Daniel Current is an ESL educator, writing program administrator, and AI tools developer with more than 16 years of experience helping students from around the world find their voice in academic English.
He holds a Master of Arts in English with a concentration in Teaching English as a Second Language and a Bachelor of Arts in Anthropology with a minor in Religious Studies — a combination that shapes everything he does in the classroom. Understanding where a student comes from, culturally and linguistically, isn't background noise to Daniel. It's the whole point.
"My mission is to improve the human condition through education — by creating authentic interactions and shared experiences that bridge cultures, build skills, and open doors."
Over the course of his career, Daniel has taught thousands of students — from intensive ESL programs for new arrivals to university-level academic composition for international undergraduates enrolled at American institutions. His classroom has always been a place where culture is an asset, not an obstacle, and where communication is understood as something that happens between people, not just on a page.
As Writing Program Administrator for the Bowling Green State University–TianGong University partnership — a joint academic program operating across the US and China — Daniel spent six years navigating the real-world complexity of bilingual curriculum design, international faculty development, and cross-cultural accreditation. He's trained and observed instructors on two continents, and he knows firsthand what it takes to build a program that works for students and teachers alike, regardless of where they're standing when class begins.
Email: Daniel.current@gmail.com
In 2025, Daniel built Mr. Dan's AI Teaching Assistant — an LLM-powered feedback tool that delivers personalized, rubric-aligned writing feedback to students at scale. Built using prompt engineering and a Retrieval-Augmented Generation (RAG) architecture, Mr. Dan's AI TA is designed around a simple conviction: AI should extend a great teacher's reach, not replace their judgment.
Daniel holds certifications in Transformer-Based Natural Language Processing, NVIDIA Deep Learning, and several AI-in-education programs. His ongoing research and practice focus on how large language models can be built and guided to support genuine learning — and how students and educators can develop meaningful literacy around these tools in the process.
ESL / EFL Instruction, Academic Writing, Curriculum Design, Writing Program Administration, LLM Prompt Engineering, AI-Generated Feedback, RAG SystemsOnline & Blended Learning, International Faculty Training, Intercultural Communication, US–China Academic Partnerships, ACUE Certified
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