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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ISET52350.2021.00019
M. Pokorný
A pandemic situation connected with a spread of COVID-19 has significantly changed methods of teaching at universities. Previously unimaginable ban on face-to-face teaching has become a reality overnight. At best, a number of students present in a class was significantly limited, at worst, face-to-face lessons were completely banned. Naturally, there was a danger of significant decrease of student’s knowledge. The paper deals with efficient utilization of e-learning in teaching Combinatorics and Data Processing at the Facuity of Education, Tmava University. We compare two different methods of learning: blended learning and e-learning. The results of the experiment prove that the ban of face-to-face lessons does not automatically mean the decrease of student’s knowledge. Thus, e-learning has potential to overcome problems associated with COVID-19 pandemic situation at universities.
{"title":"Video Lessons and E-learning Can Overcome Ban of Face-to-face Lessons in Teaching Mathematics","authors":"M. Pokorný","doi":"10.1109/ISET52350.2021.00019","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00019","url":null,"abstract":"A pandemic situation connected with a spread of COVID-19 has significantly changed methods of teaching at universities. Previously unimaginable ban on face-to-face teaching has become a reality overnight. At best, a number of students present in a class was significantly limited, at worst, face-to-face lessons were completely banned. Naturally, there was a danger of significant decrease of student’s knowledge. The paper deals with efficient utilization of e-learning in teaching Combinatorics and Data Processing at the Facuity of Education, Tmava University. We compare two different methods of learning: blended learning and e-learning. The results of the experiment prove that the ban of face-to-face lessons does not automatically mean the decrease of student’s knowledge. Thus, e-learning has potential to overcome problems associated with COVID-19 pandemic situation at universities.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"26 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":"126832164","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}
Pub Date : 2021-08-01DOI: 10.1109/ISET52350.2021.00043
Hesiqi Bin, Yi Zhang, Xueyuan Qin, Jingsi Ma
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.
{"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}
Pub Date : 2021-08-01DOI: 10.1109/ISET52350.2021.00024
Luying Qiu, Mingxia Hao, T. Long
The outbreak of COVID-19 since the end of 2019 led to large-scale online learning among college students. Because of the overlap of learning and home environment at home, students need to play a variety of roles. With the Social Role Theory as the theoretical framework, this qualitative case study had an in-depth investigation on seven college students’ current self-role and the current learning situation at home during COVID-19. Findings highlighted that the students mainly faced the following three role conflicts: First, the conflicts caused by difficulties in adapting to multiple roles of the students. Second, the conflicts caused by different role expectations on the students’ behaviors. Third, the conflicts caused by insufficient role comprehension on role cognition. This study also revealed that these role conflicts would have a certain negative impact on students’ learning and living. Implications are discussed in detail.
{"title":"Role Conflicts at Home: A Qualitative Case Study on College Students’ Online Learning During the COVID-19 Based on the Social Role Theory","authors":"Luying Qiu, Mingxia Hao, T. Long","doi":"10.1109/ISET52350.2021.00024","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00024","url":null,"abstract":"The outbreak of COVID-19 since the end of 2019 led to large-scale online learning among college students. Because of the overlap of learning and home environment at home, students need to play a variety of roles. With the Social Role Theory as the theoretical framework, this qualitative case study had an in-depth investigation on seven college students’ current self-role and the current learning situation at home during COVID-19. Findings highlighted that the students mainly faced the following three role conflicts: First, the conflicts caused by difficulties in adapting to multiple roles of the students. Second, the conflicts caused by different role expectations on the students’ behaviors. Third, the conflicts caused by insufficient role comprehension on role cognition. This study also revealed that these role conflicts would have a certain negative impact on students’ learning and living. Implications are discussed in detail.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"55 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":"128957741","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}
Pub Date : 2021-08-01DOI: 10.1109/ISET52350.2021.00011
Xiaojing Weng, M. Jong, Thomas K. F. Chiu
Collaboration is one of the vital capabilities for students in the twenty-first century. Authentic problem solving and mentoring have been recognised as efficient instructional means to promote learners’ multiple competencies. In the field, there have been studies investigating the development of collaborative skills via engaging students in authentic problem-solving tasks and/or mentoring activities. However, rare work has compared these two instructional strategies: authentic problem solving merely and with the infusion of mentorship, in terms of the effectiveness of fostering students’ collaboration. To fill the research gap, this quasi-experimental study (n=63) aims to evaluate the effectiveness of the approaches of Authentic Problem Solving (APS) and Mentor-scaffolded Authentic Problem Solving (MAPS) in the context of STEM making. Results reveal that the MAPS students learning outperformed the APS students, in terms of collaboration. Implications for future work are discussed in this paper as well.
{"title":"STEM Making: Fostering Secondary Students’ Collaborative Skills with Mentor-scaffolded Authentic Problem Solving","authors":"Xiaojing Weng, M. Jong, Thomas K. F. Chiu","doi":"10.1109/ISET52350.2021.00011","DOIUrl":"https://doi.org/10.1109/ISET52350.2021.00011","url":null,"abstract":"Collaboration is one of the vital capabilities for students in the twenty-first century. Authentic problem solving and mentoring have been recognised as efficient instructional means to promote learners’ multiple competencies. In the field, there have been studies investigating the development of collaborative skills via engaging students in authentic problem-solving tasks and/or mentoring activities. However, rare work has compared these two instructional strategies: authentic problem solving merely and with the infusion of mentorship, in terms of the effectiveness of fostering students’ collaboration. To fill the research gap, this quasi-experimental study (n=63) aims to evaluate the effectiveness of the approaches of Authentic Problem Solving (APS) and Mentor-scaffolded Authentic Problem Solving (MAPS) in the context of STEM making. Results reveal that the MAPS students learning outperformed the APS students, in terms of collaboration. Implications for future work are discussed in this paper as well.","PeriodicalId":448075,"journal":{"name":"2021 International Symposium on Educational Technology (ISET)","volume":"17 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":"128569281","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}
Pub Date : 2021-08-01DOI: 10.1109/ISET52350.2021.00041
B. Wong, K. Li
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.
本文对智能学习的好处和挑战进行了全面的综述。本次综述共收录2011 -2020年间发表的155篇论文，数据来源于Web of Science、Scopus和ProQuest三个出版数据库。它涵盖了研究中证明的智能学习的好处，研究中解决的智能学习的挑战，以及有待解决的剩余挑战。从研究总结，智能学习的好处包括三个主要方面-教学支持，学生和教师的积极看法，以及改善学习成果。经常报道的好处在于学习兴趣和动机的增强，学习经验的丰富，以及互动和协作的增加。挑战的主要领域集中在学习风格和状态的识别，提供适应性学习路径和内容推荐，以及真实的学习体验。在未来的工作中也有一些挑战需要解决，特别是教师的能力和培训，以及学生和教师对智能学习的接受程度。
{"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}
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