Prebuilt quiz banks of 435 questions across 65 modules decouple practice from live generation, with warm practice-request medians of 4.8 and 5.8 ms¶

Claim · All claims
Evidence · 1 study (2 entries) · design r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The deployed banks total 435 prepared items covering 65 configured modules, and practice uses stored keys and feedback without live generation. → Sidney Shapiro and Joshua Lindemann 2026 q2 i? A 166-request live API audit found warm medians of 4.8 ms on Node A and 5.8 ms on Node B for stored quiz operations. → Sidney Shapiro and Joshua Lindemann 2026 (2)

Evidence¶

Sidney Shapiro and Joshua Lindemann 2026¶

Sidney Shapiro and Joshua Lindemann. (2026). On-Premises Multi-Course RAG Tutoring for Business Education: Hardware–Software Trade-offs in a Campus AI Tutor. arXiv. https://arxiv.org/abs/2610.02510 doi:10.48550/arxiv.2610.02510

q2 · i? · design · r2

System description of quiz mode across Courses 1–6: "The 435 prepared items cover 65 configured modules", with deterministic grading against the bank and answer keys kept server-side until an attempt or reveal.

"The 435 prepared items cover 65 configured modules, and practice uses stored keys and feedback without live generation."

Sidney Shapiro and Joshua Lindemann 2026 (2)¶

Sidney Shapiro and Joshua Lindemann. (2026). On-Premises Multi-Course RAG Tutoring for Business Education: Hardware–Software Trade-offs in a Campus AI Tutor. arXiv. https://arxiv.org/abs/2610.02510

q2 · i? · design · r2

A separate 166-request live API audit covering all 65 module starts on each node plus warm repeats, hints, and graded answers; the section reports "Warm medians were 4.8 ms on Node A and 5.8 ms on Node B".

"Warm medians were 4.8 ms on Node A and 5.8 ms on Node B, measured server-local."

Discussion¶

Related Claims¶

• The AI feedback system returns responses in under a second for MCQs and about six seconds for open-ended questions, and its reusable prompt is roughly 2.77 times more time-efficient to prepare than equivalent educator text — related
• LLM-generated retrieval practice was practical to deploy and well received, but high correctness rates (about 70% of items at p=1.0) restricted score variance — related
• On the live single-node deployment, short-answer rounds take ≈32 s (≈$0.015/round) while multiple-choice rounds are ≈4× faster (≈7.6 s, ≈$0.005/round) because grading is deterministic — related