Background
Last term (Fall 2024) I led the unit Critical 1: Mathematics and Statistics for Data Science at CCI BSc Data Science and AI course. It was the first time I had the opportunity to arrange the entire unit from preparation to delivery and assessments. I wanted the unit to have a strong emphasis on the practical side of mathematics and statistics so that students can learn from examples, practical exercises, and projects.
Evaluation
The assessment has two elements. Element 1 is a composition of eight weekly submissions, similar to a quiz, with 2-3 multiple-choice questions corresponding to lecture contents and 1-2 written questions for students to report on the practical coding/programming exercises they did. Element 2 is an unseen time-constrained examination in which students work on a task sheet individually over one week and make a submission by the end.
I finished the marking for this unit before I read about the “Student understanding of assessment” paper (Berry O’donovan and Rust, 2004), which described an “explicit” to “tacit” framework for knowledge transfer. So this would be a timely opportunity to evaluate the two assessing elements according to the framework offered in the paper. The overall aim is to approach a balance between explicit and tacit aspects of the assessments.
Figure 1 reproduced from Berry O’donovan and Rust (2004)
Moving Forward
Examples/Mock Examination
Apart from the written marking criteria, I prepared a mocked examination for Element 2 (the examination), the mock gives a detailed breakdown of marks, and an illustration of how a completed task sheet is assessed. It acted as an exemplar in the spectrum between explicit and tacit processes (Berry O’donovan and Rust, 2004). However, I found implementing the mocked examination tricky because I do not want it to constrain what students think they will be assessed on, so instead of a full mock examination, I might reduce it into a set of (one or two) questions selected from a full examination, as a reduce exemplar next cohort.
Discussion/Feedback from the Instructor
The timeline towards the end of the unit got quite tight, I didn’t have time in class to discuss the mock exemplar. And timely discussion is indeed an important aspect of feedback exchanges since it gives time for retrospective discussion (Brooks, 2008). So for the next cohort of this unit I’ll make sure that (i) the weekly quizzes are checked in by myself or tutors, (ii) the task brief and mock/exemplar for the examination are published earlier, not toward the end of the unit.
Incorporating Formative Assessing Method
The mathematics and statistics unit combines foundational and practical learning outcomes. While I attempted to bring more practical elements into the assessment, some of the elementary math concepts are particularly harder to assess in a tacit project-based setting. For instance, calculating vector transformation might not be helpful in practical projects, but it’s a foundational element in the learning outcomes (knowledge) that need to be assessed.
The quizzes seem homogeneous in assessing this combination of foundational and practical knowledge. As discussed in the literature (Berry O’donovan and Rust, 2004), a combination of assessing methods around both the tacit aspect (learnt through experience) and the explicit aspect (disseminated knowledge). Therefore, to move forward, I will try to incorporate formative assessing methods in the future. For instance, replace the weekly quizzes with a weekly reflective blog, or a portfolio of practical exercises to be submitted by the end of the unit.
References
- Berry O’donovan, M.P., Rust, C., 2004. Know what I mean? Enhancing student understanding of assessment standards and criteria. Teaching in Higher Education 9, 325–335. https://doi.org/10.1080/1356251042000216642
- Brooks, K., 2008. Could do better? Students’ critique of written feedback. Networks 5.