2021 International Symposium on Educational Technology (ISET)最新文献_第6页

Research on Machine Understanding Math Word Problems: From the Perspective of Discourse Comprehension Models 基于话语理解模型的机器理解数学单词问题研究

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00037

Jingxiu Huang, Qingtang Liu, Yunxiang Zheng, Linjing Wu, Yigang Ding, Li Huang

{"title":"Research on Machine Understanding Math Word Problems: From the Perspective of Discourse Comprehension Models","authors":"Jingxiu Huang, Qingtang Liu, Yunxiang Zheng, Linjing Wu, Yigang Ding, Li Huang","doi":"10.1109/ISET52350.2021.00037","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00037","url":null,"abstract":"With the rapid development of artificial intelligence (Al) technology, machine understanding math word problems (MWPs) has received growing attention. However, existing methods of automatic understanding MWPs are hardly integrated into cognitive intelligent systems used for individual learning. To address the integration problem, this paper firstly clarified the relationship between understanding MWPs and discourse comprehension. According to the trait of discourse comprehension models, the existing methods were divided into knowledge schema-based methods and mental processing-based methods. Then we shortly presented the construction-integration model and proposed a conceptual framework for machine understanding MWPs. The proposed conceptual framework was established from long and short-term memory, cognitive computing services, formal representation models, and human-computer interaction. Finally, we draw a conclusion that integrating cognitive models of human understanding discourse into the process of machine understanding MWPs is conducive to developing a humanized cognitive intelligence system for personalized learning.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125887754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Video Lessons and E-learning Can Overcome Ban of Face-to-face Lessons in Teaching Mathematics 视频教学和网络教学可以克服面对面教学的障碍

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00019

M. Pokorný

引用次数: 1

Research on the Influencing Factors of College Students’ Deep Learning in Blended Learning Environment 混合式学习环境下大学生深度学习的影响因素研究

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00043

Hesiqi Bin, Yi Zhang, Xueyuan Qin, Jingsi Ma

{"title":"Research on the Influencing Factors of College Students’ Deep Learning in Blended Learning Environment","authors":"Hesiqi Bin, Yi Zhang, Xueyuan Qin, Jingsi Ma","doi":"10.1109/ISET52350.2021.00043","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00043","url":null,"abstract":"With the continuous integration and development of information technology and education, blended learning methods have emerged. Blended learning environment is a combination of an online learning environment and an offline traditional learning environment. In the blended learning environment, students gradually occupy the dominant position in learning and actively study by themselves. To better understand the deep learning of college students in the blended learning environment, the article combines literature research and scholars’ opinions to determine the five key factors that affect college students’ deep learning in the blended learning environment. On the basis of it, research hypotheses are put forward and a structural equation model is established. In the questionnaire survey, a total, of 508 college students responded to the survey. The results of this study show that self-management ability, initiative cooperation ability, learning motivation, e-learning environment, and communication frequency all have a positive effect on deep learning. Besides, all of the first four significantly affect deep learning. Finally, based on the research conclusions, relevant suggestions are put forward to improve the deep learning level of college students in the blended learning environment.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"35 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114028320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Role Conflicts at Home: A Qualitative Case Study on College Students’ Online Learning During the COVID-19 Based on the Social Role Theory 家庭角色冲突:基于社会角色理论的新型冠状病毒肺炎期间大学生在线学习的定性案例研究

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00024

Luying Qiu, Mingxia Hao, T. Long

引用次数: 1

STEM Making: Fostering Secondary Students’ Collaborative Skills with Mentor-scaffolded Authentic Problem Solving STEM制作:在导师指导下培养中学生的协作能力

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00011

Xiaojing Weng, M. Jong, Thomas K. F. Chiu

引用次数: 0

The Benefits and Challenges of Smart Learning: A Literature Review 智能学习的好处和挑战:文献综述

2021 International Symposium on Educational Technology (ISET) Pub Date : 2021-08-01 DOI: 10.1109/ISET52350.2021.00041

B. Wong, K. Li

{"title":"The Benefits and Challenges of Smart Learning: A Literature Review","authors":"B. Wong, K. Li","doi":"10.1109/ISET52350.2021.00041","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00041","url":null,"abstract":"This paper presents a comprehensive review of the benefits and challenges of smart learning. The review includes a total of 155 articles published in 2011 —2020, which were collected from three publication databases, namely Web of Science, Scopus and ProQuest. It covers the benefits of smart learning as evidenced in the studies, the challenges to smart learning addressed in the studies, and the remaining challenges to be resolved. As summarised from the studies, the benefits of smart learning cover three major areas — teaching and learning support, positive perceptions from students and teachers, and improved learning outcomes. The benefits frequently reported lie in the enhancement of learning interests and motivation, the enrichment of learning experiences, and the increase of interaction and collaboration. The major areas of challenges focus on the identification of learning styles and status, the provision of adaptive learning path and content recommendation, as well as authentic learning experiences. There are also areas of challenges to be addressed in future work, in particular teachers’ competence and training, and the acceptance of smart learning by students and teachers.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129228830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0