Conceptual framework
Define the design variables, terminology, evidence boundaries, and research agenda of Scientific Song Design.
Lingling Liu · 刘玲伶
Researching how songs can be designed for learning.
Researcher, author, founder of Scientific Song Design, founder of SSDLL, and founder and representative director of ProoProo.
About
From educational technology to Scientific Song Design
My work examines the intersection of language learning, music, learning science, educational technology, and AI-generated songs.
I earned a master’s degree from the Graduate School of Frontier Sciences at the University of Tokyo. My earlier work included the development and evaluation of three-dimensional hologram teaching materials for primary science education.
Current focus
- Scientific Song Design as a testable interdisciplinary framework
- Song Sequence Architecture across multiple songs
- Long-term vocabulary retention and retrieval
- AI-generated music in English, Chinese, and Japanese language education
- Research translation into books, tools, and learning systems
Research
A research programme connecting theory, trials, and implementation
The central objective is to make educational song design more explicit, measurable, cumulative, and open to empirical improvement.
Empirical studies
Test vocabulary, grammar, listening, engagement, transfer, and delayed retention under defined conditions.
Research translation
Develop books, song sequences, teacher resources, prototypes, and international localisation models.
Selected publications
Frameworks and books
Formal titles are preserved exactly. Records marked 【待定】 require final publication data before launch.
SSD
0.1.1
0.1.1
Scientific Song Design (SSD): A Conceptual Framework for Designing Songs for Language Learning
Version 0.1.1 Public Consultation Draft. DOI: 10.5281/zenodo.21613887.
View official record →BOOK
2023
2023
A review of prior research on the use of songs in language education and the potential of AI-generated songs: Cases from English, Chinese, and Japanese.
ProoProo. ISBN 978-4-911177-66-2. DOI: 【待定】
Research monograph title: 【待定】
Topic: Scientific Song Design and long-term learning. Final title, ISBN, DOI, and release date: 【待定】
Publication list and downloadable CV
CV file, complete citation list, Google Scholar profile, and ORCID link: 【待定】
Selected presentations
International research communication
Selected 2025 presentations on AI-generated music and language learning.
Harnessing AI-Generated Music for English Grammar Mastery: A Groundbreaking Study
8th International Conference on Advanced Research in Education, University of Oxford.
Enhancing Multilingual Vocabulary Acquisition with AI-Generated Music
8th World Conference on Research in Teaching and Education.
Enhancing Chinese Vocabulary Acquisition in Thai University Students Using AI-Generated Music
With Jumphol Thawornchob. 5th Southeast Asian Conference on Education.
Unlocking the Power of AI-Generated Music — English Vocabulary Learning
International Conference on Research in Education, Teaching and Learning. Final conference wording: 【待定】
Timeline
Building a connected research ecosystem
The personal website connects the researcher, the academic platform, the association, and the research-driven company without collapsing their distinct roles.
- Founded ProoProoResearch-driven education, publishing, and learning products.
- Published a monograph on songs in language education and AI-generated songs
- Presented multiple studies on AI-generated music and language learning
- Founded SSDLLInternational Association for Scientific Song Design and Language Learning.
- Published SSD Version 0.1 and Version 0.1.1
Connect
Research, publishing, speaking, and collaboration
For research collaboration, invited talks, publishing, media, or institutional enquiries.
Contact email: 【待定】 · Media kit: 【待定】