Are Learner Personas Warranted? A Fuzzy-Clustering Diagnostic of Level and Shape in Learning-Attitude Profiles

Designers may use learner personas to plan different content, feedback, or support for groups of students, but a clustering result alone does not establish that these groups represent distinct learner types. Whether such a categorical structure exists in the data deriving those personas is rarely tested. This paper therefore proposes an uncertainty-aware fuzzy learner-modeling framework in which fuzzy partitioning serves as a diagnostic instrument rather than as a means of generating learner types. The study applies the framework to six learning-attitude constructs measured in three undergraduate cohorts taking AI-supported courses at a Taiwanese university of technology (N = 107; 90 retained after response-quality screening). It estimates fuzzy c-means partitions for two to five clusters at the primary fuzzifier value m = 2.0, with the two- and three-cluster solutions re-estimated at m = 1.5 and m = 2.5 as sensitivity checks. The two-cluster solution is stable (adjusted Rand index = 0.891) and reasonably crisp, yet all centroids differ only in overall level. Elevation accounts for 71.0% of the standardized variance, clustering the shape component alone is uninformative, and the structural criterion consequently fails. The construct with the lowest within-person centered standardized score relates to cohort (Monte Carlo p = 0.009), but no statistically significant association with modal cluster membership is detected (Monte Carlo p = 0.240). These findings insufficiently support distinct configural learner personas in this sample, using this instrument and these six constructs. The paper contributes to debates on person-centered learner modeling by specifying a diagnostic sequence that examines profile shape before interpreting stable, concentrated fuzzy partitions as learner personas. The support-priority vector remains an exploratory description of within-person score contrasts; its instructional value has not been tested.