Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework

Yi Zhang; Peiya Zhang; Yanbin Zhang; Cheqing Jin; Wei Wang; Bin Su

doi:10.1007/978-981-97-7707-5_50

Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework

Yi Zhang
, Peiya Zhang
, Yanbin Zhang^*
, Cheqing Jin
, Wei Wang
, Bin Su

^*Corresponding author for this work

School of Data Science and Engineering

East China Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The rapid expansion of online education has highlighted the critical need for a reliable and efficient learning evaluation framework. To address this challenge, we propose a blockchain-powered framework for assessing educational behavior indicators. Leveraging blockchain's tamper-proof and traceable characteristics, the framework ensures the security and authenticity of educational data. By integrating multi-source data from the Shuishan Online platform and adopting a multi-dimensional evaluation perspective, the framework comprehensively assesses students’ online learning performance. Implementation in a real educational scenario demonstrates the framework's effectiveness in providing credible and comprehensive evaluations of students’ learning outcomes, paving the way for a transparent, efficient, and equitable educational environment.

Original language	English
Title of host publication	Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings
Editors	Cheqing Jin, Shiyu Yang, Xuequn Shang, Haofen Wang, Yong Zhang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	604-612
Number of pages	9
ISBN (Print)	9789819777068
DOIs	https://doi.org/10.1007/978-981-97-7707-5_50
State	Published - 2024
Event	21st CCF Conference on Web Information Systems and Applications in China, WISA 2024 - Yinchuan, China Duration: 2 Aug 2024 → 4 Aug 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14883 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st CCF Conference on Web Information Systems and Applications in China, WISA 2024
Country/Territory	China
City	Yinchuan
Period	2/08/24 → 4/08/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education

Keywords

Blockchain
Learning Evaluation
Online Learning

Access to Document

10.1007/978-981-97-7707-5_50

Cite this

Zhang, Y., Zhang, P., Zhang, Y., Jin, C., Wang, W., & Su, B. (2024). Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework. In C. Jin, S. Yang, X. Shang, H. Wang, & Y. Zhang (Eds.), Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings (pp. 604-612). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14883 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-7707-5_50

Zhang, Yi ; Zhang, Peiya ; Zhang, Yanbin et al. / Enhancing Online Education Assessment : A Blockchain-Powered Reliable Behavior Indicator Assessment Framework. Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings. editor / Cheqing Jin ; Shiyu Yang ; Xuequn Shang ; Haofen Wang ; Yong Zhang. Springer Science and Business Media Deutschland GmbH, 2024. pp. 604-612 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The rapid expansion of online education has highlighted the critical need for a reliable and efficient learning evaluation framework. To address this challenge, we propose a blockchain-powered framework for assessing educational behavior indicators. Leveraging blockchain's tamper-proof and traceable characteristics, the framework ensures the security and authenticity of educational data. By integrating multi-source data from the Shuishan Online platform and adopting a multi-dimensional evaluation perspective, the framework comprehensively assesses students{\textquoteright} online learning performance. Implementation in a real educational scenario demonstrates the framework's effectiveness in providing credible and comprehensive evaluations of students{\textquoteright} learning outcomes, paving the way for a transparent, efficient, and equitable educational environment.",

keywords = "Blockchain, Learning Evaluation, Online Learning",

author = "Yi Zhang and Peiya Zhang and Yanbin Zhang and Cheqing Jin and Wei Wang and Bin Su",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 21st CCF Conference on Web Information Systems and Applications in China, WISA 2024 ; Conference date: 02-08-2024 Through 04-08-2024",

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language = "英语",

isbn = "9789819777068",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

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Zhang, Y, Zhang, P, Zhang, Y, Jin, C , Wang, W & Su, B 2024, Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework. in C Jin, S Yang, X Shang, H Wang & Y Zhang (eds), Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14883 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 604-612, 21st CCF Conference on Web Information Systems and Applications in China, WISA 2024, Yinchuan, China, 2/08/24. https://doi.org/10.1007/978-981-97-7707-5_50

Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework. / Zhang, Yi; Zhang, Peiya; Zhang, Yanbin et al.
Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings. ed. / Cheqing Jin; Shiyu Yang; Xuequn Shang; Haofen Wang; Yong Zhang. Springer Science and Business Media Deutschland GmbH, 2024. p. 604-612 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14883 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Enhancing Online Education Assessment

T2 - 21st CCF Conference on Web Information Systems and Applications in China, WISA 2024

AU - Zhang, Yi

AU - Zhang, Peiya

AU - Zhang, Yanbin

AU - Jin, Cheqing

AU - Wang, Wei

AU - Su, Bin

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

PY - 2024

Y1 - 2024

N2 - The rapid expansion of online education has highlighted the critical need for a reliable and efficient learning evaluation framework. To address this challenge, we propose a blockchain-powered framework for assessing educational behavior indicators. Leveraging blockchain's tamper-proof and traceable characteristics, the framework ensures the security and authenticity of educational data. By integrating multi-source data from the Shuishan Online platform and adopting a multi-dimensional evaluation perspective, the framework comprehensively assesses students’ online learning performance. Implementation in a real educational scenario demonstrates the framework's effectiveness in providing credible and comprehensive evaluations of students’ learning outcomes, paving the way for a transparent, efficient, and equitable educational environment.

AB - The rapid expansion of online education has highlighted the critical need for a reliable and efficient learning evaluation framework. To address this challenge, we propose a blockchain-powered framework for assessing educational behavior indicators. Leveraging blockchain's tamper-proof and traceable characteristics, the framework ensures the security and authenticity of educational data. By integrating multi-source data from the Shuishan Online platform and adopting a multi-dimensional evaluation perspective, the framework comprehensively assesses students’ online learning performance. Implementation in a real educational scenario demonstrates the framework's effectiveness in providing credible and comprehensive evaluations of students’ learning outcomes, paving the way for a transparent, efficient, and equitable educational environment.

KW - Blockchain

KW - Learning Evaluation

KW - Online Learning

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DO - 10.1007/978-981-97-7707-5_50

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AN - SCOPUS:85205116212

SN - 9789819777068

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 604

EP - 612

BT - Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings

A2 - Jin, Cheqing

A2 - Yang, Shiyu

A2 - Shang, Xuequn

A2 - Wang, Haofen

A2 - Zhang, Yong

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 2 August 2024 through 4 August 2024

ER -

Zhang Y, Zhang P, Zhang Y, Jin C , Wang W, Su B. Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework. In Jin C, Yang S, Shang X, Wang H, Zhang Y, editors, Web Information Systems and Applications - 21st International Conference, WISA 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 604-612. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-981-97-7707-5_50

Enhancing Online Education Assessment: A Blockchain-Powered Reliable Behavior Indicator Assessment Framework

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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