Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
STUDY ON CURRICULUM MECHANISMS AND PATHS OF ATTENTION TRAINING FOR ALL, IN CHINA
Wenyang WAN; Avril ACCOLLA
Type:
Year:
2025
Editor:
Yong Se Kim; Yutaka Nomaguchi; Cees de Bont; Jianxi Luo; Xiaofang Yuan; Linna Hu; Meng Wang
Author:
Series:
Other endorsed
Institution:
Tongii University, China
Page(s):
347-358
Abstract:
Through a comparative analysis of 50 global nature-education programmes, this study concludes that nature-based activities are uniquely suited for cultivating perceptual and attentional skills in young children, and can support children with ADHD:a Design for All approach. Building on this foundation, we propose an empirical study on the Relax–Train Swap Model (RTSM), a novel training framework for children aged 2–7. The RTSM integrates 5-minute low-stimulation nature exposure (informed by Attention Restoration Theory) with 5- to 10-minute blocks of the “Find–Observe–Draw” (FOD) task.This FOD sequence is designed to engage core attentional processes: finding targets inhibitory control, observing sustains attention, and drawing triggers cognitive flexibility through perspective shifts. Embedded in a Relax–Train–Relax loop, the model posits that nature education can be transformed from cognitive restoration into a measurable pathway for ecological literacy and holistic development. This study proposes a model's curriculum integration with real-time observational quantification, turning "nature exposure" into "visible attention training." A challenge is posed by overgeneralization, since outcomes are moderated by contextual factors like teacher expectancy. Future work will focus on empirical validation of the proposed mechanisms and enhancing the model's local adaptability for scalable application.
Keywords:
