Pub Date : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031993
Yunkai Xiao, Yinan Gao, Chuhuai Yue, E. Gehringer
There is a trend to move education into an online environment, especially when offline learning is restricted by time, space, availability, or is impacted by issues such as a public health incident. Evaluating students’ performance in online education has always been challenging. Objective questions, which can be graded automatically, could only assess certain aspects of students’ mastery of knowledge. A grading problem appears if subjective questions exist, primarily when the class is taught at scale. Many online education platforms have been using peer assessment to resolve this problem. Aside from that, peer assessment also improves interactions between students, instructors, and peers. While peer assessment has some inherent weaknesses, reviewers may not have the same ability or attitude toward reviewing others, and the feedback generated by them shall not be taken at face value. Many algorithms have been developed to evaluate annotators’ trustworthiness and generate reliable labels in the crowdsourcing industry. We proposed an algorithm under the same concept that could provide accurate automated grading, an overview of students’ weaknesses from peer feedback, and identify reviewers who lack an understanding of certain concepts. This information allows instructors to offer targeted training and create data-driven lesson plans.
{"title":"Estimating Student Grades through Peer Assessment as a Crowdsourcing Calibration Problem","authors":"Yunkai Xiao, Yinan Gao, Chuhuai Yue, E. Gehringer","doi":"10.1109/ITHET56107.2022.10031993","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031993","url":null,"abstract":"There is a trend to move education into an online environment, especially when offline learning is restricted by time, space, availability, or is impacted by issues such as a public health incident. Evaluating students’ performance in online education has always been challenging. Objective questions, which can be graded automatically, could only assess certain aspects of students’ mastery of knowledge. A grading problem appears if subjective questions exist, primarily when the class is taught at scale. Many online education platforms have been using peer assessment to resolve this problem. Aside from that, peer assessment also improves interactions between students, instructors, and peers. While peer assessment has some inherent weaknesses, reviewers may not have the same ability or attitude toward reviewing others, and the feedback generated by them shall not be taken at face value. Many algorithms have been developed to evaluate annotators’ trustworthiness and generate reliable labels in the crowdsourcing industry. We proposed an algorithm under the same concept that could provide accurate automated grading, an overview of students’ weaknesses from peer feedback, and identify reviewers who lack an understanding of certain concepts. This information allows instructors to offer targeted training and create data-driven lesson plans.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133346483","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10032029
Ivica Pesovski, A. Bogdanova, V. Trajkovik
The goal of this paper is to systematically review the available literature on the topic of explainable recommendation systems in education, especially when recommendation systems are integrated as a part of learning management systems (LMS). The focus years for analyzing available literature are the years between 2010 and 2022, period when online learning is expanding and online learning platforms are continuously being developed, which makes these years relevant for scoping this review. The topic of interest in this research are recommendation algorithms whose results can be explained and interpreted. The first part of the methodology used in the paper utilizes an NLP-powered toolkit that automates a big part of the review process by automatically analyzing articles indexed in the IEEE Xplore, PubMed, Springer, Elsevier and MDPI digital libraries. The toolkit relies on the PRISMA methodology for standardizing systematic reviews. First, a quantitative analysis of all available literature is performed, followed by a qualitative analysis of the few selected articles which indeed focus on the explainability when implementing recommendation systems in educational context. The relevant articles are analyzed in detail and compared on multiple indicators like the field of work, tools and techniques used, and how explainability is achieved. The results show that although the amount of available research is growing and new learning management systems are being developed at a fast pace in the last few years, the explainability of the machine learning techniques used in the recommendation systems is not a popular topic among the researchers and developers with research interest in educational context. The amount of the available literature for explainable recommendation systems in educational environment is scarce, but is expected to grow following the global trend of explainable artificial intelligence $(mathrm{x}mathrm{A}mathrm{I})$ as key technique for practical implementation of advanced AI models.
{"title":"Systematic Review of the published Explainable Educational Recommendation Systems","authors":"Ivica Pesovski, A. Bogdanova, V. Trajkovik","doi":"10.1109/ITHET56107.2022.10032029","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10032029","url":null,"abstract":"The goal of this paper is to systematically review the available literature on the topic of explainable recommendation systems in education, especially when recommendation systems are integrated as a part of learning management systems (LMS). The focus years for analyzing available literature are the years between 2010 and 2022, period when online learning is expanding and online learning platforms are continuously being developed, which makes these years relevant for scoping this review. The topic of interest in this research are recommendation algorithms whose results can be explained and interpreted. The first part of the methodology used in the paper utilizes an NLP-powered toolkit that automates a big part of the review process by automatically analyzing articles indexed in the IEEE Xplore, PubMed, Springer, Elsevier and MDPI digital libraries. The toolkit relies on the PRISMA methodology for standardizing systematic reviews. First, a quantitative analysis of all available literature is performed, followed by a qualitative analysis of the few selected articles which indeed focus on the explainability when implementing recommendation systems in educational context. The relevant articles are analyzed in detail and compared on multiple indicators like the field of work, tools and techniques used, and how explainability is achieved. The results show that although the amount of available research is growing and new learning management systems are being developed at a fast pace in the last few years, the explainability of the machine learning techniques used in the recommendation systems is not a popular topic among the researchers and developers with research interest in educational context. The amount of the available literature for explainable recommendation systems in educational environment is scarce, but is expected to grow following the global trend of explainable artificial intelligence $(mathrm{x}mathrm{A}mathrm{I})$ as key technique for practical implementation of advanced AI models.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125207020","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031659
O. Bonnaud
The strategy of teaching electrical engineering applied to microelectronics is undergoing a very strong evolution combining the development of the Internet and thus the globalization of digital technology and the experience of the pandemic on distance learning approaches. On the one hand, the meteoric development of digital technology is creating new challenges related to the saturation of data transfer networks and the associated consumption of electrical energy, which are growing exponentially. On the other hand, the use of digital technology in applied sciences during the pandemic has proven to be almost ineffective. The future engineers need knowledge and know-how in order to be efficient and innovative. This document deals in a first part with the technical and scientific needs applied to microelectronics and in a second part with the training strategy and the pedagogical approach which must imperatively optimize the use of digital technology by promoting well targeted actions.. These experiments were conducted within the French national microelectronics network, which includes 12 inter-university centers and covers all the specialties in the field, and which made it possible to test the interest and effectiveness of different approaches. (Abstract)
{"title":"Higher education strategy in engineering to meet global technical challenges","authors":"O. Bonnaud","doi":"10.1109/ITHET56107.2022.10031659","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031659","url":null,"abstract":"The strategy of teaching electrical engineering applied to microelectronics is undergoing a very strong evolution combining the development of the Internet and thus the globalization of digital technology and the experience of the pandemic on distance learning approaches. On the one hand, the meteoric development of digital technology is creating new challenges related to the saturation of data transfer networks and the associated consumption of electrical energy, which are growing exponentially. On the other hand, the use of digital technology in applied sciences during the pandemic has proven to be almost ineffective. The future engineers need knowledge and know-how in order to be efficient and innovative. This document deals in a first part with the technical and scientific needs applied to microelectronics and in a second part with the training strategy and the pedagogical approach which must imperatively optimize the use of digital technology by promoting well targeted actions.. These experiments were conducted within the French national microelectronics network, which includes 12 inter-university centers and covers all the specialties in the field, and which made it possible to test the interest and effectiveness of different approaches. (Abstract)","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114616923","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 : 2022-11-07DOI: 10.1109/ithet56107.2022.10031276
Patrick Herbke, Hakan Yildiz
Digital credentials in education make it easier for students to apply for a course of study, a new job, or change a higher education institute. Academic networks, such as EMREX, support the exchange of digital credentials between students and education institutes. Students can fetch results from one educational institute and apply for a course of study at another educational institute. Digital signatures of the issuing institution can verify the authenticity of digital credentials. Each institution must provide the integration of EMREX using its identity management system. In this paper, we investigate how digital credentials can be integrated into the Self-Sovereign Identity ecosystem to overcome the known issues of academic networks. We examine known issues such as the authentication of students. Self-Sovereign Identity is a paradigm that gives individuals control of their digital identities. Based on our findings, we propose ELMO2EDS, a solution that 1) converts digital credentials from EMREX to a suitable Self-Sovereign Identy data format, 2) enables authenticating a student, and 3) enables issuing, storing, and verification of achieved study.
{"title":"ELMO2EDS: Transforming Educational Credentials into Self-Sovereign Identity Paradigm","authors":"Patrick Herbke, Hakan Yildiz","doi":"10.1109/ithet56107.2022.10031276","DOIUrl":"https://doi.org/10.1109/ithet56107.2022.10031276","url":null,"abstract":"Digital credentials in education make it easier for students to apply for a course of study, a new job, or change a higher education institute. Academic networks, such as EMREX, support the exchange of digital credentials between students and education institutes. Students can fetch results from one educational institute and apply for a course of study at another educational institute. Digital signatures of the issuing institution can verify the authenticity of digital credentials. Each institution must provide the integration of EMREX using its identity management system. In this paper, we investigate how digital credentials can be integrated into the Self-Sovereign Identity ecosystem to overcome the known issues of academic networks. We examine known issues such as the authentication of students. Self-Sovereign Identity is a paradigm that gives individuals control of their digital identities. Based on our findings, we propose ELMO2EDS, a solution that 1) converts digital credentials from EMREX to a suitable Self-Sovereign Identy data format, 2) enables authenticating a student, and 3) enables issuing, storing, and verification of achieved study.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125141711","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031804
S. Alhazbi, M. A. Hasan
Learning analytics aims to understand and optimize learning process by collecting and analyzing traced learner’s data. To utilize its potential, it should involve educational theoretical frameworks to identify the indicators in the traced data as well as to interpret the results. In this paper, we use learning analytics to explore the role of students’ self-regulation in their achievements in synchronous online learning. The study identifies three indicators in students’ traced data to capture self-regulation: session attendance time, students’ submissions of self-assessments, and study regularity by assessing their correlations with the self-regulation scales measured by self-reported instruments. The results show that these indicators are positively correlated with the students’ achievements, so they can be used to predict students’ performance in synchronous online learning, and identify students at risk.
{"title":"Using Learning Analytics to Explore the Role of Self-regulation in students’ Achievements in Synchronous Online Learning","authors":"S. Alhazbi, M. A. Hasan","doi":"10.1109/ITHET56107.2022.10031804","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031804","url":null,"abstract":"Learning analytics aims to understand and optimize learning process by collecting and analyzing traced learner’s data. To utilize its potential, it should involve educational theoretical frameworks to identify the indicators in the traced data as well as to interpret the results. In this paper, we use learning analytics to explore the role of students’ self-regulation in their achievements in synchronous online learning. The study identifies three indicators in students’ traced data to capture self-regulation: session attendance time, students’ submissions of self-assessments, and study regularity by assessing their correlations with the self-regulation scales measured by self-reported instruments. The results show that these indicators are positively correlated with the students’ achievements, so they can be used to predict students’ performance in synchronous online learning, and identify students at risk.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114070918","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031712
Luochao Wang, Raymond S. T. Lee
For the past several decades, with the rapid development of internet technologies and online transaction platforms, financial institutions and investors are facing huge challenges from the global economic environment that financial markets are becoming more unpredictable and volatile than before, especially in the stock markets, commodity markets and cryptocurrency markets. Interest and awareness of Artificial Intelligence and Quantum Finance are growing so fast that both academia and higher education are struggling to keep up with the accelerating demand of financial markets. Quantum finance is a newly developed interdisciplinary program with the integration of quantum theory, computational finance, and even computer science, which requires students to have comprehensive knowledge reserves. Meanwhile, it is extremely complicated for students to use a programming language to realize quantum finance calculations from scratch. To facilitate curricula teaching, and hands-on usage of quantum finance and AI, a Quantum Finance Software Development Kit (QFSDK) is proposed based on the author’s previous research on Quantum Finance Theory and other AI research findings. The QFSDK was prepared in python programming language as the first step in introducing students to the concepts and applications of quantum finance. The QFSDK bridges the theoretical and practical chasm for learners by developing a quantum finance calculator library. It serves as an open-source template that encourages heavy contextual modification, and it supports any online platforms in the python programming language.
{"title":"The Design and Implementation of Quantum Finance Software Development Kit (QFSDK) for AI Education","authors":"Luochao Wang, Raymond S. T. Lee","doi":"10.1109/ITHET56107.2022.10031712","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031712","url":null,"abstract":"For the past several decades, with the rapid development of internet technologies and online transaction platforms, financial institutions and investors are facing huge challenges from the global economic environment that financial markets are becoming more unpredictable and volatile than before, especially in the stock markets, commodity markets and cryptocurrency markets. Interest and awareness of Artificial Intelligence and Quantum Finance are growing so fast that both academia and higher education are struggling to keep up with the accelerating demand of financial markets. Quantum finance is a newly developed interdisciplinary program with the integration of quantum theory, computational finance, and even computer science, which requires students to have comprehensive knowledge reserves. Meanwhile, it is extremely complicated for students to use a programming language to realize quantum finance calculations from scratch. To facilitate curricula teaching, and hands-on usage of quantum finance and AI, a Quantum Finance Software Development Kit (QFSDK) is proposed based on the author’s previous research on Quantum Finance Theory and other AI research findings. The QFSDK was prepared in python programming language as the first step in introducing students to the concepts and applications of quantum finance. The QFSDK bridges the theoretical and practical chasm for learners by developing a quantum finance calculator library. It serves as an open-source template that encourages heavy contextual modification, and it supports any online platforms in the python programming language.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127434131","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031884
Kenneth Howah, E. Gide
Transfer of Learning (“transfer”) has been studied for many decades in various fields dealing with the cognitive sciences such as psychology, learning, and education. A distinction between near transfer and far transfer is generally accepted, the latter referring to significant dissimilarities along various dimensions between an original learning context and a later situation requiring the application of knowledge [1]. The far transfer of learning is the putative goal of education. However, the focus in higher education practices on this phenomenon is not generally commensurate with its importance for students about to graduate from formal schooling to permanent employment. Yet at this time of their life, transfer of prior learning becomes an issue arguably more critical than in any other period.This paper pulls together some of the key literature describing studies into the transfer of learning, and argues that the phenomenon should receive much more attention and focus in higher education than it does.Although there is some doubt in the literature about the nature or efficacy of transfer, the doubts appear to rely on scientifically narrow definitions of transfer which exclude deliberate interventions that facilitate transfer. However, such narrow approaches are unnecessary for effective application in an educational context. This is because there is substantial accumulated evidence in the literature that a wide range of practical interventions are possible in learning, teaching, and assessment in higher education that have been shown to directly facilitate the transfer of learning.
{"title":"A Critical Analysis on the Transfer of Learning Technologies in Higher Education Curriculum Design","authors":"Kenneth Howah, E. Gide","doi":"10.1109/ITHET56107.2022.10031884","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031884","url":null,"abstract":"Transfer of Learning (“transfer”) has been studied for many decades in various fields dealing with the cognitive sciences such as psychology, learning, and education. A distinction between near transfer and far transfer is generally accepted, the latter referring to significant dissimilarities along various dimensions between an original learning context and a later situation requiring the application of knowledge [1]. The far transfer of learning is the putative goal of education. However, the focus in higher education practices on this phenomenon is not generally commensurate with its importance for students about to graduate from formal schooling to permanent employment. Yet at this time of their life, transfer of prior learning becomes an issue arguably more critical than in any other period.This paper pulls together some of the key literature describing studies into the transfer of learning, and argues that the phenomenon should receive much more attention and focus in higher education than it does.Although there is some doubt in the literature about the nature or efficacy of transfer, the doubts appear to rely on scientifically narrow definitions of transfer which exclude deliberate interventions that facilitate transfer. However, such narrow approaches are unnecessary for effective application in an educational context. This is because there is substantial accumulated evidence in the literature that a wide range of practical interventions are possible in learning, teaching, and assessment in higher education that have been shown to directly facilitate the transfer of learning.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121067047","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031755
Jean-Vincent Loddo, R. Kanawati
This paper reports on the design, development and first use experience of Mariotel: a free-software project for deploying virtual remote computer science labs simply accessible from ordinary web browsers. Mariotel platform has been developed during the first generalized lockdown period due the Covid-19 pandemic situation. Simplicity has been the main principle that guided the design and development process of Mariotel. We show that this principle has largely contributed to the quick adoption of this new platform. The system has been successfully used at USPN since 2020. 42 different teachers have used the platform in order to supply ensure 9989 lab sessions, each has in average three hour duration.
{"title":"Mariotel: A web-based virtual remote computer science lab","authors":"Jean-Vincent Loddo, R. Kanawati","doi":"10.1109/ITHET56107.2022.10031755","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031755","url":null,"abstract":"This paper reports on the design, development and first use experience of Mariotel: a free-software project for deploying virtual remote computer science labs simply accessible from ordinary web browsers. Mariotel platform has been developed during the first generalized lockdown period due the Covid-19 pandemic situation. Simplicity has been the main principle that guided the design and development process of Mariotel. We show that this principle has largely contributed to the quick adoption of this new platform. The system has been successfully used at USPN since 2020. 42 different teachers have used the platform in order to supply ensure 9989 lab sessions, each has in average three hour duration.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134574802","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031827
Yunkai Xiao, Soumyadeep Chatterjee, E. Gehringer
Recent development in AI algorithms has benefited many industries, but they also brought some problems to fairness in academic evaluation. Plagiarism is one of them, and little research has been put into it. This paper examines AI tools that can be used to plagiarize and preliminary findings using existing plagiarism detection algorithms. We found that tools commonly used to detect plagiarism in the academic field are vulnerable to attacks by these AI-based tools.
{"title":"A New Era of Plagiarism the Danger of Cheating Using AI","authors":"Yunkai Xiao, Soumyadeep Chatterjee, E. Gehringer","doi":"10.1109/ITHET56107.2022.10031827","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031827","url":null,"abstract":"Recent development in AI algorithms has benefited many industries, but they also brought some problems to fairness in academic evaluation. Plagiarism is one of them, and little research has been put into it. This paper examines AI tools that can be used to plagiarize and preliminary findings using existing plagiarism detection algorithms. We found that tools commonly used to detect plagiarism in the academic field are vulnerable to attacks by these AI-based tools.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538909","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 : 2022-11-07DOI: 10.1109/ITHET56107.2022.10031955
Anthony Ward
Accounting and Finance is a core module for undergraduate students taking the Bachelor or Integrated Undergraduate Masters in Electronic Engineering with Business Management and in the taught Masters in Engineering Management at. the University of York. It is also a popular option module for all Electronic Engineering undergraduate programmes. It is traditionally assessed by a 2 question from 4 closed book exam testing students’ knowledge and understanding of the subject at its application to Engineering business problems. One of the many consequences of Covid was the inability to hold closed book exams and a switch mas made to an open book exam where students were required to answer 4 from 4 questions. This change had the advantage of testing more of the module learning outcomes but the disadvantages of opening the module up for cheating and a doubling of the marking load. With the cohort size just under 200 students the issuing of all students with a unique exam was trialed together with automatically marking as much as possible. The pilot was successful in that a unique exam was sent to 94% of the students and most questions could be marked automatically. The paper describes the automation process and provides recommendations on how this could be improved up.
{"title":"Experiences in the use of a unique open-book exam paper for every student in a cohort.","authors":"Anthony Ward","doi":"10.1109/ITHET56107.2022.10031955","DOIUrl":"https://doi.org/10.1109/ITHET56107.2022.10031955","url":null,"abstract":"Accounting and Finance is a core module for undergraduate students taking the Bachelor or Integrated Undergraduate Masters in Electronic Engineering with Business Management and in the taught Masters in Engineering Management at. the University of York. It is also a popular option module for all Electronic Engineering undergraduate programmes. It is traditionally assessed by a 2 question from 4 closed book exam testing students’ knowledge and understanding of the subject at its application to Engineering business problems. One of the many consequences of Covid was the inability to hold closed book exams and a switch mas made to an open book exam where students were required to answer 4 from 4 questions. This change had the advantage of testing more of the module learning outcomes but the disadvantages of opening the module up for cheating and a doubling of the marking load. With the cohort size just under 200 students the issuing of all students with a unique exam was trialed together with automatically marking as much as possible. The pilot was successful in that a unique exam was sent to 94% of the students and most questions could be marked automatically. The paper describes the automation process and provides recommendations on how this could be improved up.","PeriodicalId":125795,"journal":{"name":"2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121410197","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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