Pub Date : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105366
P. Netinant, Apichaya Mingkhwan, Meennapa Rakhiran
With the increasing prevalence of computer technology, interaction through the computer has become a significant challenge for certain groups, such as the elderly, disabled, and students. Hand sign recognition has emerged as a promising solution in recent years, as it offers a natural and adaptable means of human-machine interaction, particularly in educational contexts. However, real-time hand gesture recognition is a complex system development task that requires advanced technology and expertise. To address this issue, we propose a system architecture and software configuration for developing hand sign recognition based on the internet of things (IoT). In the experiment, a Raspberry Pi with a camera, Python programming, and Open-Source Computer Vision (OpenCV) software were used to develop an accurate system for detecting, recognizing, and interpreting two-hand gesture recognition in the context of human-IoT interaction. The project's primary focus is improving the accuracy of hand sign gesture recognition in real-time systems. The proposed system contributes to facilitating friendly and adaptable human-computer interaction, especially in educational services. In addition, the research result enables better computer interactions for the elderly and disabled, thus promoting greater inclusivity and accessibility in the technology industry.
{"title":"Two-Hand Gesture Recognition for User Information Interaction based on Internet of Educational Things","authors":"P. Netinant, Apichaya Mingkhwan, Meennapa Rakhiran","doi":"10.1109/ECEI57668.2023.10105366","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105366","url":null,"abstract":"With the increasing prevalence of computer technology, interaction through the computer has become a significant challenge for certain groups, such as the elderly, disabled, and students. Hand sign recognition has emerged as a promising solution in recent years, as it offers a natural and adaptable means of human-machine interaction, particularly in educational contexts. However, real-time hand gesture recognition is a complex system development task that requires advanced technology and expertise. To address this issue, we propose a system architecture and software configuration for developing hand sign recognition based on the internet of things (IoT). In the experiment, a Raspberry Pi with a camera, Python programming, and Open-Source Computer Vision (OpenCV) software were used to develop an accurate system for detecting, recognizing, and interpreting two-hand gesture recognition in the context of human-IoT interaction. The project's primary focus is improving the accuracy of hand sign gesture recognition in real-time systems. The proposed system contributes to facilitating friendly and adaptable human-computer interaction, especially in educational services. In addition, the research result enables better computer interactions for the elderly and disabled, thus promoting greater inclusivity and accessibility in the technology industry.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129924259","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105359
Qingtian Liu, Yuanyuan Li
The course of spatial sense of scale is the main part of the basic course of landscape planning and design. The project is included in the course module on the spatial sense of the scale of landscape design with immersive VR. The content describes the design, function, use, and teaching of an environmental design application to evaluate the students' sense of spatial scale and their feelings about different scale spatial structures. The experimental results show that this course can realistically simulate the spatial characteristics of real scenes, thus creating a VR environment for the experience of different indoor and outdoor 3D scenes and helping students develop an accurate sense of spatial scale. The results also show that the participant's evaluation of the vertical distance of the spatial structure is relatively accurate, while the evaluation of the user's density distance is relatively inaccurate. In the sense of spatial scale, the above squares need more open air, while the length of the trails below 4 m needs to be concentrated. For parks and hiking trails, the density of 10 m2/person is easy to feel congested, and the density of 15 m2/person is relatively suitable. Finally, the advantages and disadvantages of this design model are discussed on how to provide the opportunities and problems in the immersive virtual immersion design for the application of planning and design courses.
{"title":"Design and Application of Landscape Design Space Perception Teaching Based on VR Virtual Environment Technology","authors":"Qingtian Liu, Yuanyuan Li","doi":"10.1109/ECEI57668.2023.10105359","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105359","url":null,"abstract":"The course of spatial sense of scale is the main part of the basic course of landscape planning and design. The project is included in the course module on the spatial sense of the scale of landscape design with immersive VR. The content describes the design, function, use, and teaching of an environmental design application to evaluate the students' sense of spatial scale and their feelings about different scale spatial structures. The experimental results show that this course can realistically simulate the spatial characteristics of real scenes, thus creating a VR environment for the experience of different indoor and outdoor 3D scenes and helping students develop an accurate sense of spatial scale. The results also show that the participant's evaluation of the vertical distance of the spatial structure is relatively accurate, while the evaluation of the user's density distance is relatively inaccurate. In the sense of spatial scale, the above squares need more open air, while the length of the trails below 4 m needs to be concentrated. For parks and hiking trails, the density of 10 m2/person is easy to feel congested, and the density of 15 m2/person is relatively suitable. Finally, the advantages and disadvantages of this design model are discussed on how to provide the opportunities and problems in the immersive virtual immersion design for the application of planning and design courses.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123283268","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105317
Xi Luan
Spoken authentic corpus is of great practical significance for the dynamic research of language and teaching and acquisition of spoken French. Recently, the establishment of the spoken French corpus and empirical research based on spoken authentic corpus has become the direction of language research. Thus, we introduce the establishment and application of AI speech recognition technology in a small French spoken corpus in detail as a platform to conduct an empirical study on the phenomenon of code-switching in French classroom teachers' discourse. In the research, we find that the corpus is objective and effective in revealing the types, motivations, and functions of code-switching in French classroom teachers' discourse. The corpus also provides a reference for future research on the teaching of spoken French based on the corpus.
{"title":"Development and Application of Spoken French Corpus Based on AI Speech Recognition","authors":"Xi Luan","doi":"10.1109/ECEI57668.2023.10105317","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105317","url":null,"abstract":"Spoken authentic corpus is of great practical significance for the dynamic research of language and teaching and acquisition of spoken French. Recently, the establishment of the spoken French corpus and empirical research based on spoken authentic corpus has become the direction of language research. Thus, we introduce the establishment and application of AI speech recognition technology in a small French spoken corpus in detail as a platform to conduct an empirical study on the phenomenon of code-switching in French classroom teachers' discourse. In the research, we find that the corpus is objective and effective in revealing the types, motivations, and functions of code-switching in French classroom teachers' discourse. The corpus also provides a reference for future research on the teaching of spoken French based on the corpus.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131457669","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105373
Zhouxiang Shan, Feng Liang
Using different ways of correlation, the characteristics based on the differences between knowledge points, core predicates, and discourse characters are investigated. The relevant content of sports textbooks is used to train the word2vec relationship model with the similarity between the statistical knowledge points. As a result, the features are obtained based on the noun vector along with in-depth meaning-related information. The extracted features are used to train the sorter method of support vector machine (SVM) and K-nearest neighbor (KNN) for the analysis of the relationship between knowledge points. According to the experimental data, the specific content of the physical education textbook is selected. Compared with the traditional methods, the refined method can effectively improve the F score of the correlation. Finally, the new association extraction method is used to establish the knowledge image of sports discipline. The experimental results show that this method can effectively extract the knowledge points from the physical education curriculum textbooks.
{"title":"Extraction of STEM Knowledge Relationship in Physical Education Course Textbooks Based on KNN","authors":"Zhouxiang Shan, Feng Liang","doi":"10.1109/ECEI57668.2023.10105373","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105373","url":null,"abstract":"Using different ways of correlation, the characteristics based on the differences between knowledge points, core predicates, and discourse characters are investigated. The relevant content of sports textbooks is used to train the word2vec relationship model with the similarity between the statistical knowledge points. As a result, the features are obtained based on the noun vector along with in-depth meaning-related information. The extracted features are used to train the sorter method of support vector machine (SVM) and K-nearest neighbor (KNN) for the analysis of the relationship between knowledge points. According to the experimental data, the specific content of the physical education textbook is selected. Compared with the traditional methods, the refined method can effectively improve the F score of the correlation. Finally, the new association extraction method is used to establish the knowledge image of sports discipline. The experimental results show that this method can effectively extract the knowledge points from the physical education curriculum textbooks.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125419950","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105259
Ye Yang, Xuebing Li
Using the Gradient boost decision tree (GBDT) algorithm, the classification problem of children's cognitive level of mathematical knowledge is transformed into the classification problem in machine learning. Kindergarten children's cognitive difficulty with different mathematical knowledge modules is different. Each knowledge module can be abstracted into several basic skill points, and all knowledge modules and basic skill points form a knowledge skill matrix. In this study, based on the teaching textbooks of a large class in a kindergarten, all mathematical knowledge modules are decomposed into several basic skill points, and the knowledge skill matrix is constructed. Then, based on the children's learning data collected in the actual teaching activities, two classification models of children's mathematical knowledge and skills are constructed by using the GBDT algorithm. The two models can be applied to practical teaching. Mining children's cognitive law of mathematical knowledge help teachers design reasonable psychological intervention mechanisms and improve children's cognition level.
{"title":"Gradient Boost Decision Tree-based Research on Kindergarten Children's Cognitive Law of Mathematical Knowledge","authors":"Ye Yang, Xuebing Li","doi":"10.1109/ECEI57668.2023.10105259","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105259","url":null,"abstract":"Using the Gradient boost decision tree (GBDT) algorithm, the classification problem of children's cognitive level of mathematical knowledge is transformed into the classification problem in machine learning. Kindergarten children's cognitive difficulty with different mathematical knowledge modules is different. Each knowledge module can be abstracted into several basic skill points, and all knowledge modules and basic skill points form a knowledge skill matrix. In this study, based on the teaching textbooks of a large class in a kindergarten, all mathematical knowledge modules are decomposed into several basic skill points, and the knowledge skill matrix is constructed. Then, based on the children's learning data collected in the actual teaching activities, two classification models of children's mathematical knowledge and skills are constructed by using the GBDT algorithm. The two models can be applied to practical teaching. Mining children's cognitive law of mathematical knowledge help teachers design reasonable psychological intervention mechanisms and improve children's cognition level.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126506128","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105417
Peijiang Chen, Hu Han, Mei Zhang
Online courses have been developed rapidly due to their advantages of being free from time and space constraints and sharing, and have been widely used in higher education. Improving the learning effect of online courses is also one of the difficulties of research in the era of big data. Taking the automobile theory online course on the Zhihuishu platform as an example, we analyze the influencing factors of online courses learning and establish a linear regression prediction model with correlation analysis and linear regression methods by selecting and extracting the data of students' main learning behaviors in the learning process. The results show that the number of student online course logins, the number of interactions. and test scores are the key indicators to predict their learning performance. On this basis, countermeasures and suggestions are put forward to improve the learning effect of online courses.
{"title":"Learning Effect Evaluation of Online Course Based on Linear Regression Analysis","authors":"Peijiang Chen, Hu Han, Mei Zhang","doi":"10.1109/ECEI57668.2023.10105417","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105417","url":null,"abstract":"Online courses have been developed rapidly due to their advantages of being free from time and space constraints and sharing, and have been widely used in higher education. Improving the learning effect of online courses is also one of the difficulties of research in the era of big data. Taking the automobile theory online course on the Zhihuishu platform as an example, we analyze the influencing factors of online courses learning and establish a linear regression prediction model with correlation analysis and linear regression methods by selecting and extracting the data of students' main learning behaviors in the learning process. The results show that the number of student online course logins, the number of interactions. and test scores are the key indicators to predict their learning performance. On this basis, countermeasures and suggestions are put forward to improve the learning effect of online courses.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114272937","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105382
Xinge Zhang
With the rapid increase of Internet application, a large volume of public comment data is accrued on the network platform and brings a great opportunity to the public comment analysis using big data technology. Similar to the new network applications such as cloud computing, the Internet of Things (IoT), the mobile Internet, and big data technology attract research interest based on computer and network advancements. However, the research on big data-driven online media public comment is still in the initial stage, and the relevant analysis model and its implementation plans remain to be further clarified. In this context, this study is put forward to clarify the dimensional model of network media public comment information based on big data and its action mechanism, and then express the implementation plans of the network media public comment analysis model based on big data. The model includes information collection technology, text clustering technology, and information preprocessing technology. The research results of this work is helpful to efficiently mine and identify the public comment information from the massive data in the era of big data and is referable for the public comment supervision and guidance in the network media.
{"title":"Public Comment Analysis Model of Network Media Based on Big Data Mining and Implementation Plans","authors":"Xinge Zhang","doi":"10.1109/ECEI57668.2023.10105382","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105382","url":null,"abstract":"With the rapid increase of Internet application, a large volume of public comment data is accrued on the network platform and brings a great opportunity to the public comment analysis using big data technology. Similar to the new network applications such as cloud computing, the Internet of Things (IoT), the mobile Internet, and big data technology attract research interest based on computer and network advancements. However, the research on big data-driven online media public comment is still in the initial stage, and the relevant analysis model and its implementation plans remain to be further clarified. In this context, this study is put forward to clarify the dimensional model of network media public comment information based on big data and its action mechanism, and then express the implementation plans of the network media public comment analysis model based on big data. The model includes information collection technology, text clustering technology, and information preprocessing technology. The research results of this work is helpful to efficiently mine and identify the public comment information from the massive data in the era of big data and is referable for the public comment supervision and guidance in the network media.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117009411","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105265
Ning Fang
After the outbreak of the epidemic, the employment situation has undergone tremendous changes, and college students have encountered many difficulties in finding jobs. This study is conducted to understand the employment trends of college students across the country in the post-epidemic era. We take Shandong Province as a sample to conduct a questionnaire survey. Data is collected to analyze how to use big data technology to guide college graduates in employment. By establishing big data platforms, a standardized response system for the employment of college students is constructed and a model is built to guide the employment, and find out the countermeasures of employment.
{"title":"Research and Countermeasures on Changes in Employment Trends of College Students in Post-epidemic Era under Big Data Mining","authors":"Ning Fang","doi":"10.1109/ECEI57668.2023.10105265","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105265","url":null,"abstract":"After the outbreak of the epidemic, the employment situation has undergone tremendous changes, and college students have encountered many difficulties in finding jobs. This study is conducted to understand the employment trends of college students across the country in the post-epidemic era. We take Shandong Province as a sample to conduct a questionnaire survey. Data is collected to analyze how to use big data technology to guide college graduates in employment. By establishing big data platforms, a standardized response system for the employment of college students is constructed and a model is built to guide the employment, and find out the countermeasures of employment.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125376804","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105395
P. Netinant, Supanut Chuencheevajaroen, Meennapa Rakhiran
Recent growth in game development has attracted the interest of software designers and developers for game development. Developing a game involves a variety of approaches and resources. Gamification-based learning is a challenging development. Thus, this research aims to demonstrate the design and development of an educational English-learning game using object-oriented techniques run on a small single-board computer. In this research, we proposed the Ario game inspired by a Mario-like game to support English language learning with an educational innovation. The Ario game was created and developed using object-oriented methodology, Python programming, and a Raspberry Pi system. Python's library for game development is extensive. Pygame is a Python module designed for the development of game applications. This benefit of Pygame is to create games with unique features. Rapid application development (RAD) is the most compatible approach with the features of game development software model design and development. The software functionality of the Ario game is decomposed into components to improve software quality.
{"title":"Ario Game: Learning English Game Development with Python on Raspberry Pi","authors":"P. Netinant, Supanut Chuencheevajaroen, Meennapa Rakhiran","doi":"10.1109/ECEI57668.2023.10105395","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105395","url":null,"abstract":"Recent growth in game development has attracted the interest of software designers and developers for game development. Developing a game involves a variety of approaches and resources. Gamification-based learning is a challenging development. Thus, this research aims to demonstrate the design and development of an educational English-learning game using object-oriented techniques run on a small single-board computer. In this research, we proposed the Ario game inspired by a Mario-like game to support English language learning with an educational innovation. The Ario game was created and developed using object-oriented methodology, Python programming, and a Raspberry Pi system. Python's library for game development is extensive. Pygame is a Python module designed for the development of game applications. This benefit of Pygame is to create games with unique features. Rapid application development (RAD) is the most compatible approach with the features of game development software model design and development. The software functionality of the Ario game is decomposed into components to improve software quality.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128307905","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 : 2023-02-03DOI: 10.1109/ECEI57668.2023.10105325
P. Chaipidech, N. Srisawasdi
Over the last few years, 360° virtual learning environment has been introduced as an educational tool. Educators started embedding the related technology into their classes. In general, this technology is recognized as a suitable tool to illustrate real-context experiences when the reality is hardly accessible, for instance, due to safety issues. However, the pedagogical implementation of these learning media has not been widely explored, especially in the context of higher education. In this study, we aimed to develop the 360° virtual learning environment and design the pedagogical usage to support learners before they are in the context of in-field inquiry activity. The 29 preservice science teachers were recruited in this study. After participating in the 360° virtual learning environment and the out-of-class inquiry activity, the perception questionnaire was administrated. Moreover, they were asked to provide feedback regarding their learning experiences. The quantitative and qualitative analysis, including arithmetic means, standard deviation, and content analysis, is used to analyze the learners' perceptions and self-reflection, respectively. The results and findings of this study are discussed to apply the 360° virtual learning environment to the learning domain.
{"title":"Integrating 360° Virtual Learning Environment to Support Out-Of-Class Inquiry Activity for Preservice Teachers: A Preliminary Study","authors":"P. Chaipidech, N. Srisawasdi","doi":"10.1109/ECEI57668.2023.10105325","DOIUrl":"https://doi.org/10.1109/ECEI57668.2023.10105325","url":null,"abstract":"Over the last few years, 360° virtual learning environment has been introduced as an educational tool. Educators started embedding the related technology into their classes. In general, this technology is recognized as a suitable tool to illustrate real-context experiences when the reality is hardly accessible, for instance, due to safety issues. However, the pedagogical implementation of these learning media has not been widely explored, especially in the context of higher education. In this study, we aimed to develop the 360° virtual learning environment and design the pedagogical usage to support learners before they are in the context of in-field inquiry activity. The 29 preservice science teachers were recruited in this study. After participating in the 360° virtual learning environment and the out-of-class inquiry activity, the perception questionnaire was administrated. Moreover, they were asked to provide feedback regarding their learning experiences. The quantitative and qualitative analysis, including arithmetic means, standard deviation, and content analysis, is used to analyze the learners' perceptions and self-reflection, respectively. The results and findings of this study are discussed to apply the 360° virtual learning environment to the learning domain.","PeriodicalId":176611,"journal":{"name":"2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130160020","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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