Where 50 Years of Teaching Meets the Future of Education
Weevil Labs builds AI-powered tools for educators, by educators. We are researchers, curriculum designers, and developers solving real problems in higher education.
Built by professors who code
Weevil Labs is an educational technology company founded by two career university professors with a combined 50+ years of classroom experience. We are not Silicon Valley outsiders guessing what teachers need. We are teachers who build what we wish existed.
Our expertise spans AI-augmented writing assessment, curriculum design, TESOL methodology, and full-stack software development. We publish peer-reviewed research on the tools we build, and we build tools based on the research we publish.
We teach. We code. We ship.
What we do
AI-Augmented Writing Assessment
We design and build AI systems that evaluate student writing with the nuance of an experienced instructor. Our error taxonomy, grounded in Corder (1967), Richards (1971), and James (1998), powers granular feedback that goes far beyond rubric checkboxes.
Curriculum & Instructional Design
Assessment-backward course design for flipped classrooms. Every material we create is engineered so students can succeed on their first submission. We design for learning outcomes, not seat time.
Educational Technology Development
Full-stack product development from concept to deployment. Python, JavaScript, React, Next.js, Vercel, Claude API. We build production tools, not prototypes.
TESOL & Applied Linguistics
Specialized in English as a Foreign Language contexts across East and Central Asia. We understand L1 interference patterns for Korean, Vietnamese, Chinese, and Uzbek learners at a granular level.
The team
Associate Professor, Dong-A University, Busan, South Korea (2011-present, promoted 2019)
Instructor, Webster University Tashkent (8 TESOL MA courses online)
MA English, BA English (University of Illinois Springfield)
2x Teacher of the Year. Associate Editor, JKALS (2024-present)
Focus: AI-assisted writing assessment, flipped classroom methodology, automated lecture production. 20+ years in higher education.
Associate Professor, Dong-A University, Busan, South Korea
Focus: AI-based error analysis, EFL writing instruction, computational linguistics
Co-author on all Weevil Labs research publications. Lead researcher on the AI error taxonomy project that powers Mark-O-Matic's grading engine.
Our research
We publish what we build. We build what we publish.
"A Taxonomy of Errors in English as she is spoke: Toward an AI-Based Method of Error Analysis for EFL Writing Instruction"
Development of an AI-assisted error analysis system using LLMs (Claude 3.5 Sonnet, DeepSeek R1) with a detailed taxonomy grounded in Corder, Richards, and James. Implemented through Python-coded API calls for granular feedback beyond traditional rubric-based assessments.
Read on arXiv open_in_newPublication details coming soon
Publication details coming soon
Publication details coming soon
What we're building
Mark-O-Matic
AI-Powered Grading for University Teachers
40 essays graded in 10 minutes, not 16 hours. Upload papers, apply your rubric, get back graded essays with inline Word comments, rubric scores, and actionable feedback students will actually use.
Reeducation
Rapid Workforce Retraining at Scale
A platform targeting the 4.8M global cybersecurity role gap. Market to employers, charge placement fees. Curriculum designed by career educators, delivered through AI-augmented instruction.
Let's talk
Whether you are an institution looking for AI-powered assessment tools, a publisher interested in our research, or an investor who sees what we see: the future of education is built by the people who teach.