Category: Socoles

Welcome to Databases

Welcome to Information Modelling & Databases, Part B, Databases! We will resume Tuesday 5 November with a lecture at 15:30h. in EOS N 01.630.

The Databases part contains mandatory, individual quizzes, for which the following honour code applies:

  • You do not share the solutions;
  • The solutions to the quizzes should be your own work;
  • You do not post the quizzes, nor the solutions anywhere online;
  • You do not use instruction-tuned large language models like Github Copilot or ChatGPT;
  • You are allowed, and encouraged, to discuss the quizzes, and to ask clarifying questions to your fellow students; Please use the Brightspace Discussion Forum to reach out to me, the teaching assistants and your fellow students.

New this year are the optional SQL Mastery Assignments for students that want to go the extra mile. Students that successfully submit solutions to the SQL Mastery Assignments get free travel and participation to DuckCon #6 in Amsterdam on 31 January 2025!!

Also this year, we will experiment with a new automatic grader called Socoles that will automatically give feedback on open questions that require SQL solutions. Socoles is developed by Benard Wanjiru. Socoles helps us grade the assignments for more than 300 students in the course. Of course, you will get human feedback too, during the tutorials on Friday mornings.

Wishing you a fruitful Part B!
Best wishes,  Djoerd Hiemstra

Sensitivity of Automated SQL Grading in Computer Science Courses

by Benard Wanjiru, Patrick van Bommel, and Djoerd Hiemstra

Previous research has primarily relied on fixed procedures when implementing partial grading systems. As a result, the sensitivity of such systems in terms of error analysis becomes inflexible as well. In this paper, we employ a software correctness model that allows for a dynamic and flexible approach for adjusting the sensitivity of a grading system based on the user’s needs and goals. We show how partial grading can be used to award fair grades and also categorize students into groups based on their strengths and weaknesses observed in their answers. Furthermore, we show how the sensitivity of a grading system can be varied to allow such grouping. To illustrate this, we analysed more than 2000 answers for 6 SQL programming assignments. An implication of this study is that instructors can carry out more effective partial grading of SQL queries as well as adjust learning material based on the needs of a particular group of students. They can address the observed limitations, thereby bridging the gap between high-performing students and those that require additional attention.

To be presented at the third International Conference on Innovations in Computing Research (ICR) on August 12–14, 2024 in Athens, Greece.

[download pdf]

Towards a Generic Model for Classifying Software into Correctness Levels and its Application to SQL

by Benard Wanjiru, Patrick van Bommel, and Djoerd Hiemstra

Automated grading systems can save a lot of time when carrying our grading of software exercises. In this paper, we present our ongoing work on a generic model for generating software correctness levels. These correctness levels enable partial grades of students’ software exercises. The generic model can be used as a foundation for correctness of SQL queries and can be generalized to different programming languages.

To be presented at the SEENG 2023 Workshop on Software Engineering for the Next Generation of the 45th International Conference on Software Engineering on Tuesday 16 May in Melbourne, Australia.

[download pdf]