Benjamin Hall is the lead researcher and developer behind the AI-Assisted Comprehension Assessor (AACA), an educational AI platform focused on evaluating student comprehension while upholding academic integrity in the era of large language models. His research advances the field beyond traditional plagiarism detection toward learning verification—assessing whether students genuinely understand course material, regardless of whether AI tools were used during drafting. AACA analyzes student essays and dynamically generates aligned assessments, including Canvas-compatible quizzes, that probe conceptual understanding, reasoning, and content mastery.

Benjamin Hall’s work integrates natural language processing, prompt engineering, and assessment theory to transform unstructured student writing into structured, standards-aligned evaluation artifacts. His research includes automated processing pipelines (PDF/DOCX to clean text to AI analysis to QTI/XML output), controlled question generation with deterministic scoring logic, and safeguards to reduce hallucinations and bias in AI-generated assessments. The work is grounded in real instructional environments and supports scalable instructor workflows while emphasizing fairness, transparency, and pedagogical value. Development and evaluation of AACA are conducted in collaboration with academic partners affiliated with Morgan State University, with broader implications for ethical AI adoption in education, formative assessment design, and AI-augmented teaching practices.