摘要：
This paper presents an algorithm for proving plane geometry theorems stated by text and diagram in a complementary way. The problem of proving plane geometry theorems involves two challenging subtasks, being theorem understanding and theorem proving. This paper proposes to consider theorem understanding as a problem of extracting relations from text and diagram. A syntax–semantics (S2) model method is proposed to extract the geometric relations from theorem text, and a diagram mining method is proposed to extract geometry relations from diagram. Then, a procedure is developed to obtain a set of relations that is consistent with the given theorem with high confidence. Finally, theorem proving is conducted by using the existing proving methods which take the extracted geometric relations as input. The experimental results show that the proposed theorem proving algorithm can prove 86% of plane geometry theorems in the test dataset of 200 theorems, which is all the theorems in the popular textbook. The proposed algorithm outperforms the existing algorithms mainly because it can extract relations not only from text but also from diagram.
作者：
Yu, Xinguo（余新国）;Wang, Mingshu;Gan, Wenbin;He, Bin*;Ye, Nan
期刊：
International Journal of Pattern Recognition and Artificial Intelligence,2019年33(7):1940005 ISSN：0218-0014
通讯作者：
He, Bin
作者机构：
[Yu, Xinguo; Gan, Wenbin; He, Bin; Wang, Mingshu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Ye, Nan] Univ Queensland, Brisbane, Qld 4072, Australia.
通讯机构：
[He, Bin] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
关键词：
Automatic solver;relation extraction;syntax-semantic model;arithmetic word problems;plane geometry theorems
摘要：
This paper presents a framework for solving math problems stated in a natural language (NL) and applies the framework to develop algorithms for solving explicit arithmetic word problems and proving plane geometry theorems. We focus on problem understanding, that is, the transformation of a NL description of a math problem to a formal representation. We view this as a relation extraction problem, and adopt a greedy algorithm to extract the mathematical relations using a syntax-semantics model, which is a set of patterns describing how a syntactic pattern is mapped to its formal semantics. Our method yields a human readable solution that shows how the mathematical relations are extracted one at a time. We apply our framework to solve arithmetic word problems and prove plane geometry theorems. For arithmetic word problems, the extracted relations are transformed into a system of equations, and the equations are then solved to produce the solution. For plane geometry theorems, these extracted relations are input to an inference system to generate the proof. We evaluate our approach on a set of arithmetic word problems stated in Chinese, and two sets of plane geometry theorems stated in Chinese and English. Our algorithms achieve high accuracies on these datasets and they also show some desirable properties such as brevity of algorithm description and legibility of algorithm actions.
期刊：
ICIET 2019: Proceedings of the 2019 7th International Conference on Information and Education Technology,2019年:Pages 230–237
通讯作者：
Zhang, Juan
作者机构：
[Zhang, Juan] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Tian, Yuan] Cent China Normal Univ, Sch Psychol, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Zhang, Juan] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
会议名称：
7th International Conference on Information and Education Technology (ICIET)
会议时间：
MAR 29-31, 2019
会议地点：
Univ Aizu, Aizuwakamatsu, JAPAN
会议主办单位：
Univ Aizu
关键词：
Field independent-dependent cognitive style;Teaching mode;Learning performance
摘要：
In order to explore the relationships among learning performance, field independent-dependent cognitive styles and teaching modes, and to test what kind of cognitive styles are suitable for what kind of teaching modes, an experimental study was conducted on 90 college students. Participants were assigned to one of three teaching modes: traditional classroom, online learning, and flipped classroom. Outcomes were assessed in terms of learning achievement, reaction time during test-taking, and learning satisfaction. The results showed that (1) There were significant differences in the influence of the three teaching modes on learning achievement, reaction time and learning satisfaction. (2) Students with a field-independent cognitive style showed a faster reaction time during test-taking than those with a field-dependent style. (3) The interaction between cognitive style and teaching modes was significantly related to reaction time. So, in future education, we should attach importance to the matching of teaching modes and individual differences.
作者机构：
[Liu, Tingting; Chen, Zengzhao; Liu, Hai; Zhang, Zhaoli; Chen, Yingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Liu, Tingting] Carnegie Mellon Univ, Sch Comp Sci, 5000 Forbes Ave, Pittsburgh, PA 15213 USA.;[Liu, Hai] City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China.
会议名称：
2nd International Conference on Advances in Image Processing (ICAIP) / 2nd International Conference on Software Engineering and Development (ICSED
会议时间：
JUN 16-18, 2018
会议地点：
Chengdu, PEOPLES R CHINA
会议主办单位：
[Liu, Tingting;Chen, Zengzhao;Liu, Hai;Zhang, Zhaoli;Chen, Yingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.^[Liu, Tingting] Carnegie Mellon Univ, Sch Comp Sci, 5000 Forbes Ave, Pittsburgh, PA 15213 USA.^[Liu, Hai] City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China.
作者机构：
[Hung, Jui-Long; Shelton, Brett E.] Boise State Univ, Boise, ID 83725 USA.;[Yang, Juan; Du, Xu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
会议名称：
1st International Conference of Innovative Technologies and Learning (ICITL)
会议时间：
AUG 27-30, 2018
会议地点：
Portoroz, SLOVENIA
会议主办单位：
[Shelton, Brett E.;Hung, Jui-Long] Boise State Univ, Boise, ID 83725 USA.^[Yang, Juan;Du, Xu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
会议论文集名称：
Lecture Notes in Computer Science
关键词：
Learning analytics;Academic at-risk factors;Academic success factors;Ensemble model
摘要：
This study proposes an analytic approach which combines two predictive models (the predictive model of successful students and the predictive model of at-risk students) to enhance prediction performance for use under the constraints of limited data collection. A case study was conducted to examine the effects of the model combination approach. Eight variables were collected from a data warehouse and the Learning Management System. The best model was selected based on the lowest misclassification rate in the validation dataset. The confusion matrix compares the model's performance with the following parameters: accuracy, misclassification, and sensitivity. The results show the new combination approach can capture more at-risk students than the singular predictive model, and is only suitable for the ensemble predictive algorithms.
作者：
HE binghua;CHEN zengzhao;LI gaoyang;JIANG lang;ZHANG zhao;...
期刊：
MATEC Web of Conferences,2018年173
作者机构：
National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, 430079, China;Information Construction Office Hubei University of Chinese Medicine, Wuhan, 430065, China
摘要：
Aiming at the problem of recognition effect is not stable when 2D facial expression recognition in the complex illumination and posture changes. A facial expression recognition algorithm based on RGB-D dynamic sequence analysis is proposed. The algorithm uses LBP features which are robust to illumination, and adds depth information to study the facial expression recognition. The algorithm firstly extracts 3D texture features of preprocessed RGB-D facial expression sequence, and then uses the CNN to train the dataset. At the same time, in order to verify the performance of the algorithm, a comprehensive facial expression library including 2D image, video and 3D depth information is constructed with the help of Intel RealSense technology. The experimental results show that the proposed algorithm has some advantages over other RGB-D facial expression recognition algorithms in training time and recognition rate, and has certain reference value for future research in facial expression recognition.
作者：
Du, Xu*;Zhang, Fan*;Zhang, Mingyan*;Xu, Shuai*;Liu, Mengjin*
作者机构：
[Xu, Shuai; Zhang, Mingyan; Liu, Mengjin; Du, Xu; Zhang, Fan; Xu, S] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
会议名称：
1st International Conference of Innovative Technologies and Learning (ICITL)
会议时间：
AUG 27-30, 2018
会议地点：
Portoroz, SLOVENIA
会议主办单位：
[Du, Xu;Zhang, Fan;Zhang, Mingyan;Xu, Shuai;Liu, Mengjin] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
会议论文集名称：
Lecture Notes in Computer Science
关键词：
The result integration mechanism;The crowd wisdom;Task result confidence;User confidence
摘要：
Correlating massive resources with knowledge points can help to achieve effective aggregation of resources and to improve learners learning efficiency and learning experience. This paper proposes a result integration mechanism based on the crowd wisdom to determine the association of learning resources and knowledge points, and ensure the final annotation result has certain credibility. Accordingly, we propose a user confidence to evaluate the user's ability to complete the tasks. The experimental results show that the proposed algorithms improve the accuracy and efficiency comparing with the majority voting method, and algorithm to estimate user's confidence can converge to actual value efficiently.
期刊：
2018 International Symposium on Educational Technology (ISET),2018年:8-12
通讯作者：
Xu, Jian
作者机构：
[Xu, Jian; He, RanRan; Zhang, Dan; Zhou, Peng] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
通讯机构：
[Xu, Jian] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
会议名称：
International Symposium on Educational Technology (ISET)
会议时间：
JUL 31-AUG 02, 2018
会议地点：
Kansai Univ, Osaka, JAPAN
会议主办单位：
Kansai Univ
关键词：
Learning Cyber Space;usage intention;teachers of primary school;regression
摘要：
The trend of using Learning Cyber Space is now rapidly expanding in China, which is expected to change the teaching and learning mode in primary and secondary school. Teachers' usage plays a key role in promoting the LCS. However, the teachers' registering rate of LCS is relatively high while the actual usage rate is low. The purpose of this study is to verified factors including learning resource, user-interface and function, perceived ease of use that affected primary school teachers' use of LCS. The result shown that user-interface and function and perceived ease of use have significant influence on the primary school teachers' use of LCS. Perceived ease of use was found as the most significant factor for usage of primary school teachers' LCS. Learning resource, however, has little impact on the primary school teachers' use of LCS. Implications of this finding are also discussed, which could provide some suggestions for the future development of LCS.
摘要：
With the popularization development of MOOC platform, the number of online courses grows rapidly. Efficient and appropriate course recommendation can improve learning efficiency. Traditional recommendation system is applied to the closed educational environment in which the quantity of courses and users is relatively stable. Recommendation model and algorithm cannot directly be applied to MOOC platform efficiently. With the light of the characteristics of MOOC platform, MCRS proposed in this paper has made great improvement in the course recommendation model and recommendation algorithm. MCRS is based on distributed computation framework. The basic algorithm of MCRS is distributed association rules mining algorithm, which based on the improvement of Apriori algorithm. In addition, it is useful to mine the hidden courses rules in course enrollment data. Firstly, the data is pre-processed into a standard form by Hadoop. It aims to improve the efficiency of the basic algorithm. Then it mines association rules of the standard data by Spark. Consequently, course recommendation information is transferred into MySQL through Sqoop, which makes timely feedback and improves user's courses retrieval efficiency. Finally, to validate the efficiency of MCRS, a series of experiments are carried out on Hadoop and Spark, and the results shows that MCRS is more efficient than traditional Apriori algorithm and Apriori algorithm based on Hadoop, and the MCRS is suitable for current MOOC platform.
