Pub Date : 2023-07-31DOI: 10.3991/ijet.v18i14.38385
A. Berglund
The advent of augmented reality (AR) is reshaping the way people experience physical and virtual environments, from observation to immersion. Growing interest in adopting AR provides opportunities for immersive learning, upskilling, and renewal. However, uncertainties exist in how to maneuver a transition toward making use of this technology through systematic integration. Due to the turmoil caused by the global pandemic health crisis, implementation of AR now faces urgency in minimizing adoption thresholds and establishing a more systematic escalation approach. This paper investigates the characteristics of such learning approaches and examines the integration of AR with customized progression. Two solution suppliers were investigated to uncover the integration process of AR, which, to the best of our knowledge, is scarcely explored in existing research. This study reveals that a balanced escalation of user-centric learning activities, i.e., an onboarding process, harmonizes anticipated cognition levels for a designated AR application tool.
{"title":"Overcoming Integration Thresholds for Augmented Reality","authors":"A. Berglund","doi":"10.3991/ijet.v18i14.38385","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.38385","url":null,"abstract":"The advent of augmented reality (AR) is reshaping the way people experience physical and virtual environments, from observation to immersion. Growing interest in adopting AR provides opportunities for immersive learning, upskilling, and renewal. However, uncertainties exist in how to maneuver a transition toward making use of this technology through systematic integration. Due to the turmoil caused by the global pandemic health crisis, implementation of AR now faces urgency in minimizing adoption thresholds and establishing a more systematic escalation approach. This paper investigates the characteristics of such learning approaches and examines the integration of AR with customized progression. Two solution suppliers were investigated to uncover the integration process of AR, which, to the best of our knowledge, is scarcely explored in existing research. This study reveals that a balanced escalation of user-centric learning activities, i.e., an onboarding process, harmonizes anticipated cognition levels for a designated AR application tool.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46139686","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.41921
Heng Liang
A diversified academic assessment mechanism can effectively improve students’ learning motivation, make up for the possible blind spots of a single assessment method, and better guide students’ learning and teachers’ teaching. Using data mining methods to process evaluation data for diversified academic assessment mechanisms in colleges and universities can discover patterns in students’ learning, find key factors affecting academic performance, and provide a basis for teaching reform. Most of the current process evaluation data mining methods focus on hard skills, such as academic performance and classroom participation, but it is difficult to evaluate soft skills such as critical thinking and teamwork. To this end, this paper studies the process evaluation data mining methods for a diversified academic assessment mechanism in colleges and universities. It constructs an indicator system for process evaluation of diversified academic assessment mechanism in colleges and universities, gives a quantitative method for indicators, and performs fuzzy comprehensive evaluation based on AHP-entropy weight method. For the evaluation of text-based indicators, a consistency training method is introduced to train the process evaluation correlation mining model using a large amount of unlabeled process evaluation examples, which effectively solves the problems of lack of labeled data, high labeling cost, and changes in data distribution, and improves the performance and availability of the model. The experimental results verify the effectiveness of the proposed method.
{"title":"Process Evaluation for Diversified Academic Assessment Mechanism in Higher Education Institutions by Use of Data Mining","authors":"Heng Liang","doi":"10.3991/ijet.v18i14.41921","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.41921","url":null,"abstract":"A diversified academic assessment mechanism can effectively improve students’ learning motivation, make up for the possible blind spots of a single assessment method, and better guide students’ learning and teachers’ teaching. Using data mining methods to process evaluation data for diversified academic assessment mechanisms in colleges and universities can discover patterns in students’ learning, find key factors affecting academic performance, and provide a basis for teaching reform. Most of the current process evaluation data mining methods focus on hard skills, such as academic performance and classroom participation, but it is difficult to evaluate soft skills such as critical thinking and teamwork. To this end, this paper studies the process evaluation data mining methods for a diversified academic assessment mechanism in colleges and universities. It constructs an indicator system for process evaluation of diversified academic assessment mechanism in colleges and universities, gives a quantitative method for indicators, and performs fuzzy comprehensive evaluation based on AHP-entropy weight method. For the evaluation of text-based indicators, a consistency training method is introduced to train the process evaluation correlation mining model using a large amount of unlabeled process evaluation examples, which effectively solves the problems of lack of labeled data, high labeling cost, and changes in data distribution, and improves the performance and availability of the model. The experimental results verify the effectiveness of the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44268537","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.41917
Yashen Xie
Quality management of network classroom teaching has always been an urgent problem to be solved. Big data technology handles massive amounts of data and provides new quality management methods and means for network classroom teaching. However, data integration and fusion is a complex task and existing methods may not be able to deal with data fragmentation effectively, because data is often distributed across different systems and platforms in the network teaching environment. Therefore, this research aimed to study the quality management of network classroom teaching based on big data technology. This study provided a framework diagram of teaching quality evaluation criteria and factors affecting the teaching quality in the big data environment, explained complex relationships and effects among the factors, and described teaching quality prediction problems. The dimensionality reduction method of Least Absolute Shrinkage and Selection Operator (LASSO) was used for comprehensive status data integration of factors affecting teaching quality. An unequal-interval grey Riccati-Bernoulli model was constructed to study the internal relationships between various variable factors and network classroom teaching quality. Then the execution process of the prediction model, detailed modeling steps and teaching quality management steps were provided. The experimental results verified that the constructed model was effective.
{"title":"Use of Big Data Technology for Network Classroom Teaching Quality Management","authors":"Yashen Xie","doi":"10.3991/ijet.v18i14.41917","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.41917","url":null,"abstract":"Quality management of network classroom teaching has always been an urgent problem to be solved. Big data technology handles massive amounts of data and provides new quality management methods and means for network classroom teaching. However, data integration and fusion is a complex task and existing methods may not be able to deal with data fragmentation effectively, because data is often distributed across different systems and platforms in the network teaching environment. Therefore, this research aimed to study the quality management of network classroom teaching based on big data technology. This study provided a framework diagram of teaching quality evaluation criteria and factors affecting the teaching quality in the big data environment, explained complex relationships and effects among the factors, and described teaching quality prediction problems. The dimensionality reduction method of Least Absolute Shrinkage and Selection Operator (LASSO) was used for comprehensive status data integration of factors affecting teaching quality. An unequal-interval grey Riccati-Bernoulli model was constructed to study the internal relationships between various variable factors and network classroom teaching quality. Then the execution process of the prediction model, detailed modeling steps and teaching quality management steps were provided. The experimental results verified that the constructed model was effective.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46683533","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.40201
Aria Bisri, Atina Putri, Y. Rosmansyah
To answer the challenges and take advantage of opportunities in this digital era, digital transformation (DT) is carried out in various fields, including higher education. Although DT does not yet have an agreed-upon definition, several papers provide approaches to understanding it. This paper presents a systematic literature review (SLR) to understand DT in higher education by addressing the research questions of what, why, and how to conduct DT in higher education. Sixty-six papers from five digital libraries, namely IEEE Xplore, Scopus, Web of Science, SpringerLink, and ScienceDirect, are discussed in this paper. The results of the SLR reveal that in higher education, the success of DT is strongly influenced by the leadership of executive in managing the institution to overcome barriers, to adopt appropriate strategies, and to maintain a consistent approach to implementation.
为了应对数字时代的挑战并抓住机遇，数字化转型(DT)在各个领域进行，包括高等教育。虽然DT还没有一个公认的定义，但有几篇论文提供了理解它的方法。本文提出了一个系统的文献综述(SLR)，通过解决在高等教育中进行什么、为什么以及如何进行DT的研究问题来理解高等教育中的DT。本文讨论了来自IEEE explore、Scopus、Web of Science、SpringerLink、ScienceDirect等5个数字图书馆的66篇论文。SLR的结果表明，在高等教育中，行政管理人员在管理机构克服障碍、采取适当的战略和保持一致的实施方法方面的领导能力强烈影响着DT的成功。
{"title":"A Systematic Literature Review on Digital Transformation in Higher Education: Revealing Key Success Factors","authors":"Aria Bisri, Atina Putri, Y. Rosmansyah","doi":"10.3991/ijet.v18i14.40201","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.40201","url":null,"abstract":"To answer the challenges and take advantage of opportunities in this digital era, digital transformation (DT) is carried out in various fields, including higher education. Although DT does not yet have an agreed-upon definition, several papers provide approaches to understanding it. This paper presents a systematic literature review (SLR) to understand DT in higher education by addressing the research questions of what, why, and how to conduct DT in higher education. Sixty-six papers from five digital libraries, namely IEEE Xplore, Scopus, Web of Science, SpringerLink, and ScienceDirect, are discussed in this paper. The results of the SLR reveal that in higher education, the success of DT is strongly influenced by the leadership of executive in managing the institution to overcome barriers, to adopt appropriate strategies, and to maintain a consistent approach to implementation.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45154080","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.39871
Randa Obeidallah, Ayat Al Ahmad, Duha Qutishat
Extended reality is proposed as a means to deliver qualitative material to students in higher education institutions. The usage of this technology has increased due to Covid-19 lock down. This paper aims to categorize the challenges encountered by literature that deployed extended reality (XR) in higher education during and after the lockdown. However, the number of available articles addressing these challenges is limited, with a total number of 40 articles obtained from dimensions’ dataset. In this study, bibliometric analysis is used to highlight the number of publications, citations, and authors in this field. Thematic analysis with inductive reasoning is applied to extract the primary challenge themes mentioned in 23 articles. After reviewing the eligible articles; we categorized the challenges into three main themes: Teacher, Student, and Technology.
{"title":"Challenges of Extended Reality Technology in Higher Education: A Review","authors":"Randa Obeidallah, Ayat Al Ahmad, Duha Qutishat","doi":"10.3991/ijet.v18i14.39871","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.39871","url":null,"abstract":"Extended reality is proposed as a means to deliver qualitative material to students in higher education institutions. The usage of this technology has increased due to Covid-19 lock down. This paper aims to categorize the challenges encountered by literature that deployed extended reality (XR) in higher education during and after the lockdown. However, the number of available articles addressing these challenges is limited, with a total number of 40 articles obtained from dimensions’ dataset. In this study, bibliometric analysis is used to highlight the number of publications, citations, and authors in this field. Thematic analysis with inductive reasoning is applied to extract the primary challenge themes mentioned in 23 articles. After reviewing the eligible articles; we categorized the challenges into three main themes: Teacher, Student, and Technology.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42026073","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.39873
Haitham Qawaqneh, F. Ahmad, Ali Ratib Alawamreh
This research investigates the impact of virtual laboratories (VLabs) based on artificial intelligence (AI) on developing students’ motivation toward learning mathematics. A semiexperimental approach is used to achieve the research objectives. The research sample, consisting of 80students from the seventh grade, is selected by the purposeful sampling approach. The research sample is randomly distributed into three groups: two experimental groups and one control group. The first group of 26 students is taught using the AI-based VLabs, while the second group of 27 students is taught using a VLab based on 3D visual imaging, and the third group, a control group consisting of 27 students, is taught using the traditional approach. The research instrument, a questionnaire for learning motivation, was designed after ensuring its validity and reliability. The findings of the motivation questionnaire indicate that students in the first experimental group have more motivation to learn mathematics than students in the second experimental group and the control group. The results also show that the students in the second experimental group have more motivation to learn mathematics than the students in the control group. Given the said findings, the research recommends using virtual laboratories based on artificial intelligence and all its applications in the learning process due to their impact on students’ mathematics learning.
{"title":"The Impact of Artificial Intelligence-Based Virtual Laboratories on Developing Students’ Motivation Towards Learning Mathematics","authors":"Haitham Qawaqneh, F. Ahmad, Ali Ratib Alawamreh","doi":"10.3991/ijet.v18i14.39873","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.39873","url":null,"abstract":"This research investigates the impact of virtual laboratories (VLabs) based on artificial intelligence (AI) on developing students’ motivation toward learning mathematics. A semiexperimental approach is used to achieve the research objectives. The research sample, consisting of 80students from the seventh grade, is selected by the purposeful sampling approach. The research sample is randomly distributed into three groups: two experimental groups and one control group. The first group of 26 students is taught using the AI-based VLabs, while the second group of 27 students is taught using a VLab based on 3D visual imaging, and the third group, a control group consisting of 27 students, is taught using the traditional approach. The research instrument, a questionnaire for learning motivation, was designed after ensuring its validity and reliability. The findings of the motivation questionnaire indicate that students in the first experimental group have more motivation to learn mathematics than students in the second experimental group and the control group. The results also show that the students in the second experimental group have more motivation to learn mathematics than the students in the control group. Given the said findings, the research recommends using virtual laboratories based on artificial intelligence and all its applications in the learning process due to their impact on students’ mathematics learning.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47834374","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}
As the demand for cross-cultural communication has been increasing because of globalization, communicative language ability (CLA) has become an important component of quality education for college students. CLA evaluation and difference analysis help educators understand and identify problems and shortcomings of students in the learning process. However, most of the existing CLA evaluation and difference analysis methods focus on written and oral tests of college students in an interactive teaching environment, instead of evaluating actual communicative ability in the interactive environment. Therefore, this research aimed to study the CLA evaluation of college students and difference analysis in an interactive teaching environment. The environment for improving the CLA was analyzed first. After setting up five-level evaluation indexes for the CLA evaluation of college students in the interactive teaching environment, three methods were used to weight the CLA evaluation indexes, namely, the fuzzy analytic hierarchy process (FAHP), the entropy weight method (EWM), and the coefficient of variation method (CVM). Then a model for evaluating the CLA was constructed, which minimized the CLA improvement difference of college students. Finally, the experimental results verified that the proposed method was effective.
{"title":"Evaluation of Students' Communicative Language Ability and Difference Analysis in an Interactive Teaching Environment","authors":"Xin Zhao, Jia Song, Ru Wang, Fengming Jiao, Mingli Gao","doi":"10.3991/ijet.v18i14.41911","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.41911","url":null,"abstract":"As the demand for cross-cultural communication has been increasing because of globalization, communicative language ability (CLA) has become an important component of quality education for college students. CLA evaluation and difference analysis help educators understand and identify problems and shortcomings of students in the learning process. However, most of the existing CLA evaluation and difference analysis methods focus on written and oral tests of college students in an interactive teaching environment, instead of evaluating actual communicative ability in the interactive environment. Therefore, this research aimed to study the CLA evaluation of college students and difference analysis in an interactive teaching environment. The environment for improving the CLA was analyzed first. After setting up five-level evaluation indexes for the CLA evaluation of college students in the interactive teaching environment, three methods were used to weight the CLA evaluation indexes, namely, the fuzzy analytic hierarchy process (FAHP), the entropy weight method (EWM), and the coefficient of variation method (CVM). Then a model for evaluating the CLA was constructed, which minimized the CLA improvement difference of college students. Finally, the experimental results verified that the proposed method was effective.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47236877","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.39833
N. Karelkhan, Aknur Kadirbek, Peter Schmidt
Geoinformation systems, as teaching tools in education, are closely linked to interdisciplinary and natural sciences. Currently, the application of geoinformation systems (GIS) in the educational process holds great potential for higher education. This paper presents a pedagogical system for teaching and learning a GIS course, along with a wide range of information sources that educators can choose from. The pedagogical system of introducing special GIS courses is divided into content, organizational and methodological structures. The theoretical and practical foundations of the introduction of special GIS courses are also considered. Additionally, the paper provides information about practical works setting up and implementing ArcGIS to work with maps and geospatial data with Python. The pedagogical system described in this paper was employed in the educational process of the L.N. Gumilyov Eurasian National University (Astana, Kazakhstan) and K. Zhubanov Aktobe Regional University (Aktobe, Kazakhstan). This experimental research examines how perceptions of geocapabilities evolved among 119 higher education students as they acquired technical skills in web mapping by investigating real-world issues with ArcGIS.
{"title":"Setting Up and Implementing ArcGIS to Work with Maps and Geospatial Data with Python for Teaching Geoinformation Systems in Higher Education","authors":"N. Karelkhan, Aknur Kadirbek, Peter Schmidt","doi":"10.3991/ijet.v18i14.39833","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.39833","url":null,"abstract":"Geoinformation systems, as teaching tools in education, are closely linked to interdisciplinary and natural sciences. Currently, the application of geoinformation systems (GIS) in the educational process holds great potential for higher education. This paper presents a pedagogical system for teaching and learning a GIS course, along with a wide range of information sources that educators can choose from. The pedagogical system of introducing special GIS courses is divided into content, organizational and methodological structures. The theoretical and practical foundations of the introduction of special GIS courses are also considered. Additionally, the paper provides information about practical works setting up and implementing ArcGIS to work with maps and geospatial data with Python. The pedagogical system described in this paper was employed in the educational process of the L.N. Gumilyov Eurasian National University (Astana, Kazakhstan) and K. Zhubanov Aktobe Regional University (Aktobe, Kazakhstan). This experimental research examines how perceptions of geocapabilities evolved among 119 higher education students as they acquired technical skills in web mapping by investigating real-world issues with ArcGIS.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42549355","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.40423
S. Ketab, Abdulwahid Al Abdulwahid
A massive number of users are currently utilizing e-learning. Despite the flexibility provided, the traditional methods of course delivery are still used, including e-examinations. There is significant concern about the potential for cheating. The current solutions in this respect fundamentally fail to offer the required level of security. This paper seeks to develop an e-invigilator that will provide continuous and transparent invigilation of examinees. The study involves a detailed presentation of the proposed architecture and a complete design to be the core of the system, which captures, processes, and monitors students in a controlled and convenient fashion. The proposed framework prototype was developed, presented, and utilized, involving 51 participants to conduct an experiment to explore the viability of the proposed framework. For all 51 participants in this experiment, the false rejection rate was 0 in 2D facial recognition mode, while in 3D facial recognition mode it was 0.04827. Moreover, in order to evaluate the robustness of the approach against targeted misuse, three participants were tasked with a series of nine threat scenarios. The false acceptance rate was 0.038 in the 2D mode and 0 in the 3D mode.
{"title":"Continuous and Transparent E-Invigilation of E-Assessments","authors":"S. Ketab, Abdulwahid Al Abdulwahid","doi":"10.3991/ijet.v18i14.40423","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.40423","url":null,"abstract":"A massive number of users are currently utilizing e-learning. Despite the flexibility provided, the traditional methods of course delivery are still used, including e-examinations. There is significant concern about the potential for cheating. The current solutions in this respect fundamentally fail to offer the required level of security. This paper seeks to develop an e-invigilator that will provide continuous and transparent invigilation of examinees. The study involves a detailed presentation of the proposed architecture and a complete design to be the core of the system, which captures, processes, and monitors students in a controlled and convenient fashion. The proposed framework prototype was developed, presented, and utilized, involving 51 participants to conduct an experiment to explore the viability of the proposed framework. For all 51 participants in this experiment, the false rejection rate was 0 in 2D facial recognition mode, while in 3D facial recognition mode it was 0.04827. Moreover, in order to evaluate the robustness of the approach against targeted misuse, three participants were tasked with a series of nine threat scenarios. The false acceptance rate was 0.038 in the 2D mode and 0 in the 3D mode.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44475370","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 : 2023-07-31DOI: 10.3991/ijet.v18i14.41919
Dapeng Bao, Liquan Chen, Wenbo Wang
Exploring the problem of teaching quality monitoring and evaluation from the perspective of educational balance can help educators and policy makers discover educational inequality problems, thereby promoting fair allocation of educational resources and opportunities. In light of this, this study attempts to research teaching quality monitoring and evaluation from the perspective of educational balance. At first, the mechanism of promoting educational balance by information technology was expounded, and the principle and necessity of a comprehensive assessment based on the evaluation results of different evaluators were explained. Then, this study innovatively introduced the whitening weight function (WWF)-grey evaluation model into the conventional grey clustering evaluation, calculated the unit comprehensive clustering coefficients of the indexes of teaching quality evaluation from the perspective of educational balance, and gave fair, accurate, and effective evaluations. After that, the grey GM (1,1) model was applied to the prediction of teaching quality improvement effect, the future trend of teaching quality changes was predicted based on history data, and the results provided references for teaching reform and educational decision-making. At last, experimental results verified the validity of the proposed method.
{"title":"A Novel Method of Teaching Quality Monitoring and Evaluation from the Perspective of Educational Balance","authors":"Dapeng Bao, Liquan Chen, Wenbo Wang","doi":"10.3991/ijet.v18i14.41919","DOIUrl":"https://doi.org/10.3991/ijet.v18i14.41919","url":null,"abstract":"Exploring the problem of teaching quality monitoring and evaluation from the perspective of educational balance can help educators and policy makers discover educational inequality problems, thereby promoting fair allocation of educational resources and opportunities. In light of this, this study attempts to research teaching quality monitoring and evaluation from the perspective of educational balance. At first, the mechanism of promoting educational balance by information technology was expounded, and the principle and necessity of a comprehensive assessment based on the evaluation results of different evaluators were explained. Then, this study innovatively introduced the whitening weight function (WWF)-grey evaluation model into the conventional grey clustering evaluation, calculated the unit comprehensive clustering coefficients of the indexes of teaching quality evaluation from the perspective of educational balance, and gave fair, accurate, and effective evaluations. After that, the grey GM (1,1) model was applied to the prediction of teaching quality improvement effect, the future trend of teaching quality changes was predicted based on history data, and the results provided references for teaching reform and educational decision-making. At last, experimental results verified the validity of the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46209107","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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