Abstract
Eye-movement studies of manual production often average gaze across an entire trial, obscuring how visual information use changes once actions begin. We separated the pre-writing and writing phases in a fixed progressive Chinese calligraphy task. Thirty-seven postgraduate students completed two style-guided transfer (SGT) pages, a worked example, and two evolution-based mapping (EBM) pages; 34 contributed usable gaze data. On SGT pages, reference allocation fell from 0.626 before writing to 0.131 during writing, whereas the share of reference viewing directed to diagnostic tokens rose from 0.473 to 0.601. On EBM pages, allocation to the cue-plus-context display fell from 0.825 to 0.447 after pen onset but remained substantial; cue share and context coverage also declined. Participant-level process blocks did not improve quality models. In exploratory page-level EBM analyses, greater pre-writing context coverage was associated with higher product quality. These findings identify pen onset as a useful boundary for analyzing visual information use in constrained production: external sampling is greatest before writing, and task-specific re-access persists during execution. Because the task order was fixed, page-family differences cannot be separated from practice or scaffolding. Phase-specific area-of-interest measures can therefore add process information to product scores without treating gaze as a direct measure of cognition.
| Original language | English |
|---|---|
| Number of pages | 15 |
| Journal | Journal of Eye Movement Research |
| Volume | 19 |
| Issue number | 4 |
| Early online date | 30 Jun 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 30 Jun 2026 |
Bibliographical note
Acknowledgments: The authors thank Shiwei He and Yi Zheng for research assistance, including support with experimental setup and participant‑session coordination. During the preparation of this manuscript, the authors used generative artificial intelligence tools (ChatGPT, OpenAI; 5.5) for language editing and phrasing support. All AI‑assisted text was reviewed and revised by the authors, who take full responsibility for the manuscript.Funding
Funding: This research was funded by the University Grants Committee (UGC), Hong Kong, Fund for Innovative Technology‑in‑Education (FITE), project title “Bridging in Web 3.0: Engaging Business Student in the Metaverse Office for Virtual Internship”.
Keywords
- eye tracking
- gaze allocation
- Chinese calligraphy
- external visual information
- eye–hand coordination
- response processes
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