Pub Date : 2023-06-07DOI: 10.3991/ijet.v18i11.38653
A. Assainova, D. Abykenova, Zhanara T. Aubakirova, Kymbatsha M. Mukhamediyeva, Kymbat A. Kozhageldinova
Computational thinking is an important and necessary part of a modern person’s thinking. It has been proven that the development of this way of thinking in students with mental disabilities allows them to navigate quickly in the modern world, identify problems and create complex solutions. Online schooling during the COVID-19 pandemic demonstrated the possibilities of the usage of web technologies in the education of children with mental disabilities. This study aims to evaluate the impact of web technologies on the development of computational thinking of students with mental disorders. The experiment involved 14 students aged 8-12 and 4 tutors. For 8 weeks children were trained in computational thinking and computer science. Assessment of computational thinking was performed with cCT-test by El-Hamamsi et al. before and after the experiment. After conducting computer science lessons using web technologies the respondents showed a higher level of computational thinking (M=15,7, SD=3,69), compared to the results of preliminary testing (M=5,93, SD=2,3). Web technologies can significantly increase the effectiveness of inclusive pedagogy, which establishes the importance of integrating web technologies into the teaching system in inclusive classes of general education schools.
{"title":"Web Technologies in the Development of Computational Thinking of Students with Mental Disabilities","authors":"A. Assainova, D. Abykenova, Zhanara T. Aubakirova, Kymbatsha M. Mukhamediyeva, Kymbat A. Kozhageldinova","doi":"10.3991/ijet.v18i11.38653","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.38653","url":null,"abstract":"Computational thinking is an important and necessary part of a modern person’s thinking. It has been proven that the development of this way of thinking in students with mental disabilities allows them to navigate quickly in the modern world, identify problems and create complex solutions. Online schooling during the COVID-19 pandemic demonstrated the possibilities of the usage of web technologies in the education of children with mental disabilities. This study aims to evaluate the impact of web technologies on the development of computational thinking of students with mental disorders. The experiment involved 14 students aged 8-12 and 4 tutors. For 8 weeks children were trained in computational thinking and computer science. Assessment of computational thinking was performed with cCT-test by El-Hamamsi et al. before and after the experiment. After conducting computer science lessons using web technologies the respondents showed a higher level of computational thinking (M=15,7, SD=3,69), compared to the results of preliminary testing (M=5,93, SD=2,3). Web technologies can significantly increase the effectiveness of inclusive pedagogy, which establishes the importance of integrating web technologies into the teaching system in inclusive classes of general education schools.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70111820","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.38923
Otman Jaber, Osama Swidan, Michael N. Fried
This study reports on findings of two design cycles of augmented reality environment intended to engage high school students in covariational reasoning. The study used a designed-based research method to develop and improve the learning environment. In this report, we present the initial design and discuss how it promoted students' engagement at elementary levels of covariation. Following this first cycle, we introduced a redesigned learning environment. We provide evidence of how the new design in the second cycle promoted students' engagement at advanced levels of covariational reasoning. Six groups of three 15- to 17-year-old students participated in the research. Using AR headsets, each group carried out two activities well-suited, in principle, to covariational reasoning. The students' interactions were video-recorded, and the theory of semiotic representation was used to analyze the degree of their engagement in covariational reasoning. The design emphasized multiple representations generally, and the compatibility between the explored phenomenon and its mathematical representations, specifically. Findings show that the design considerations in the second design cycle significantly improved the students' engagement at different levels of covariation, including advanced levels. Keywords—covariational reasoning, representations, design principles
{"title":"Design Considerations in Developing an Augmented Reality Learning Environment for Engaging Students in Covariational Reasoning","authors":"Otman Jaber, Osama Swidan, Michael N. Fried","doi":"10.3991/ijet.v18i11.38923","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.38923","url":null,"abstract":"This study reports on findings of two design cycles of augmented reality environment intended to engage high school students in covariational reasoning. The study used a designed-based research method to develop and improve the learning environment. In this report, we present the initial design and discuss how it promoted students' engagement at elementary levels of covariation. Following this first cycle, we introduced a redesigned learning environment. We provide evidence of how the new design in the second cycle promoted students' engagement at advanced levels of covariational reasoning. Six groups of three 15- to 17-year-old students participated in the research. Using AR headsets, each group carried out two activities well-suited, in principle, to covariational reasoning. The students' interactions were video-recorded, and the theory of semiotic representation was used to analyze the degree of their engagement in covariational reasoning. The design emphasized multiple representations generally, and the compatibility between the explored phenomenon and its mathematical representations, specifically. Findings show that the design considerations in the second design cycle significantly improved the students' engagement at different levels of covariation, including advanced levels. \u0000 \u0000Keywords—covariational reasoning, representations, design principles","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41538280","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.41083
Y. Zhang
Analysis of student learning behavior characteristics is an important means for educators to better understand students and improve the quality and effectiveness of teaching in the field of education. It is necessary to refer to students' cognitive levels for analysis of student learning behavior characteristics. However, existing algorithms only focus on the overall performance and grades of students, ignoring the individual differences in learning cognitive levels among students, which affects the accuracy of the analysis results. Therefore, this paper conducts research on student online learning behavior characteristics based on a multidimensional cognitive model. Firstly, a multidimensional and multilevel model for evaluating students' cognitive levels is constructed, and the process of evaluating students' cognitive levels is sustainable and can be adjusted in real-time as students' cognitive levels change. By considering the differences in evaluation levels and students' cognitive levels, targeted observation and extraction of students' online learning behavior characteristics can be achieved. A new model based on variational autoencoder neural network is proposed to perform decoupled representation of students' implicit preferences. By using a regularization term based on maximum mean difference, the model can learn independent hidden vectors sensitive to dynamic and static factors from students' online learning behavior history data and multidimensional cognitive evaluation history data. The experimental results verify the effectiveness of the constructed model.
{"title":"Student Online Learning Behavior Characteristics Based on Multidimensional Cognitive Model","authors":"Y. Zhang","doi":"10.3991/ijet.v18i11.41083","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.41083","url":null,"abstract":"Analysis of student learning behavior characteristics is an important means for educators to better understand students and improve the quality and effectiveness of teaching in the field of education. It is necessary to refer to students' cognitive levels for analysis of student learning behavior characteristics. However, existing algorithms only focus on the overall performance and grades of students, ignoring the individual differences in learning cognitive levels among students, which affects the accuracy of the analysis results. Therefore, this paper conducts research on student online learning behavior characteristics based on a multidimensional cognitive model. Firstly, a multidimensional and multilevel model for evaluating students' cognitive levels is constructed, and the process of evaluating students' cognitive levels is sustainable and can be adjusted in real-time as students' cognitive levels change. By considering the differences in evaluation levels and students' cognitive levels, targeted observation and extraction of students' online learning behavior characteristics can be achieved. A new model based on variational autoencoder neural network is proposed to perform decoupled representation of students' implicit preferences. By using a regularization term based on maximum mean difference, the model can learn independent hidden vectors sensitive to dynamic and static factors from students' online learning behavior history data and multidimensional cognitive evaluation history data. The experimental results verify the effectiveness of the constructed model.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43485164","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.41085
Lihua Wang
Cross-cultural teaching management in the big data environment not only enhances the quality and effectiveness of education but also promotes global cooperation and exchange in education, which has important practical significance and value. Existing methods for analyzing effectiveness and practicality are usually qualitative analysis methods. While this method emphasizes the complexity and diversity of educational phenomena, it may lead to subjectivity and instability in data processing and result presentation, affecting the reliability and objectivity of the analysis results. In this paper, a quantitative comparative analysis of the effectiveness and practicality of cross-cultural teaching management in the big data environment is conducted, which helps educators better understand the needs of students from different cultural backgrounds and develop more targeted teaching plans to improve the quality of education. First, the content of cross-cultural teaching management in the big data environment is explained, and the reasons and implementation process of the comparative analysis of effectiveness and practicality are provided. The evaluation indicators for the effectiveness and practicality of cross-cultural teaching management in the big data environment are determined, and the evaluation methods are given. Experimental analysis results are presented with examples to validate the effectiveness of the proposed method.
{"title":"Comparative Analysis of Cross-Cultural Teaching Management in Big Data Environment","authors":"Lihua Wang","doi":"10.3991/ijet.v18i11.41085","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.41085","url":null,"abstract":"Cross-cultural teaching management in the big data environment not only enhances the quality and effectiveness of education but also promotes global cooperation and exchange in education, which has important practical significance and value. Existing methods for analyzing effectiveness and practicality are usually qualitative analysis methods. While this method emphasizes the complexity and diversity of educational phenomena, it may lead to subjectivity and instability in data processing and result presentation, affecting the reliability and objectivity of the analysis results. In this paper, a quantitative comparative analysis of the effectiveness and practicality of cross-cultural teaching management in the big data environment is conducted, which helps educators better understand the needs of students from different cultural backgrounds and develop more targeted teaching plans to improve the quality of education. First, the content of cross-cultural teaching management in the big data environment is explained, and the reasons and implementation process of the comparative analysis of effectiveness and practicality are provided. The evaluation indicators for the effectiveness and practicality of cross-cultural teaching management in the big data environment are determined, and the evaluation methods are given. Experimental analysis results are presented with examples to validate the effectiveness of the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46232456","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.41079
Jun Liang, Yixin Li
The cognitive level of students is a very important factor that should be considered when constructing learning paths, however, it’s not that all students could have sufficient technical skills to participate in learning programs offered by the learning paths, so in real cases, the learning paths can hardly meet the actual learning requirements of each student. To solve this matter, this paper aims to explore a new method for constructing online learning paths based on the cognitive level assessment of college students. At first, this paper introduced a deep learning model into the assessment of college students’ cognitive level, that is, the collected data of the feedback assessment information of student learning was adopted to assess the cognitive level of students, then the paper introduced in detail the structure and principle of the proposed model. After that, this paper proposed a weighted learning method that integrates the learning paths of students with different cognitive levels to ensure the interpretability of the generated learning paths. For a specific student cognitive level on learning paths, the proposed method assigns different weights for learning paths based on history student cognitive level on each node of the learning paths, thereby planning better and easier learning paths for students to achieve their learning goals. At last, experimental results verified the validity of the constructed model and the proposed method.
{"title":"A Novel Method for Constructing Online Learning Paths Based on Cognitive Level Assessment of College Students","authors":"Jun Liang, Yixin Li","doi":"10.3991/ijet.v18i11.41079","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.41079","url":null,"abstract":"The cognitive level of students is a very important factor that should be considered when constructing learning paths, however, it’s not that all students could have sufficient technical skills to participate in learning programs offered by the learning paths, so in real cases, the learning paths can hardly meet the actual learning requirements of each student. To solve this matter, this paper aims to explore a new method for constructing online learning paths based on the cognitive level assessment of college students. At first, this paper introduced a deep learning model into the assessment of college students’ cognitive level, that is, the collected data of the feedback assessment information of student learning was adopted to assess the cognitive level of students, then the paper introduced in detail the structure and principle of the proposed model. After that, this paper proposed a weighted learning method that integrates the learning paths of students with different cognitive levels to ensure the interpretability of the generated learning paths. For a specific student cognitive level on learning paths, the proposed method assigns different weights for learning paths based on history student cognitive level on each node of the learning paths, thereby planning better and easier learning paths for students to achieve their learning goals. At last, experimental results verified the validity of the constructed model and the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48007039","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.34833
Abdullatif A. AlMunifi, Arwa Y. Aleryani
Platforms for online courses including Massive Open Online Courses (MOOCs) have become the most remarkable well-built environment for teaching and learning. Until recently the various types of online courses have been an optional and supplementary source of gaining knowledge and skills to compensate the learning lose in formal education, either for students or professionals. COVID-19 brought unprecedented disruption to the education industry. Work integrated learning in very essential fields, namely, technology and engineering, did not take place. Despite the fact that MOOCs boosted formal education by providing online courses, the learning loss had already been maximized. This research addresses the motivations, challenges and interactions as well as the tangible and intangible impacts of technology and engineering online courses on MENA (Middle-East and North Africa) professionals; and to what extent have these courses been able to promote professionals to a new development in their careers? A survey questionnaire with standardized closed-ended and open-ended questions was conducted online with 66 professionals who have been purposely selected. The analysis of responses and findings show that the desire to develop and enhance knowledge previously acquired is the most important motivation. The results also showed weakness in the tangible achievements of the participants, and most of the achievements were the enhancement of knowledge. In spite of the set of challenges and inadequacies in achievements, the online platforms are providing a valuable well-built environment for life-long learning to advance knowledge, skills and to compensate for lost learning.
{"title":"Online Courses in Technology and Engineering: To What Extent Do They Tangibly Enhance Professional Development?","authors":"Abdullatif A. AlMunifi, Arwa Y. Aleryani","doi":"10.3991/ijet.v18i11.34833","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.34833","url":null,"abstract":"Platforms for online courses including Massive Open Online Courses (MOOCs) have become the most remarkable well-built environment for teaching and learning. Until recently the various types of online courses have been an optional and supplementary source of gaining knowledge and skills to compensate the learning lose in formal education, either for students or professionals. COVID-19 brought unprecedented disruption to the education industry. Work integrated learning in very essential fields, namely, technology and engineering, did not take place. Despite the fact that MOOCs boosted formal education by providing online courses, the learning loss had already been maximized. This research addresses the motivations, challenges and interactions as well as the tangible and intangible impacts of technology and engineering online courses on MENA (Middle-East and North Africa) professionals; and to what extent have these courses been able to promote professionals to a new development in their careers? A survey questionnaire with standardized closed-ended and open-ended questions was conducted online with 66 professionals who have been purposely selected. The analysis of responses and findings show that the desire to develop and enhance knowledge previously acquired is the most important motivation. The results also showed weakness in the tangible achievements of the participants, and most of the achievements were the enhancement of knowledge. In spite of the set of challenges and inadequacies in achievements, the online platforms are providing a valuable well-built environment for life-long learning to advance knowledge, skills and to compensate for lost learning.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43981057","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.39347
K. Lipták
The aim of the study is to measure the human resource potential of the North-Hungarian region in Hungary by developing and estimating a human development index at the level of municipalities. The results of the calculations will be produced for the last 3 census years (1990, 2001, 2011), showing which municipalities have the strongest human resource potential. In disadvantaged municipalities with low human development, there is an increased need for a social learning process. The existence of social enterprises can further strengthen the population retention capacity of a municipality, especially when targeted improvements and innovations are created. The study describes a successful social enterprise in a deprived municipality.
{"title":"Social Learning in Disadvantaged Municipalities in Hungary","authors":"K. Lipták","doi":"10.3991/ijet.v18i11.39347","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.39347","url":null,"abstract":"The aim of the study is to measure the human resource potential of the North-Hungarian region in Hungary by developing and estimating a human development index at the level of municipalities. The results of the calculations will be produced for the last 3 census years (1990, 2001, 2011), showing which municipalities have the strongest human resource potential. In disadvantaged municipalities with low human development, there is an increased need for a social learning process. The existence of social enterprises can further strengthen the population retention capacity of a municipality, especially when targeted improvements and innovations are created. The study describes a successful social enterprise in a deprived municipality.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47790050","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.39253
Doğuş Beyoğlu, Cigdem Hursen
In recent years, as well as in various other fields, developments in technology have gained a prominent place in the field of geography education. The purpose of this study is to identify the trends in the use of technology in research on geography education and to provide guidance to researchers in this field. In this regard, a detailed search was conducted for the studies published in the Web of Science database. As a result of the search, a total of 621 academic studies, which analyse the use of technology in geography education research, in Education Educational Research Category was accessed. The metadata of academic studies were downloaded from the Web of Science database and analysed with the software MS Excel and VOSviewer. The findings obtained from the study demonstrated an increase in the number of publications and citations over the years, and it was identified that the number of publications and citations increased more rapidly as of 2006 in comparison to previous years. When the geographical distribution of the studies was analysed, it was revealed that most of the studies were conducted in the UK, followed by the USA, Brazil, Australia, and China. According to keyword analysis, the most popular topics in recent years are geographic information technologies, online learning, virtual reality and visual communication technologies.
近年来，与其他领域一样，技术的发展在地理教育领域占据了突出的地位。本研究的目的是识别地理教育研究中技术应用的趋势，并为该领域的研究者提供指导。在这方面，我们对Web of Science数据库中发表的研究进行了详细的搜索。作为搜索的结果，在教育教育研究类别中，共有621项学术研究分析了地理教育研究中技术的使用。从Web of Science数据库中下载学术研究元数据，使用MS Excel和VOSviewer软件进行分析。从研究中获得的结果表明，多年来出版物和引用的数量有所增加，并且确定了2006年的出版物和引用数量与前几年相比增长更快。当分析研究的地理分布时，发现大多数研究是在英国进行的，其次是美国、巴西、澳大利亚和中国。根据关键词分析，近年来最热门的话题是地理信息技术、在线学习、虚拟现实和视觉传播技术。
{"title":"The Use of Technology in Geography Education Research: A Bibliometric Analysis","authors":"Doğuş Beyoğlu, Cigdem Hursen","doi":"10.3991/ijet.v18i11.39253","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.39253","url":null,"abstract":"In recent years, as well as in various other fields, developments in technology have gained a prominent place in the field of geography education. The purpose of this study is to identify the trends in the use of technology in research on geography education and to provide guidance to researchers in this field. In this regard, a detailed search was conducted for the studies published in the Web of Science database. As a result of the search, a total of 621 academic studies, which analyse the use of technology in geography education research, in Education Educational Research Category was accessed. The metadata of academic studies were downloaded from the Web of Science database and analysed with the software MS Excel and VOSviewer. The findings obtained from the study demonstrated an increase in the number of publications and citations over the years, and it was identified that the number of publications and citations increased more rapidly as of 2006 in comparison to previous years. When the geographical distribution of the studies was analysed, it was revealed that most of the studies were conducted in the UK, followed by the USA, Brazil, Australia, and China. According to keyword analysis, the most popular topics in recent years are geographic information technologies, online learning, virtual reality and visual communication technologies.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41618706","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.35405
Miami Abdul Aziz Al-Masoudy, Ahmed Al-Azawei
Predicting students' success in virtual learning environments (VLEs) can help educational institutions improve their online services and provide efficient online learning content. However, this cannot be achieved without identifying the possible effective features that have a high influence on students' performance. This research aims at providing an early prediction approach to learners' achievement on VLEs. A new feature selection method called a Developed Sequential Feature Selection (D-SFS) was proposed to identify the most effective features that could highly enhance prediction accuracy. The findings suggest that the D-SFS method outperforms the original Sequential Forward Selection (SFS) approach. The prediction accuracy using the SFS method was 92.466% with seventeen features, whereas the proposed approach successfully predicted 92.518% of students' performance using seven features only. Such outcomes highlight the importance of implementing a feature selection method to enhance prediction accuracy, decrease the number of features, and reduce the model's time and execution complexity.
{"title":"Proposing a Feature Selection Approach to Predict Learners' Performance in Virtual Learning Environments (VLEs)","authors":"Miami Abdul Aziz Al-Masoudy, Ahmed Al-Azawei","doi":"10.3991/ijet.v18i11.35405","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.35405","url":null,"abstract":"Predicting students' success in virtual learning environments (VLEs) can help educational institutions improve their online services and provide efficient online learning content. However, this cannot be achieved without identifying the possible effective features that have a high influence on students' performance. This research aims at providing an early prediction approach to learners' achievement on VLEs. A new feature selection method called a Developed Sequential Feature Selection (D-SFS) was proposed to identify the most effective features that could highly enhance prediction accuracy. The findings suggest that the D-SFS method outperforms the original Sequential Forward Selection (SFS) approach. The prediction accuracy using the SFS method was 92.466% with seventeen features, whereas the proposed approach successfully predicted 92.518% of students' performance using seven features only. Such outcomes highlight the importance of implementing a feature selection method to enhance prediction accuracy, decrease the number of features, and reduce the model's time and execution complexity.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42839819","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 : 2023-06-07DOI: 10.3991/ijet.v18i11.41081
Qiong Ding
The practice teaching of software operation emphasizes operation practice and practical experience, and it lays special attention on the interactions among students and teachers and teaching in accordance with aptitude. As a typical knowledge sharing platform, question-and-answer (Q&A) community is developing fast and can be taken as an assistant teaching method for the practice teaching of software operation to facilitate the teaching knowledge sharing between teachers and students. Most existing studies consider the attention mechanism of the correlation between questions and answers based on the similarity of word vectors, which has resulted in unsatisfactory accuracy and interpretability of the answers given by the model, in view of this matter, this paper studied a new method of teaching knowledge sharing oriented to the practice teaching of software operation. At first, this paper elaborated on the idea of knowledge sharing, and proposed a knowledge answer selection model for practice teaching of software operation based on the aggregation of features and attention to solve the problem with conventional studies which generally focus on the weighting of attention of a single sentence. Comparing the word granularity of sentence sequences to be matched and aggregating the comparison results have solved the problem with conventional methods in ignoring the interaction between the sentence sequences to be matched. At last, experimental results verified the effectiveness of the proposed method.
{"title":"A New Method of Teaching ‘Software Operation’ by a Knowledge Sharing Oriented to Practice Teaching Approach","authors":"Qiong Ding","doi":"10.3991/ijet.v18i11.41081","DOIUrl":"https://doi.org/10.3991/ijet.v18i11.41081","url":null,"abstract":"The practice teaching of software operation emphasizes operation practice and practical experience, and it lays special attention on the interactions among students and teachers and teaching in accordance with aptitude. As a typical knowledge sharing platform, question-and-answer (Q&A) community is developing fast and can be taken as an assistant teaching method for the practice teaching of software operation to facilitate the teaching knowledge sharing between teachers and students. Most existing studies consider the attention mechanism of the correlation between questions and answers based on the similarity of word vectors, which has resulted in unsatisfactory accuracy and interpretability of the answers given by the model, in view of this matter, this paper studied a new method of teaching knowledge sharing oriented to the practice teaching of software operation. At first, this paper elaborated on the idea of knowledge sharing, and proposed a knowledge answer selection model for practice teaching of software operation based on the aggregation of features and attention to solve the problem with conventional studies which generally focus on the weighting of attention of a single sentence. Comparing the word granularity of sentence sequences to be matched and aggregating the comparison results have solved the problem with conventional methods in ignoring the interaction between the sentence sequences to be matched. At last, experimental results verified the effectiveness of the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48538267","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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