Normal University, Beijing, People’s Republic of China;Jingshi Liyun School of Shunde, Foshan, Guangdong, People’s Republic of China;Advanced Innovation Center for Future Education, Faculty of education, Beijing Normal University, Beijing, People’s Republic of China;[Pan, Mengqi] School of Educational Technology, Faculty of education, Beijing Normal University, Beijing, People’s Republic of China<&wdkj&>Jingshi Liyun School of Shunde, Foshan, Guangdong, People’s Republic of China
通讯机构：
[Ling Chen] S;School of Educational Technology, Faculty of education, Beijing Normal University, Beijing, People’s Republic of China<&wdkj&>Advanced Innovation Center for Future Education, Faculty of education, Beijing Normal University, Beijing, People’s Republic of China
期刊：
Expert Systems with Applications,2023年214:118943 ISSN：0957-4174
通讯作者：
Chen, Zengzhao(zzchen@ccnu.edu.cn)
作者机构：
[Wang, Hu; Chen, Zengzhao; Li, Jiawen; Liu, Hai; Zheng, Qiuyu] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.;[Li, Jiawen; Zheng, Qiuyu] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.;[Wang, Hu; Chen, Zengzhao; Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Wang, Xuyang] Aviat Ind Corp, Luoyang Inst Electroopt Equipment, Luoyang 471023, Henan, Peoples R China.
通讯机构：
[Zengzhao Chen] F;Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China<&wdkj&>National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China
关键词：
Connection attention mechanism;Features fusion;Frame-level features;Speech emotion recognition;Utterance-level features
作者机构：
[Chen, Jingying; Xu, Ruyi; Zhang, Kun] National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, People's Republic of China;School of Media and Technology, Liaocheng University, Liaocheng, People’s Republic of China;[Wang, Guangshuai] School of Computer Science, Wuhan University, Wuhan, People’s Republic of China;[Wang, Jidong] School of Teacher Education, Huzhou University, Huzhou, People’s Republic of China;[Zheng, Wenming] Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, People’s Republic of China
通讯机构：
[Jingying Chen] N;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, People's Republic of China
关键词：
autism spectrum disorder;computer games;computerized evaluation tool;quantitative indicator;validity;Visual motor integration
作者：
Yang, Shuoqiu;Du, Xu;Tang, Hengtao;Hung, Jui-Long;Tang, Yeye
期刊：
Education and Information Technologies,2023年:1-28 ISSN：1360-2357
通讯作者：
Tang, HT
作者机构：
[Yang, Shuoqiu; Du, Xu; Tang, Yeye] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Peoples R China.;[Tang, Hengtao; Tang, HT] Univ South Carolina, Dept Leadership Learning Design & Inquiry, Columbia, SC 29208 USA.;[Hung, Jui-Long] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.;[Hung, Jui-Long] Boise State Univ, Dept Educ Technol, Boise, ID USA.
通讯机构：
[Tang, HT ] U;Univ South Carolina, Dept Leadership Learning Design & Inquiry, Columbia, SC 29208 USA.
关键词：
Collaborative problem solving;Group interaction;Group interaction density;Collaborative performance
摘要：
Collaborative Problem Solving (CPS) has received increasing attention for its role in promoting learners' cognitive and social development in STEM education. However, little is known about how learners interact dynamically within a group at different time granularities. This gap mainly resulted from overlooking the time dimension of interactions, leading to a lack of nuanced understanding of moment-to-moment interaction in CPS. In this study, we demonstrated the potential of temporal group interaction density in modeling online CPS interactions and investigated the impact of temporal interaction density on CPS processes and outcomes. Specifically, we proposed using cumulative weighted density to measure the holistic state of group interactions and explained the differences in group interactions with different collaborative performance and interaction densities by modeling the transition and evolution of interaction sequences through Apriori and cumulative relative centrality. Results indicated that group interaction density cannot directly predict their collaborative performance, but notable differences in interaction patterns existed in the high-performance groups with different interaction densities, while low-performance groups showed interactive commonalities towards the completion of CPS. The findings of this study guided the design of CPS interventions and supported the process mining of CPS interactions, with vital practical implications for CPS assessment and skills development.
作者机构：
[Zhu, Sha; Yang, Harrison Hao] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Guo, Qing] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.;[Yang, Harrison Hao] SUNY Coll Oswego, Sch Educ, Oswego, NY 13126 USA.
通讯机构：
[Harrison Hao Yang] N;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China<&wdkj&>School of Education, State University of New York at Oswego, Oswego, NY 13126, USA<&wdkj&>Author to whom correspondence should be addressed.
关键词：
assessment methodologies;digital games;21st century skills;media in education
摘要：
Traditional methods of student assessment (SA) include self-reported surveys, standardized tests, etc. These methods are widely regarded by researchers as inducing test anxiety. They also ignore students' thinking processes and are not applicable to the assessment of higher-order skills. Digital game-based assessment (DGBA) is thought to address the shortcomings of traditional assessment methods. Given the advantages of DGBA, an increasing number of empirical studies are working to apply digital games for SA. However, there is a lack of any systematic review of DGBA studies. In particular, very little is known about the characteristics of the games, the content of the assessment, the methods of implementation, and the distribution of the results. This study examined the characteristics of DGBA studies, and the adopted games on SA in the past decade from different perspectives. A rigorous systematic review process was adopted in this study. First, the Web of Science (WOS) database was used to search the literature on DGBA published over the last decade. Then, 50 studies on SA were selected for subsequent analysis according to the inclusion and exclusion criteria. The results of this study found that DGBA has attracted the attention of researchers around the world. The participants of the DGBA studies were distributed across different educational levels, but the number of participants was small. Among all game genres, educational games were the most frequently used. Disciplinary knowledge is the most popular SA research content. Formative assessment modeling with process data and summative assessment using final scores were the most popular assessment methods. Correlation analysis was the most popular analysis method to verify the effectiveness of games on SA. However, many DGBA studies have reported unsatisfactory data analysis results. For the above findings, this study further discussed the reasons, as well as the meanings. In conclusion, this review showed the current status and gaps of DGBA in the SA application; directional references for future research of researchers and game designers are also provided.
期刊：
Behaviour & Information Technology,2023年 ISSN：0144-929X
通讯作者：
Chen, JY
作者机构：
[Sun, Jianchi; Wang, Guangshuai; Liu, Xiaodi; Chen, Jingying; Zhang, Kun; Ma, Pianpian] Cent China Normal Univ, Fac Artificial Intelligence Educ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Wang, Guangshuai] Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China.;[Zhang, Rujing] Liaocheng Univ, Sch Media & Technol, Liaocheng, Peoples R China.
通讯机构：
[Chen, JY ] C;Cent China Normal Univ, Fac Artificial Intelligence Educ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
关键词：
Evaluation;autism;gross motor skills;PEP-3
摘要：
To effectively evaluate the gross motor ability of autistic children, we proposed a method of computerised evaluation of gross motor skills (CEGM). The CEGM integrates Dynamic Time Warping (DTW) method and OpenPose technology to automatically detect key joints and return a score. Ten items were selected for evaluation based on the gross motor subtest of the Psychoeducational Profile - Third Edition (PEP-3) scale, including upper limb movement, lower limb movement, and body coordination performance. 30 autistic participants (males: 23, female: 7) with an average age of 5.00 years were recruited in this study. Then we compared the results of evaluation using CEGM and the original PEP-3 gross motor subtest in autistic children. The results showed that in the evaluations using CEGM and PEP-3, Cronbach's alpha coefficients and Spearman-rank correlation coefficients were all greater than 0.80, intraclass correlation coefficient (ICC) were all greater than 0.90, indicating good agreement in evaluating the gross motor ability of autistic children. Moreover, compared to the PEP-3, the evaluation using CEGM provided precise quantitative indicators (trajectory, velocity, and angle of joint). Therefore, our findings demonstrate that CEGM can be used in the initial evaluation of the gross motor ability of autistic children.
摘要：
Real-time emotion recognition in conversations (ERC), which relies on only the historical utterances to achieve ERC, has recently gained increasing attention due to its significance in providing real-time empathetic services. Although utilizing multimodal information can mitigate the issues of unimodal approaches, few real-time ERC studies consider the differences in representation ability of different modalities and explore comprehensive conversational context from different perspectives based on different structures. Furthermore, the heavy annotation cost makes it difficult to collect sufficient labeled data, which also limits the performance of current supervised ERC approaches. To address these issues, we propose a novel framework SMFNM for real-time ERC, which integrates semi-supervised learning with multimodal fusion under the guidance of main-modal. Specifically, SMFNM utilizes additional unlabeled data to extract high-quality intra-modal representations, and implements cross-modal interaction to capture complementary information to enhance the audio representations. Then SMFNM employs the directed acyclic graph and the Gated Recurrent Units for exploring more accurate conversational context from both the multimodal and main-modal perspectives, respectively. Finally, these two types of contextual features are fused for emotion identification. Extensive experiments on benchmark datasets (i.e., IEMOCAP (4-way), IEMOCAP (6-way) and MELD) demonstrate the effectiveness, superiority and rationality of our SMFNM.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
期刊：
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,2023年31:826-834 ISSN：2329-9290
作者机构：
[Dong, Ming; Tu, Xinhui; Wang, Yufan; Mei, Jie; He, Tingting] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smart, Wuhan 430079, Peoples R China.;[Dong, Ming; Tu, Xinhui; Wang, Yufan; Mei, Jie; He, Tingting] Cent China Normal Univ, Natl Language Resources Monitor & Res Ctr Network, Wuhan 430079, Peoples R China.;[Dong, Ming; Tu, Xinhui; Mei, Jie; He, Tingting] Cent China Normal Univ, Sch Comp Sci & Technol, Wuhan 430079, Peoples R China.;[Wang, Yufan] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
关键词：
Training;Correlation;Bit error rate;Semantics;Natural languages;Logic gates;Filling;Natural language processing;spoken language understanding;intent detection;slot filling
摘要：
Spoken language understanding (SLU) is an essential part of a task-oriented dialogue system, which mainly includes intent detection and slot filling. Some existing approaches obtain enhanced semantic representation by establishing the correlation between two tasks. However, those methods show little improvement when applied to BERT, since BERT has learned rich semantic features. In this paper, we propose a BERT-based model with the probability-aware gate mechanism, called PAGM (<underline>P</underline>robability <underline>A</underline>ware <underline>G</underline>ated <underline>M</underline>odel). PAGM aims to learn the correlation between intent and slot from the perspective of probability distribution, which explicitly utilizes intent information to guide slot filling. Besides, in order to efficiently incorporate BERT with the probability-aware gate, we design the stacked fine-tuning strategy. This approach introduces a mid-stage before target model training, which enables BERT to get better initialization for final training. Experiments show that PAGM achieves significant improvement on two benchmark datasets, and outperforms the previous state-of-the-art results.
作者机构：
[Chen, Zengzhao; Miao, Bingchen; Liu, Hai] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.;[Chen, Zengzhao; Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.;[Chen, Zengzhao] Cent China Normal Univ, Natl Intelligent Soc Governance Expt Base Educ, Wuhan 430079, Peoples R China.;[Zhang, Aijun] China Telecom Corp Henan Branch, Zhengzhou 450016, Peoples R China.
通讯机构：
[Zhang, AJ ] C;China Telecom Corp Henan Branch, Zhengzhou 450016, Peoples R China.
期刊：
Journal of Computing in Higher Education,2023年35(3):487-520 ISSN：1042-1726
通讯作者：
Lingyun Kang
作者机构：
[Yang, Zongkai; Liu, Sannyuya; Liu, Zhi; Zhao, Liang; Kang, Lingyun; Su, Zhu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Yang, Zongkai; Liu, Sannyuya; Liu, Zhi; Zhao, Liang; Su, Zhu] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.
通讯机构：
[Lingyun Kang] N;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, People’s Republic of China
摘要：
Understanding the relationship between interactive behaviours and discourse content has critical implications for instructors' design and facilitation of collaborative discussion activities in the online discussion forum (ODF). This paper adopts social network analysis (SNA) and epistemic network analysis (ENA) methods to jointly investigate the relationships between students’ network characteristics, discussion topics, and learning outcomes in a course discussion forum. Discourse data from 207 participants were included in this study. The findings indicated that (1) the interactive network generated in the collaborative discussion activities was sparsely connected, and there was limited information exchange between instructors and students; (2) students’ discussion topics were mainly related to the learning content; (3) compared with the isolated group, students in the leader, mediator, and animator groups were more concerned about topics related to the learning content; and (4) students who discussed more topics related to the learning content performed better than the students who discussed more topics related to learning methods and social interactions. The learning outcomes of the influencer and leader groups were significantly higher than those of the peripheral and isolated groups. However, there was no significant correlation between students’ individual centrality and their learning outcomes. The findings enrich the ODF research on the comprehensive identification of interactive behaviours and discourse content in the process of collaborative discussion activities and on the discussion topic differences between different role groups. The study findings also have practical implications for instructors to design effective instructional interventions aimed at improving the quality of collaboration in the ODF.
作者机构：
[Tang, Hengtao] Univ South Carolina, Dept Educ Studies, Columbia, SC USA.;[Dai, Miao; Du, Xu; Li, Hao] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Peoples R China.;[Hung, Jui-Long] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.;[Hung, Jui-Long] Boise State Univ, Dept Educ Technol, Boise, ID USA.
通讯机构：
[Du, X ] C;Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Peoples R China.
作者：
Li, Miaoyun;Lu, Chun;Yang, Harrison H.;Wu, Di;Yang, Xiao
期刊：
ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT,2023年71(5):2137-2154 ISSN：1042-1629
通讯作者：
Yang, HH
作者机构：
[Li, Miaoyun; Yang, Harrison H.] Cent China Normal Univ, Fac Artificial Intelligence Educ, Nanhu Campus Complex Bldg,382 Xiongchu Ave, Wuhan, Hubei, Peoples R China.;[Lu, Chun] Strateg Res Base Minist Educ, Res Ctr Sci & Technol Promoting Educ Innovat & Dev, Sci Hall,152 Luoyu Rd, Wuhan, Hubei, Peoples R China.;[Yang, Harrison H.] SUNY Coll Oswego, Sch Educ, 7060 State Route 104, Oswego, NY 13126 USA.;[Wu, Di] Cent China Normal Univ, Educ Informatizat Strategy Res Base Minist Educ, Sci Hall,152 Luoyu Rd, Wuhan, Hubei, Peoples R China.;[Yang, Xiao] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Sci Hall,152 Luoyu Rd, Wuhan, Hubei, Peoples R China.
通讯机构：
[Yang, HH ] C;Cent China Normal Univ, Fac Artificial Intelligence Educ, Nanhu Campus Complex Bldg,382 Xiongchu Ave, Wuhan, Hubei, Peoples R China.;SUNY Coll Oswego, Sch Educ, 7060 State Route 104, Oswego, NY 13126 USA.
