Grace Liping Guo

Abstract

Traditional and integrative health programmes often rely on experiential knowledge that is difficult to document, compare and study systematically. The challenge is not simply to digitise this knowledge, but to create research and learning structures that preserve context while generating usable evidence.
This presentation introduces the design of Daoland's emerging research and learning infrastructure. The model combines online education with structured questionnaires, semi-structured interviews, focus-group discussions and planned longitudinal participant follow-up. AI is being explored as a support layer for organising, synthesising and tracing qualitative and quantitative information, rather than as a substitute for practitioner judgement or scientific evaluation.
Using Daoland as a developing case, the presentation examines three design questions: how to connect subjective experience with measurable outcomes, how to sustain participant engagement over time, and how to preserve the integrity of traditional knowledge within digital systems. The aim is not to claim clinical efficacy, but to explore how stronger infrastructure can support future integrative-health research and education.

Biography

Grace Liping Guo is a cross-cultural strategist, programme designer and educator based in Amsterdam, working at the intersection of technology, AI, learning and human development. Her career spans international IT consulting, programme and project management, entrepreneurship, cross-cultural communication and education across China and Europe.
She holds two master's degrees, including an International MBA, and has experience designing programmes, digital systems and learning processes for international organisations and communities. She is also a yoga and meditation teacher with a long-standing interest in Chinese philosophy, holistic wellbeing and mind-body practices.
Grace is currently contributing to the development of Daoland's research and learning infrastructure. Her focus is on how digital tools and AI can support structured learning, participant feedback, documentation and future research without replacing practitioner judgement or oversimplifying traditional knowledge. Her broader interest is in building bridges between human experience, technology, evidence and culture.