Cognitive strategies in interpreting UML class diagrams with emphasis on load, order and symbolic confusion

Abstract

Unified Modelling Language (UML) class diagrams are critical in computing education, yet students face significant cognitive challenges in interpreting these complex visual-technical representations. This study examines three dimensions: cognitive load (mental effort), order (the sequential analytical strategies students employ), and symbolic confusion (misinterpretation of UML notation). Building on prior semiotic analyses of UML class diagram cognition, this exploratory study, using thematic analysis, applies Cognitive Load Theory (CLT) to examine how 11 first-year computing students at a South African university manage mental load during the interpretation of UML class diagrams. Through the semi-structured interviews, student-created artefacts, and systematic behavioural observations across three activities of increasing complexity (simple element identification, relationship analysis, and complex diagram construction), we identified four primary cognitive strategies: analytical sequencing and prior knowledge; symbolic confusion and clarification; diagram orientation and redrawing; and cognitive load management through decomposition. Participants demonstrated metacognitive awareness of working memory limits, employing adaptive strategies like spatial rearrangement, symbolic error correction, and systematic breakdown of visual complexity. Two key sources of extraneous load emerged: symbolic confusion from ambiguous notation and spatial disorientation from unconventional layouts, prompting compensatory behaviours such as diagram redrawing and self-correction. This exploratory study provides preliminary evidence for the potential application of CLT to diagrammatic reasoning, suggesting that these participants acted as active cognitive agents. Given the exploratory nature of this study, pedagogical implications tentatively suggest the value of explicit training in systematic analysis, symbol fluency, standardised visual designs, and metacognitive strategies. These findings require validation through larger-scale studies before broader implementation recommendations can be made. These findings inform cognitive load management in technical education and suggest directions for broader validation.