Learning the Manchu Writing System: The Role of Intra‐Symbol Processing in Orthography Acquisition
Year: 2026
Type: article
Abstract: ABSTRACT Characteristics of the Manchu writing system provide an excellent testing ground for current theorizing about orthography acquisition. Using traditionally demarcated orthographic units called uju hergen —symbol blocks representing phonological syllables—we investigated the role of visual features and phonological representations in learning the Manchu symbol set. Novice Manchu learners ( n = 196; 89.8% female; M age = 18.79) participated in two experiments. Experiment 1 focused on visual complexity effects and Experiment 2 on mapping complexity effects and switching costs. Among visual characteristics, the number of connected points was found to make a unique contribution to uju hergen recognition. Naming error rate was lower for a list of uju hergen with single (one‐to‐one) mapping between a phoneme marker and sound compared to a matched list but with multiple (one‐to‐many) mapping. No switching cost was observed between lists with low‐ and high‐switching‐demand. Established explanatory constructs of grain size, orthographic depth, and orthographic breadth, referenced together as the construct of orthographic scale, explain the results. But reading uju symbol blocks also requires processing within symbol blocks: at the visual level, connected points provide the sub‐symbol cues to decompose discrete simple features and recompose them into phoneme markers; and at the level of phonological representation, the resultant markers must be read by appropriate symbol‐to‐sound mapping. Together, our study expands theorizing on orthography acquisition by bringing focus on the under‐studied construct of intra‐symbol processing.
Source: Reading Research Quarterly
DOI: 10.1002/rrq.70106
Authors: Bai Li, Victoria Murphy, Sonali Nag
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,530
Awards: G2624984290, G7962775832
OpenAlex ID: W7147544214
