undergraduate student critical literacy with grades

the gap this fills

measurement literacy already means something in education and psychology: what a practitioner needs to know to build and interpret a measure — validity, reliability, how raw scores become summary statistics, how to account for error. in every existing version, the literacy belongs to the measurer.

i’m interested in the other side of that relationship. frameworks for personal data literacy say very little about what someone’s understandings and practices actually accomplish inside an institutional, high-stakes measurement system — or whether they give that person any control over the measure at all.

the definition

critical measurement literacy: the cognitive, reflexive, and embodied understandings and practices people develop within a measurement system that describes them.

what it claims to measure, what it measures in practice, how it is produced and used, and where you stand inside it. the word critical is doing real work there. it isn’t just recognising that a measure is constructed — following freire, it’s an awareness of the structural conditions that produce the system and position people within it.

i organise it by dimension rather than by domain, which is a departure from how pangrazio and selwyn structure personal data literacies:

• cognitive — closest to their data understandings.
• reflexive — closest to their data reflexivity.
• embodied — the dimension their framework doesn’t foreground, and the reason i restructured it. following lupton, people make sense of data about themselves through feeling, not only interpretation. leave that out and you miss most of what a grade does to someone.

how it ran

an interview study and a diary study at a large public us university, irb-reviewed and determined exempt. the setting matters: this university grades numerically from 0.7 to 4.0 in tenth-of-a-point increments, so students are handed an unusually fine-grained number to reason about.

• an 11-week diary study with 12 undergraduates writing weekly about grades.
• 7 semi-structured interviews.
• weekly codesigned sessions run as a directed research group, where participants chose the prompts and built the following week’s activities.
• participatory analysis — i taught open coding and participants coded their own entries, naming the categories in their own words.

agency within, not over

the argument the paper turns on. students accomplish a great deal with what they know: they locate themselves in the system, allocate effort against it, and act to protect a gpa. that is real agency, and it is agency within the measurement system.

what i found almost no evidence of is agency over it — any traction on what grades measure or how they get used. by freire’s standard, that falls short of critical consciousness, and the interesting question is why. the parts of grading students meet directly are points, weights, and conversions: the machinery of how a grade is calculated, never why the scheme takes that shape, who decided it, or how it might change.

so the adjustment runs one way. students change their effort, their courses, their conduct; the grading practice behind those decisions stays exactly where it was. that is mau’s metric society, and it has consequences for who ends up in which field — bowker and star would call it convergence, a classification system reshaping the world it classifies.

and critique sits right alongside compliance. plenty of participants could name the gap between what grades claim to measure and what they measure in practice. naming it did not make grades any less consequential to them.

the paper is in preparation and hasn’t been peer reviewed, so the findings behind this aren’t on the page yet. happy to talk them through — get in touch.

where it goes

this is the study the rest of my grades work grew out of — most directly the tools students build when the institution won’t show them their own data clearly.

the framework is built to travel. credit scores, rideshare ratings, and performance metrics are all institutionally mandated measures people live under without controlling — and my current work follows the same structure into ai-run hiring interviews.