Dr. Kofi Nyarko
Director, CEAMLS; Professor of Electrical & Computer Engineering
Research in computer vision, machine learning and trustworthy AI. Holds four U.S. patents.
Our program
Morgan State is a historically Black research university in Baltimore. Our outreach team writes AI lessons, trains teachers and runs student workshops, with a focus on schools that have few devices. The lessons, stories and printables on this site come out of that classroom work.
How it grew
- 2023 First AI workshops at one Baltimore public library.
- 2024 Technology audits showed devices and internet were the main barrier, so we rebuilt the lessons to run from printed materials.
- 2025–26 Pilot across 12 schools and 2 libraries, funded by the Maryland Center for Computing Education, and the first AI Teacher Fellows cohort.
- Next Expanding to more Maryland schools, and studying which approaches work best.
Team
Zamalia Bennett
K–12 Outreach Program Manager
Leads curriculum design and teacher development. Twenty years with Baltimore City Public Schools as a teacher and interventionist.
Farhana Begum
K–12 Outreach Program Coordinator; Doctoral Researcher
Coordinates the program. Researches digital twins for connected-vehicle safety and AI reliability.
Jamal Williamson
Undergraduate Researcher, Electrical & Computer Engineering
Helps run student workshops and events, and builds demos.
Oludamisi Arowosegbe
Undergraduate Researcher, Electrical & Computer Engineering
Helps deliver hands-on AI activities and supports students at CEAMLS events.
Impact
Figures from the K–12 AI Curriculum Development Project, September 2025 – June 2026, reported to the Maryland Center for Computing Education.
| Figure | What it counts |
|---|---|
| 250 students | Students our team taught directly, in schools, libraries and summer camp. |
| 2,000+ students | Students reached through the teachers we trained. |
| 50 teachers | AI Teacher Fellows from 12 schools who took part in the 25-hour PD program. |
| 30 lessons | Classroom lessons designed by those Fellows. |
| 14 sites | 12 schools and 2 public libraries. |
| 38% → 85% | Student AI comprehension on our pre/post assessment, before and after the lessons. |
| 2.7 → 3.9 | Teacher confidence in teaching AI, out of 5, across the PD series. |
| 80% and 78% | Stakeholders who said the DEAR model could be adapted for future lessons (80%) and that culturally responsive design improved access (78%). |
| 4 of 4 | Student engagement during hands-on activities, on our classroom observation rubric. |
How we measured learning
The 38% to 85% result comes from a pre/post assessment of 175 students in grades 4 and 5 at Title I primary sites, reported in the project's final report to the Maryland Center for Computing Education (2026). The assessment, surveys and observation rubric are in our evaluation toolkit.
Partners
- Maryland Center for Computing Education (MCCE), which funded the 2025–26 pilot.
What people said
"I pulled a unit on a Monday and taught it by Thursday. My students had the most engaged discussion I have seen all year, about AI and about real-world consequences."
"I used to think AI was only for college students or engineers. The activities here showed me that I can train my own image classifier, it took about 20 minutes and I was completely hooked."
Contact
Email k12ceamls@morgan.edu. We answer within 5 school days.
To bring the program to your school or library, use the request form. Research papers are listed on our research page.
CEAMLS, Morgan State University, 1700 East Cold Spring Lane, Baltimore, MD 21251.