期刊：
Current Psychology,2023年42(27):23687-23697 ISSN：1046-1310
通讯作者：
Zhongling Pi
作者机构：
[Yang, Jiumin; Liu, Caixia; Zhang, Yi] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.;[Wu, Changcheng] Cent China Normal Univ, Natl Engn Res Ctr Learning, Artificial Intelligence Educ Div, Wuhan 430079, Peoples R China.;[Wu, Changcheng] Sichuan Normal Univ, Coll Comp Sci, Chengdu 610101, Peoples R China.;[Pi, Zhongling] Shaanxi Normal Univ, Minist Educ, Key Lab Modern Teaching Technol, 199 South Changan Rd, Xian 710062, Shaanxi, Peoples R China.
通讯机构：
[Pi, Z.] K;Key Laboratory of Modern Teaching Technology (Ministry of Education), Shaanxi Normal University, No. 199 South Chang’an Road, Yanta District, Shaanxi Province, Xi’an, China
作者机构：
[Zhang, Cheng; Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Deng, Yongjian] Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China.;[Deng, Yongjian] Minist Educ, Engn Res Ctr Intelligence Percept & Autonomous Co, Beijing, Peoples R China.;[Li, Youfu; Xie, Bochen] City Univ Hong Kong, Dept Mech Engn, Kowloon, Hong Kong, Peoples R China.
会议名称：
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
会议时间：
JUN 17-24, 2023
会议地点：
Vancouver, CANADA
会议主办单位：
[Zhang, Cheng;Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.^[Deng, Yongjian] Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China.^[Deng, Yongjian] Minist Educ, Engn Res Ctr Intelligence Percept & Autonomous Co, Beijing, Peoples R China.^[Xie, Bochen;Li, Youfu] City Univ Hong Kong, Dept Mech Engn, Kowloon, Hong Kong, Peoples R China.
会议论文集名称：
IEEE Conference on Computer Vision and Pattern Recognition
摘要：
Head pose estimation (HPE) has been widely used in the fields of human machine interaction, self-driving, and attention estimation. However, existing methods cannot deal with extreme head pose randomness and serious occlusions. To address these challenges, we identify three cues from head images, namely, neighborhood similarities, significant facial changes, and critical minority relationships. To leverage the observed findings, we propose a novel critical minority relationship-aware method based on the Transformer architecture in which the facial part relationships can be learned. Specifically, we design several orientation tokens to explicitly encode the basic orientation regions. Meanwhile, a novel token guide multiloss function is designed to guide the orientation tokens as they learn the desired regional similarities and relationships. We evaluate the proposed method on three challenging benchmark HPE datasets. Experiments show that our method achieves better performance compared with state-of-the-art methods. Our code is publicly available at https://github.com/zc2023/TokenHPE.
期刊：
Asia Pacific Education Review,2023年:1-14 ISSN：1598-1037
通讯作者：
Li, MY
作者机构：
[Yang, Wei; Yang, Xiao] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Lu, Chun] Minist Educ, Res Ctr Sci & Technol Promoting Educ Innovat & Dev, Strateg Res Base, Wuhan, Hubei, Peoples R China.;[Li, Miaoyun] Cent China Normal Univ, Educ Informatizat Strategy Res Base, Minist Educ, Wuhan, Hubei, Peoples R China.;[Lu, Chun] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan, Hubei, Peoples R China.;[Li, Miaoyun] Cent China Normal Univ, Educ Informatizat Strategy Res Base, Minist Educ, Wuhan, Hubei, Peoples R China.
通讯机构：
[Li, MY ] ;Cent China Normal Univ, Educ Informatizat Strategy Res Base, Minist Educ, Wuhan, Hubei, Peoples R China.
关键词：
Perceived ICT competence;Academic performance;Multilevel analysis;Rural Chinese schools
摘要：
The relationship between Information and Communication Technology (ICT) and academic performance is a controversial issue that has attracted increasing attention from administrators, policymakers, and researchers. The relationship between perceived ICT competence and the academic performance of rural students deserves particular attention. Although a small but growing body of research has examined the relationship between perceived ICT competence and student academic performance, few studies have viewed perceived ICT competence as a multilevel construct. This study aimed to fill this gap by examining the relationship between multilevel perceived ICT competence (i.e., student- and school-level perceived ICT competence) and student academic performance using a sample of 5530 students from 156 schools in rural China. Two-level hierarchical linear modeling results indicated that student- and school-level perceived ICT competence could predict academic performance. Furthermore, school-level perceived ICT competence could moderate the relationship between student-level ICT competence and academic outcomes. Specifically, the role of student-level perceived ICT competence showed heterogeneity across schools. Academic performance was strongly correlated with student-level perceived ICT competence in schools with a low level of perceived ICT competence; in contrast, this outcome was not observed in schools with a high level of perceived ICT competence. The findings suggest that administrators and policymakers in China should pay special attention to rural schools where perceived ICT competence is low and consider providing services for students in these schools to promote educational equity.
期刊：
Information Processing & Management,2023年60(1):103106 ISSN：0306-4573
通讯作者：
Jing Wang
作者机构：
[Yang, Shuoqiu; Li, Hao; Hu, Zhuang; Du, Xu; Wang, Jing] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.;[Yang, Shuoqiu; Li, Hao; Hu, Zhuang; Du, Xu; Wang, Jing] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.
通讯机构：
[Jing Wang] N;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China<&wdkj&>Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China
关键词：
Bi-hypergraph network;Intelligent education;Knowledge hypergraph;Teaching image annotation;Visual-knowledge features fusion;Visual-knowledge inconsistency
期刊：
Education and Information Technologies,2023年28(3):3145-3172 ISSN：1360-2357
通讯作者：
Yating Li
作者机构：
[Li, Yating; Zhou, Chi; Chen, Min; Man, Shuo] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Chen, Min] Minist Educ, Educ Informatizat Strategy Res Base, Wuhan 430079, Hubei, Peoples R China.;[Li, Yating] Minist Educ, Strateg Res Base, Res Ctr Sci & Technol Promoting Educ Innovat & De, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Yating Li] N;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China<&wdkj&>Research Center of Science and Technology Promoting Educational Innovation and Development, Strategic Research Base of the Ministry of Education, Wuhan, China
关键词：
Digital divide;Information literacy development;Information literacy evaluation;Status and difference analysis;Teachers’ information literacy
作者机构：
[Yu, Shengquan] Beijing Normal Univ, Adv Innovat Ctr Future Educ, Beijing, Peoples R China;[Zhang, Lishan] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China;[Huang, Yuwei; Yang, Xi] 17Zuoye, Beijing, Peoples R China;[Zhuang, Fuzhen] Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
通讯机构：
[Yu, Shengquan] B;Beijing Normal Univ, Adv Innovat Ctr Future Educ, Beijing, Peoples R China.
摘要：
Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This method performs well for closed-ended questions that have single or very limited numbers of correct answers. However, some short-answer questions ask students to express their own thoughts based on various facts; hence, they have no reference answers. Such questions are called semi-open-ended short-answer questions. Questions of this type often appear in reading comprehension assessments. In this paper, we developed an automatic semi-open-ended short-answer grading model that integrates both domain-general and domain-specific information. The model also utilizes a long-short-term-memory recurrent neural network to learn the representation in the classifier so that word sequence information is considered. In experiments on 7 reading comprehension questions and over 16,000 short-answer samples, our proposed automatic grading model demonstrates its advantage over existing models.
摘要：
早期预警是在线学习中的重要主题,通过早期预警识别有不及格风险的学生可帮助教师及时开展个性化教学干预。使用深度学习模型对学生微观行为模式进行分析以提高早期预警的效果,并提出结合LSTM-autoencoder特征处理和注意力权重计算的不及格风险学生早期预警模型(LSTM-autoencoder and attention based early warning model,LAA)。该方法通过LSTM-autoencoder对学生行为时间序列数据进行特征处理,采用注意力机制计算关键预测因子。实验结果表明,LAA比基线模型取得更高的召回率,对低交互型和非持续型学生具有更好的识别效果,且能将教学干预时间提前;此外,该方法可识别影响成绩的关键周次和行为,可用于辅助教师开展在线教学指导。
摘要：
Dialogue state tracking (DST) is a core component of task-oriented dialogue systems. Recent works focus mainly on end-to-end DST models that omit the spoken language understanding (SLU) module to directly obtain the dialogue state based on a user’s dialogue. However, the slot information detected by slot filling in SLU is closely tied to the slot–value pair that needs to be updated in DST. Efficient use of the key slot semantic knowledge obtained by slot filling contributes to improving the performance of DST. Based on this idea, we introduce slot filling as a subtask and build an end-to-end joint model to explicitly integrate the slot information detected by slot filling, which further guides DST. In this article, a novel stack-propagation framework with slot filling for multidomain DST is proposed. The stack-propagation framework is introduced to jointly model slot filling and DST. The framework directly feeds the key slot semantic knowledge detected by slot filling into the DST module. In addition, a slot-masked attention mechanism is designed to enable DST to focus on the key slot information obtained by slot filling. When the slot value is updated, a slot–value softcopy mechanism is designed to enhance the influence of the words marked by key slots. Experiments show that our approach outperforms previous methods and performs outstandingly on two benchmark datasets. IEEE
作者机构：
[Yang, Bing; Liu, Tingting] Hubei Univ, Sch Educ, 368 Youyi Rd, Wuhan 430062, Hubei, Peoples R China.;[Subramanian, Sriram; Liu, Tingting; Zhang, Zhaoli; Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Ju, Jianping] Hubei Business Coll, Sch Artificial Intelligence, Wuhan 430079, Peoples R China.;[Tang, Jianyin] Changchun Univ Sci & Technol, Sch Electromech Engn, Changchun 130022, Peoples R China.;[Liu, Hai] UCL, UCL Interact Ctr, London, England.
通讯机构：
[Ju, JP ] H;[Liu, H ] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;Hubei Business Coll, Sch Artificial Intelligence, Wuhan 430070, Peoples R China.
作者机构：
[Tang, Hengtao] Univ South Carolina, Dept Educ Studies, Columbia, SC 29208 USA.;[Dai, Miao; Yang, Shuoqiu; Li, Hao; Du, Xu] Cent China Normal Univ, Natl Engn Res Ctr Learning, 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 83725 USA.
通讯机构：
[Hengtao Tang] D;Department of Educational Studies, University of South Carolina, Columbia, United States
关键词：
collaborative problem-solving (CPS);attention;multimodal learning analytics;online;hidden Markov model (HMM)
作者机构：
[Yang, Zongkai; Liu, Sannyuya; Liu, Zhi; Peng, Xian] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.;[Yang, Zongkai; Liu, Sannyuya; Mu, Rui] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Chen, Jia] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.
通讯机构：
[Xian Peng] N;National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, People’s Republic of China
