Hybrid Scratch-to-Python Pathways vs Pure-Track Approaches: A Literature Synthesis

Does a hybrid Scratch-to-Python pathway, structured around an explicit and scaffolded transition between the two environments, outperform pure-track approaches — either Scratch-only continued upward or Python-direct from entry — on transfer to text-based programming? The question matters for Vietnamese K-12 informatics where Scratch dominates primary instruction and Python is mandated from grade 10, leaving a five-to-seven-year gap that supplementary materials must bridge. We synthesise eight literature strands: MeerbaumSalant and Armoni on persistent Scratch-era habit patterns; Weintrop-Wilensky on the short-run motivational and conceptual advantages of block-first that decay without explicit transition; Bau et al. on the Pencil Code and Droplet vertical-editor design that toggles block and text representations of the same source; Hermans on Hedy as a graded text-based language that converges on Python over twelve levels; Harvey and Mönig on Snap! as a dual-mode environment extending Scratch upward; Sentance and Waite on the PRIMM (Predict-Run-InvestigateModify-Make) pedagogy that has become the canonical postblock scaffold; Moors and colleagues on the four-way taxonomy of transition designs; and du Boulay and Sorva on the notionalmachine gap that any transition must close. We organise the design space along three axes — vertical (block-to-text within one tool), horizontal (Scratch then Python with an explicit bridge curriculum), and dual-modality concurrent — and synthesise effect-size predictions stratified by learner age band. We catalogue four failure modes of poorly engineered hybrids: Scratch habit lock-in; semantic discontinuity at the bridge; motivational cliff at first text error; bridge-as-recapitulation collapse. We close with six design rules that distinguish an effective hybrid from a nominal one. The recommendation: a horizontal hybrid with PRIMM-style bridge curriculum is the strongest candidate for the Vietnamese mainstream cohort; the Python-direct path examined in node A2.5 retains its case for the gifted cohort.