In preparation for this
oral
exam, students are given a list of 20-30 questions from across the course (these questions cover all of the significant theorems covered over the semester). On the day of the assessment, the student is randomly assigned 2 of these questions and given 30-45 minutes to write their answers (answers consist of the statement of the theorem and the proof) on the blank paper provided. Students are observed whilst writing. Each student is then questioned for 15 minutes, and this oral component is
video
recorded. They are first questioned about their
written
responses and must defend their answers (staff highlight any mistakes or gaps in their responses). They are then asked further questions about other aspects of the course.
Advantages
This assessment is identity verified and covers all the course material so therefore allows a reliable measure of student learning.
Challenges
Two course staff (may include tutors such as graduate students) must assess each student which takes considerable resources. However, marking is done on the spot so there are therefore trade-offs with the more common methods of assessment that require time for marking (e.g. assignments or exam scripts). May not be possible in larger courses (over 40 students) as it may take too much time to be viable.
Tips for implementation
To ensure this assessment is adequately moderated two staff are needed.
Learning outcomes
A complete and comprehensive knowledge of the theoretical basis of the course. A deep understanding of the important theoretical constructions featured in the course. An ability to link theory with applications and analyse examples.
How it supports academic integrity
This is an identity-verified assessment. Students are observed completing their
written
responses, and then must also demonstrate their knowledge in a conversation with course staff.
PLEASE NOTE: The academic integrity information displayed on this page is currently under review. Some examples and descriptions were developed before the widespread availability of generative AI tools and may not reflect current approaches to assessment security. When adapting an assessment idea, staff should consider how the design supports authorship, verifies student achievement of learning outcomes, and mitigates inappropriate use of AI and other forms of academic misconduct.
