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AssessChain: A Hybrid Blockchain-Based System for Transparent and Reliable Online Assessment

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Title: AssessChain: A Hybrid Blockchain-Based System for Transparent and Reliable Online Assessment
Language: English
Authors: Ye Qingyi (ORCID 0000-0002-9461-7049), Wang Liangmin, Pan Senshan, Zhang Yifan, Li Jiayi
Source: Education and Information Technologies. 2024 29(15):20665-20689.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 25
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Information Technology, Electronic Learning, Online Courses, Assessment Literacy, Computer Software Evaluation, Evaluation Methods, Evaluation Problems, Trust (Psychology)
DOI: 10.1007/s10639-024-12713-z
ISSN: 1360-2357
1573-7608
Abstract: Information technology advancements have facilitated the widespread adoption of online education, providing learners with more flexible and convenient means of accessing educational resources and completing learning tasks. To improve the quality of online education and promote collaborative learning, online assessment is crucial in this transition. However, there are concerns about the transparency of the existing online assessment system. Centralized control by educational authorities restricts user access to the assessment process, resulting in a lack of user trust in assessment outcomes. Moreover, the abundance of online users also raises concerns about the reliability of assessors. In this paper, we present "AssessChain," a decentralized system that integrates hybrid blockchains to make all assessment procedures, including set criteria, feedback, calculation, and moderation, visible and verifiable to users. Besides, AssessChain introduces an assessor selection scheme (ASEL) employing an enhanced density clustering algorithm to ensure the reliability of assessors, avoiding low-quality feedback. We have implemented the system and proved that the performance is reasonable in terms of throughput and latency, and the proposed ASEL can generally identify malicious assessors with more than 95% accuracy. By integrating information technology, the system encourages all educational participants to trust the assessment process and results, which helps promote equity in educational assessment.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1449333
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Ye+Qingyi%22">Ye Qingyi</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9461-7049">0000-0002-9461-7049</externalLink>)<br /><searchLink fieldCode="AR" term="%22Wang+Liangmin%22">Wang Liangmin</searchLink><br /><searchLink fieldCode="AR" term="%22Pan+Senshan%22">Pan Senshan</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang+Yifan%22">Zhang Yifan</searchLink><br /><searchLink fieldCode="AR" term="%22Li+Jiayi%22">Li Jiayi</searchLink>
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Information technology advancements have facilitated the widespread adoption of online education, providing learners with more flexible and convenient means of accessing educational resources and completing learning tasks. To improve the quality of online education and promote collaborative learning, online assessment is crucial in this transition. However, there are concerns about the transparency of the existing online assessment system. Centralized control by educational authorities restricts user access to the assessment process, resulting in a lack of user trust in assessment outcomes. Moreover, the abundance of online users also raises concerns about the reliability of assessors. In this paper, we present "AssessChain," a decentralized system that integrates hybrid blockchains to make all assessment procedures, including set criteria, feedback, calculation, and moderation, visible and verifiable to users. Besides, AssessChain introduces an assessor selection scheme (ASEL) employing an enhanced density clustering algorithm to ensure the reliability of assessors, avoiding low-quality feedback. We have implemented the system and proved that the performance is reasonable in terms of throughput and latency, and the proposed ASEL can generally identify malicious assessors with more than 95% accuracy. By integrating information technology, the system encourages all educational participants to trust the assessment process and results, which helps promote equity in educational assessment.
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