On 2 June 2025 at 12:15 Eerik Muuli will defend his doctoral thesis “Automating the assessment and feedback processes in IT teaching – improving creation and maintenance from the teaching staff perspective“ to obtain the degree of Doctor of Philosophy (in Computer Science).
Supervisor
Assoc. Prof. Marina Lepp, University of Tartu
Opponents
Prof. Natalie Kiesler, Technische Hochschule Nürnberg Georg Simon Ohm (Germany)
Prof. Lauri Malmi, Aalto University (Finland)
Summary
For the past few decades, IT (Information Technology) has seen continuous growth, creating a demand for skilled professionals and significantly increasing the number of students pursuing IT education. The increasing number of students brings a bigger workload on teaching staff, particularly in grading and providing feedback on programming assignments. This challenge is heavily affecting large-scale courses, where traditional manual assessment is no longer feasible.
This research focuses on exploring automation to reduce the workload of the teaching staff and developing automated systems that simplify the assessment and feedback process in programming courses. First, valuable insights were gathered from interviews with the teaching staff, exploring their needs and expectations. As a result, two key systems were developed.
The first system utilizes image recognition to automatically assess programming tasks with graphical outputs. This approach allows for a more creative and flexible assignment design, which was previously constrained by having to manually test these assignments. The system was tested and evaluated on multiple programming courses. As a result, this system has reduced the manual effort required from instructors and provided timely feedback to students.
The second system introduces a system that utilizes Test Specific Language (TSL) that simplifies the creation and maintenance of automated assessments. The system has a user-friendly interface, which makes automated assessments more accessible to teaching staff who may not have deep technical expertise. This approach standardizes the assessment process among different courses.
The implementation of these systems has shown significant results in reducing the workload on educators while maintaining the quality of assessment and feedback provided to students. The developed systems and gathered insights in this work can serve as a framework for future research and development.
The defence will be held also in Zoom (meeting ID: 670 504 9543, passcode: ati).
