Middlesex University has long been focused teaching our students the
practical skills they need for their careers. Taking this as our guiding
principle while revalidating our undergraduate mathematics programmes
we decided to radically rethink how we approached assessment to build in
more continuous assessment that could be contextualised in an authentic
way.
To prepare students for their mathematical careers we distinguish
between authentic assessment, that is submission formats that are
closely aligned with work tasks, and authentic problems, which use real
data, complicated real-life models or the kind of imprecise formulation
that typifies real-world problems.
In this talk we will discuss our rationale for this approach to learning and
teaching, we will give examples of our assessment approach and how we mitigate against the barriers to equality of opportunity that this approach
has made explicit.
Authentic assessment requires students to be confident with a variety of
submission formats. Following the pandemic we are increasingly
conscious of the digital divide between our students, not just in access to
technology but particularly in the skills and attitudes to using technology
for educational and productive purposes. We will detail how our authentic
assessment provision enables us to explicitly develop these important
technical skills in all our taught maths modules. For example, calculus
assessment uses visualisation technologies, and statistics assessment
includes obtaining datasets from trustworthy sources.
Finally, we will discuss plans to scale our approach to larger service
modules, and to incorporate the latest technological division between
students: the use of Large Language Models.