ANONYMOUS ASSIGNMENT EVALUATION SYSTEM

Author

Vallapu Shiva Shankar, Ms. Varshini Priyamvada


Abstract

 Evaluation of assignments is a crucial part of the academic routine that allows to evaluate students' work and progress. However, conventional methods of assignment evaluation are not only time-consuming, but are also prone to certain forms of bias since evaluators can recognize identity of students. In order to overcome these problems, this paper introduces the Anonymous Assignment Evaluation System (AAES), a digital platform that provides means for the secure and anonymous evaluation of academic assignments. The platform offers a full assignment evaluation workflow that includes assignment creation, anonymous submission by the students, identification of anonymous assignments, evaluation of assignments according to the rubric, management and publishing of results of assignment evaluation. Students' identity is dissociated from their assignments through use of cryptographic anonymous tokens and encryption of identity-related information. The system is implemented as a multi-tenant web platform that utilizes such tools as MongoDB for data management, Redis for background processes and MinIO for file storage.


Keywords

Anonymous Evaluation, Assignment Assessment, Student Privacy, Cryptographic Security, Digital Education, Rubric-Based Evaluation, Academic Assessment, Web Application, Fair Evaluation, Multi-Tenant System.



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References


  1. M. Malouff et al., "The Risk of a Halo Bias as a Reason to Keep Students Anonymous During Grading," Teaching of Psychology, Vol. 40, No. 3, pp. 199–202, 2013.
  2. S. Bischoff et al., "A Quasi-Experimental Study of Ethnic and Gender Bias in University Grading," PLOS ONE, Vol. 16, 2021.
  3. Panadero & M. Alqassab, "An Empirical Review of Anonymity Effects in Peer Assessment, Peer Feedback, Peer Review, Peer Evaluation and Peer Grading," Assessment & Evaluation in Higher Education, 2019.
  4. Fraile et al., "Investigating Anonymity in Formative and Summative Peer Assessment: Effects on University Students’ Social-Affective Factors, Perceptions and Preference," Studies in Educational Evaluation, 2024.
  5. Panadero, M. Romero, & J. W. Strijbos, "The Impact of a Rubric and Friendship on Peer Assessment: Effects on Construct Validity, Performance, and Perceptions of Fairness and Comfort," Studies in Educational Evaluation, 2013.
  6. Black & D. Wiliam, "Assessment and Classroom Learning," Assessment in Education: Principles, Policy & Practice, Vol. 5, No. 1, pp. 7–74, 1998.
  7. Boud & N. Falchikov, "Rethinking Assessment in Higher Education: Learning for the Longer Term," Routledge, 2007.
  8. Sadler, "Beyond Feedback: Developing Student Capability in Complex Appraisal," Assessment & Evaluation in Higher Education, Vol. 35, No. 5, pp. 535–550, 2010.
  9. Panadero, "A Review of Self-Regulated Learning: Six Models and Four Directions for Research," Frontiers in Psychology, Vol. 8, 2017.
  10. D. Krippendorff, "Content Analysis: An Introduction to Its Methodology," SAGE Publications, 2018.
  11. Stallings et al., "Computer Security and Privacy in Educational Systems," International Journal of Educational Technology, 2020.
  12. Stallings, "Cryptography and Network Security: Principles and Practice," Pearson, 2017.
  13. Ferguson, B. Schneier, & T. Kohno, "Cryptography Engineering: Design Principles and Practical Applications," Wiley, 2010.
  14. Fowler, "Patterns of Enterprise Application Architecture," Addison-Wesley, 2002.
  15. Schwaber & J. Sutherland, "The Scrum Guide: The Definitive Guide to Scrum," 2020.

 

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