Blog 3

Rethinking the Average Learner in Economics

A recent learning experience that clearly assumed an “average” learner was in my international economics course, particularly when we studied abstract trade models such as the Richardian and Heckscher-Ohlin frameworks. Lectures moved quickly from equations to graphs to theoretical conclusions, often presenting fully completed diagrams and symbolic proofs in a single explanation. Implicitly, this structure assumed that all students could immediately interpret shifting PPF curves, connect labour coefficients to relative prices, and understand relationships such as real wage = price x marginal product in real time.

However, as the Inclusive Learning Design post reminds us, there is no such thing as an “average” learner (EDCI 335, 2026). The Inclusive Design Guide further emphasizes that learner variability is the norm, not the exception (Inclusive Design Research Centre [IDRC], n.d.). In this context, the traditional lecture format positioned speed, abstract reasoning, and mathematical fluency as universal strengths rather than variable skills. When content was delivered primarily through fast-paced visual graphs and equations, it created barriers for learners like me who need repetition, narrative explanation, or alternative representations to fully process abstract ideas.

Using Universal Design for Learning (UDL), this experience could be redesigned to better anticipate variability. First, applying multiple means of representation (CAST, 2018) would involve building graphs step-by-step instead of presenting them complete, pairing equations with plain-language explanations, and offering short recap videos or annotated summaries. Interactive graph simulations in a technology-mediated environment could further allow students to manipulate variables and observe changes dynamically.

Second, multiple means of engagement could support persistence. Low-stakes quizzes with immediate feedback and slower “concept walkthrough” recordings would reduce cognitive overload and allow students to revisit difficult ideas at their own pace.

Finally, incorporating multiple means of action and expression would diversify assessment. Rather than relying solely on timed exams, students could submit recorded problem explanations, annotated graph analyses, or scaffolded assignments that breal complex proofs into smaller steps.

This experience illustrates how higher education often designs for an imagined “average” learner. As inclusive design argues, barriers are frequently created by systems – not students (IDRC, n.d.). By intentionally designing for variability through UDL, we create more equitable pathways for all learners to achieve rigorous outcomes.

Reference list

CAST. (2018). Universal Design for Learning guidelines version 2.2. http://udlguidelines.cast.org

EDCI 335. (2026). Inclusive Learning Design. https://edtechuvic.ca/edci335/inclusive-learning-design/

Inclusive Design Research Centre. (n.d.). Inclusive Design Guide. https://guide.inclusivedesign.ca/