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Proceedings of International Conference on Applied Innovation in IT  ·  2025/04/26  ·  Vol. 13  ·  Issue 1  ·  pp. 147–154
Automated Assessment of Student Queries in Redis
Yuliia Prokop
In recent years, the popularity of NoSQL systems has grown significantly due to their flexibility and high performance when working with large volumes of data. Redis is one of the most popular key-value stores actively used in industry and education. However, automated approaches for NoSQL assignment evaluation, especially those involving advanced Redis modules, remain underdeveloped. This paper presents a web-based system for automated assessment of students’ Redis queries, supporting basic structures (e.g., list, sorted set, and hash manipulation) and advanced features (RedisJSON and RediSearch). The system provides instant feedback on syntax errors, enabling students to correct mistakes and resubmit solutions in real-time. A pilot study with 42 master’s students showed that about 78% successfully mastered the basics of Redis on the first try, while only 39% passed advanced assignments. With repeated attempts and targeted feedback, overall success on advanced tasks increased to 76%, highlighting the importance of continuous, automated guidance. The paper also discusses typical errors logged by the system (inconsistent or incorrect key naming, syntax errors when setting key expiration, incorrect index creation or JSON field references, etc.). The results demonstrate that integrating an automated Redis query assessment into educational programs can significantly enhance student engagement and learning efficiency. The flexible and modular design of the proposed system allows easy extension to other NoSQL databases and provides valuable data for instructors to refine teaching materials.
NoSQL Redis Key-value Store Automated Assessment RedisJSON RediSearch Education Databases.
References
  1. DB-Engines, "DBMS popularity broken down by database model," DB-Engines, [Online]. Available: https://db-engines.com/en/ranking_categories. [Accessed: 19-Feb-2025].
  2. N. Tripathi, "Teaching NoSQL databases in higher education: A review of models, tools and methods," SSRN, 2024, [Online]. Available: http://dx.doi.org/10.2139/ssrn.4971813.
  3. M. Menzin, S. Mohan, D. R. Musicant, and R. Soori Murthi, "NoSQL in undergrad courses is no problem," in Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020, pp. 962-963, [Online]. Available: https://doi.org/10.1145/3328778.3366909.
  4. S. Mohan, "Teaching NoSQL databases to undergraduate students: a novel approach," in Proceedings of the 49th ACM Technical Symposium on Computer Science Education, 2018, pp. 314-319, [Online]. Available: https://doi.org/10.1145/3159450.3159554.
  5. M. Greiner, "Teaching NoSQL data models: a tutorial," in Proceedings of the 2021 AMCIS, 2021, Article 19.
  6. S. Kim, "Seamless integration of NoSQL class into the database curriculum," in Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, 2020, pp. 314-320, [Online]. Available: https://doi.org/10.1145/3341525.3387399.
  7. M. Lin, J. Jun, Y. Zhu, and C. Zhan, "Research on the teaching reform of database curriculum major in computer in big data era," in Proc. 2017 12th Int. Conf. Computer Science and Education (ICCSE), IEEE, 2017, pp. 570-573.
  8. B. Fowler, J. Godin, and M. Geddy, "Teaching case: introduction to NoSQL in a traditional database course," Journal of Information Systems Education, vol. 27, no. 2, p. 99, 2016.
  9. A. Bajaj and W. Bick, "The rise of NoSQL systems: research and pedagogy," Journal of Database Management, vol. 31, no. 3, pp. 67-82, 2020, [Online]. Available: https://doi.org/10.4018/JDM.2020070104.
  10. C. Costa and M. Santos, "Big data: State-of-the-art concepts, techniques, technologies, modeling approaches and research challenges," IAENG International Journal of Computer Science, vol. 44, pp. 285-301, 2017.
  11. W. Wu, "Assessing peer correction of SQL and NoSQL queries," in Proceedings of the 54th ACM Technical Symposium on Computer Science Education V.1, 2023, pp. 535-541.
  12. A. Alawini, P. Rao, L. Zhou, L. Kang, and P.-C. Ho, "Teaching data models with TriQL," in Proceedings of the 1st International Workshop on Data Systems Education, 2022, pp. 16-21.
  13. Z. Li, S. Yang, K. Cunningham, and A. Alawini, "Assessing Student Learning Across Various Database Query Languages," 2023 IEEE Frontiers in Education Conference (FIE), College Station, TX, USA, 2023, pp. 1-9, [Online]. Available: https://doi.org/10.1109/FIE58773.2023.10343409.
  14. R. Alkhabaz, S. Poulsen, M. Chen, and A. Alawini, "Insights from student solutions to MongoDB homework problems," in Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V.1, 2021, pp. 276-282, [Online]. Available: https://doi.org/10.1145/3430665.3456308.
  15. M. Chen, S. Poulsen, R. Alkhabaz, and A. Alawini, "A quantitative analysis of student solutions to graph database problems," in Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V.1, 2021, pp. 283-289, [Online]. Available: https://doi.org/10.1145/3430665.3456314.
  16. A. Werner, "Applying NoSQL data adapter with the learning paths mechanism for better knowledge transfer in the age of distance learning," Procedia Computer Science, vol. 207, pp. 3330-3339, 2022, [Online]. Available: https://doi.org/10.1016/j.procs.2022.09.424.
  17. A. Werner and M. Bach, "NoSQL e-learning laboratory-interactive querying of MongoDB and CouchDB and their conversion to a relational database," in Communications in Computer and Information Science, vol. 865, 2018, pp. 581-592, [Online]. Available: https://doi.org/10.1007/978-3-319-67792-7_56.

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