Researcher in Language Education and Scientific Song Design
Making learning songs researchable.
My work develops conceptual and methodological foundations for designing, documenting, sequencing, and evaluating songs for language learning.
About
Lingling Liu is a researcher developing Scientific Song Design (SSD), an interdisciplinary framework for the systematic design, documentation, sequencing, and evaluation of learning songs and song sequences.
Her current work focuses on vocabulary acquisition, long-term retention, multilingual language learning, and AI-assisted educational song design. Drawing on more than a decade of experience in language education, together with professional experience in simultaneous interpretation, she connects research development with multilingual teaching and communication practice.
Education
Research architecture
Current research examines Scientific Song Design across English, Chinese, and Japanese language-learning contexts through one overarching programme, a design architecture, an empirical pathway, and a clearly defined learning focus.
Overarching research programme
A proposed interdisciplinary research programme for the systematic design, documentation, evaluation, and iterative improvement of learning songs and song sequences.
DesignDocumentSequenceEvaluate
A proposed cross-song music–language relational architecture that makes relations between target-language content and musical or sonic features explicit, inspectable, and testable.
Research on retention, retrieval, transfer, implementation, learner experience, safety, and calibrated evidence claims in song-supported language learning.
Research on how systematically designed songs and song sequences may support vocabulary acquisition, retrieval, spaced review, and long-term retention across languages and learner age groups.
Generative AI is treated as a design and research tool rather than as a standalone research field.
Selected work
Foundational work is presented with its publication type, version, evidence status, and persistent record.
Featured research · SSD Foundation Series
Song Sequence Architecture and Research Agenda
The document sets out the SSD research programme, develops Song Sequence Architecture as its core construct, and proposes the research agenda through which both should be empirically tested.
Scientific Song Design is currently under theoretical development and public consultation. The present framework has not yet undergone formal external peer review, and its educational effectiveness should not be regarded as established.
Read on Zenodo ↗
English original · Japanese & Chinese extended abstracts
Foundational monograph2023
Case Studies in English, Chinese, and Japanese
This cross-language review surveys preliminary studies on song utilization in language education across English, Chinese, and Japanese contexts and examines the potential of AI songs. The publication contains an English original with Japanese and Chinese extended abstracts.
Published before the formal proposal of SSD, it represents an early scholarly foundation in Lingling Liu's research trajectory toward Scientific Song Design.
Research trajectory
Presentations
2025
Lingling Liu · 8th Japan AI Music Society Forum · Senzoku Gakuen College of Music · 12 October 2025
Lingling Liu · 8th International Conference on Advanced Research in Education · Oxford, UK · 27 March 2025
Lingling Liu · The 8th World Conference on Research in Teaching and Education (WORLDTE2025) · Germany · 14 March 2025
Lingling Liu and Jumphol Thawornchob · The 5th Southeast Asian Conference on Education (SEACE2025) · Malaysia · 21 February 2025
Lingling Liu and Zhentao Xu · EduCon Tokyo 2025 — International Conference on Education · Tokyo · 20–21 January 2025
2024
Lingling Liu and Yuanyuan Zhang · The 16th Asian Conference on Education (ACE2024) · Tokyo · 25 November 2024
Leadership & implementation
Three complementary roles connect field building, scholarly publication, and the translation of research concepts into practice.
Association
International Association for Scientific Song Design and Language Learning
Founder & President
An academic association supporting research dialogue, standards development, publication, and international collaboration in Scientific Song Design and language learning.
Visit SSDLL ↗Association journal
Journal of Scientific Song Design and Language Learning
Editor-in-Chief
CALL FOR PAPERS OPEN
Inaugural issue planned for December 2026
The association journal of SSDLL and a scholarly publication platform for research, methods, evidence, evaluation, and practice-related scholarship.
Research & publishing company
ProoProo Co., Ltd.
Founder, Representative Director & Researcher
A research-driven education company supporting publishing, educational product development, and the responsible translation of research into practical learning contexts.
Visit ProoProo ↗Profiles & records
Citations and indexed scholarly output
0009-0002-1144-649X
Persistent researcher identifier
Publications, presentations, and academic activities
Research profile and international scholarly network
Versioned public research records for Scientific Song Design
Professional profile
Contact
Lingling Liu welcomes scholarly dialogue and carefully aligned collaboration related to Scientific Song Design, language learning, learning evidence, educational song design, and multilingual research.
Academic correspondencelingling.liu@scientificsongdesign.org