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I am a Teaching Fellow and PhD student in the Department of Informatics. I obtained my MSci in Computer Science from Royal Holloway, University of London.

My research focuses on the automated assessment of code quality and programming assessment.

Before my PhD, I worked as a full-stack software engineer within a data analytics company and was responsible for various projects, including data ingestion and web-based data visualization.

Research Topics

  • Computer Science Education
  • Programming Education
  • Automated Assessment
  • Natural Language Processing
  • Software Tools
  • Human-Computer Interaction

Key Projects

Menagerie: A Dataset of Graded CS1 Assignments

The Menagerie dataset consists of a second semester CS1 assignment that ran over four academic years (18/19 - 21/22). It consists of 667 total submissions, with 273 of those being subsequently graded post hoc as part of a study into the consistency of human graders, and includes final grades and feedback for correctness, code elegance, readability and documentation.

OpenScienceFoundation

Grants

  • College Teaching Fund - King’s College London - £10,222.50

Publications

  1. Messer, M., Brown, N. C. C., Kölling, M., & Shi, M. (2024). How Consistent Are Humans When Grading Programming Assignments? https://arxiv.org/abs/2409.12967
  2. Messer, M., Shi, M., Brown, N. C. C., & Kölling, M. (2024). Grading Documentation with Machine Learning. In A. M. Olney, I.-A. Chounta, Z. Liu, O. C. Santos, & I. I. Bittencourt (Eds.), Artificial Intelligence in Education (pp. 105–117). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-64302-6_8
  3. Messer, M., Brown, N. C. C., Kölling, M., & Shi, M. (2024). Automated Grading and Feedback Tools for Programming Education: A Systematic Review. ACM Trans. Comput. Educ., 24(1). https://doi.org/10.1145/3636515
  4. Messer, M., Brown, N. C. C., Kölling, M., & Shi, M. (2023). Machine Learning-Based Automated Grading and Feedback Tools for Programming: A Meta-Analysis. Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1, 491–497. https://doi.org/10.1145/3587102.3588822
  5. Messer, M. (2022). Grading Programming Assignments with an Automated Grading and Feedback Assistant. In M. M. Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (pp. 35–40). Springer International Publishing.
  6. Messer, M. (2022). Detecting When a Learner Requires Assistance with Programming and Delivering a Useful Hint. In A. Mitrovic & N. Bosch (Eds.), Proceedings of the 15th International Conference on Educational Data Mining (pp. 778–781). International Educational Data Mining Society. https://doi.org/10.5281/zenodo.6852958
  7. Messer, M. (2022). Automated Grading and Feedback of Programming Assignments. Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 2, 638–639. https://doi.org/10.1145/3502717.3532113