PEDAL

PEDAL is a research-grounded AI pedagogical engine for multilingual language education that addresses a critical gap in educational technology. While generative AI can rapidly produce language learning content, it rarely applies validated principles of second language acquisition or delivers pedagogically reliable instructional support. PEDAL overcomes this by embedding task-based language teaching, CEFR-aligned progression, and evidence-based learning principles directly into its AI orchestration framework.

In 2025, PEDAL achieved proof of concept through the development of a minimum viable product capable of generating CEFR-aligned reading and listening activities. Internal evaluation with language educators at UCD demonstrated that the generated content was coherent, usable, and pedagogically sound, providing early validation of both the underlying technology and its educational value.

The next phase will focus on transforming the MVP into a market-ready platform by strengthening the AI orchestration layer, improving backend infrastructure for secure institutional deployment, refining teacher-facing workflows, and generating evidence of user demand and procurement readiness through engagement with higher education stakeholders.

By the end of the project, PEDAL will have a robust, institution-ready platform supported by evidence of technical feasibility, educational effectiveness, commercial viability, and procurement potential. This will establish the foundation for pilot deployments and position the technology for commercialisation within the rapidly growing AI-enabled education market