Writing development is often assessed through aggregate improvements in surface-level features, yet less attention has been given to how multiple linguistic dimensions evolve jointly over time. We model writing development as a multidimensional system shaped by stable individual variation and instructional progression across staged assignments, using interpretable linguistic features from the Writing Analytics Toolkit (WAT) and transformer-based sentence embeddings.Variance partitioning reveals substantial between-student stability alongside stage-dependent change. Mixed-effects models identify non-uniform developmental trajectories: academic focus, information density, and conventional language increase, whereas development of ideas and lexical variety decline, indicating tradeoffs across competing dimensions. Cross-lagged analyses further show dynamic dependencies between dimensions, suggesting coordinated change rather than independent progression.Embedding-based analyses capture stage-dependent shifts in semantic representation, with larger changes in earlier stages and increasing stability over time. Although assignment structure contributes to observed variation, stable individual differences and cross-stage dependencies indicate underlying developmental processes that generalize across tasks.Together, these findings characterize writing development as structured change in a multidimensional representational system, highlighting the need for computational models that capture stable variation, non-monotonic trajectories, and interactions among linguistic components.