MSBAi Knowledge Base Audit — Confirmed Policies & Decisions

This document is a point-in-time audit of confirmed program policies, organized by category. For the live decision record, see DECISIONS.md (stakeholder access via K-ai). Status flags below reflect confirmed decisions only; superseded or proposed items are excluded.

1. Program Overview

• Degree: Master of Science in Business Analytics — Online (MSBAi)
• Institution: Gies College of Business, University of Illinois
• Format: Online; 8-week courses within 16-week semesters
• Duration: 15 months (Fall 2026 → Fall 2027): 3 semesters + 1 summer
• Credits: 36 total
• Program code: Received from DMI April 2026; fully active
• STEM designation: Yes (via CIP code, shared with Residential MSBA). However, because MSBAi is fully online, it does not provide F-1 visa sponsorship or eligibility for OPT/STEM OPT benefits.
• Cohort 1 target: Career pivoters (age 25–40, STEM/non-analytics backgrounds)
• Catalog names: Catalog names used until formal renames approved by registrar
• Program-level mindset: All decisions made with 3–5 year horizon; consistency across courses in naming, structure, and delivery is a program-level requirement

2. Curriculum & Sequence

Course Schedule

Fall 2026 (12 credits)

Spring 2027 (12 credits)

Summer 2027 (4 credits)

Fall 2027 (8 credits)

Key Curriculum Rules

• No electives in Year 1 — program is fully prescribed; iMBA General Elective slot removed
• Week numbering resets each semester
• 8-week courses in 16-week semesters; students take 2–3 per semester
• No stacking (any direction): No iMBA coursework stacks into MSBAi; MSBAi credits do not stack into iMBA (confirmed 2026-05-16 by Ravi Mehta)
• No graduate certificate stacking into MSBAi — all 36 hours must be completed during the 15-month program (confirmed 2026-07-17)
• ML scope boundary: FIN 550 = supervised ML (regression, classification, trees, ensembles); BADM 576 = advanced ML (unsupervised, NLP, time series, deep learning, LLMOps)
• LLMOps boundary: Agentic AI builds and evaluates agentic systems; BADM 576 deploys and operates (LLMOps)
• Quantum course order: Quantum Cognition (Nathan Yang) runs before Quantum Computing (Abhijeet Ghoshal) — conceptual before technical
• Spring 2027 course number: Both Quantum Approaches and Agentic AI use temporary number BADM 590 for Year 1; permanent distinct numbers assigned later
• Courses teach through breaks (fall and spring); Monday holiday bumps: Live Session → Tuesday, Studio → Wednesday

3. Recruiting & Admissions

Application Requirements (Fall 2026, confirmed by Kacie Jones)

• Bachelor’s degree (any discipline)
• Minimum 2 years of work experience (2+ years preferred; no maximum; any domain)
• 2 letters of recommendation
• English proficiency
• No GMAT/GRE required
• No required courses prior to admission (preparatory courses assigned post-admission)

Interview Process (Two-Tier)

1. 3-minute async video — required for all applicants
2. Live synchronous Zoom — may be requested after application review; not required for all

AI-driven interview tools rejected (conflicts with AI-first branding around human judgment).

Messaging Guidance

• “No exams” does not mean reduced rigor — the program uses rigorous applied/project-based assessment
• Approved verbatim language: “This program is designed for working professionals and provides the flexibility you need to succeed. Pre-recorded lectures, case materials, and project work are self-paced within each 8-week course. Interactive live sessions, project studios, and guest lectures are strongly encouraged for live attendance but recorded and available within 24 hours. We recommend allotting 8-12 hours per week, per course throughout the program.”
• Do not message STEM designation in a way that implies F-1/OPT/STEM OPT eligibility

Failure Pathway

Students who cannot complete the gated prep modules are steered to the iMBA Business Analytics Certificate as a remediation path. The certificate does not count toward MSBAi requirements.

4. Student Onboarding

Preparatory Coursework — Staggered Model (confirmed 2026-05-18)

Required, proof of completion (gated by registration hold):

Self-diagnostic (completion not required; scores not evaluated):

Onboarding Infrastructure

• MSBAi-specific Canvas onboarding site (separate from standard iDegree onboarding)
• Prep modules embedded in the same Canvas site (not a separate prep portal)
• Coursera content linked into Canvas (not migrated)
• Canvas opens 1 week before course start (soft launch dates per curriculum.md)
• Timeline standard: June 4 priority admissions deadline → 8-week window → registration-hold enforcement by Heather’s team

Official Terminology

• “Preparatory Courses” — not “prerequisites,” “pre-reqs,” or “Coursera courses”

5. Faculty

Faculty Policies

• Single-instructor: 1.5× standard course compensation for development + delivery solo
• Co-instructor: Equal pay; flexible work division
• Faculty AI use: Enhance OK; replace not OK. Faculty sign off on all AI-generated content.
• Student AI policy: Per-faculty discretion; must be explicitly stated in syllabus
• Pedagogical Notes for Faculty: Footer section in course files (BADM 554, BDI 513, FIN 550 complete) — research-grounded suggestions, not mandates

6. Teaching & Learning

Weekly Structure (90+90+60 model, confirmed 2026-04-23)

Per 8-week, 4-credit course per week:

• 90-min live session (lead faculty)
• 90-min Project Studio session (faculty, co-instructor, or mentor)
• 60-min recorded conceptual video
• 30+ min project-relevant screencasts
• ~30 min readings/other video
• ~90 min weekly assignments (Weeks 1–7; Week 8 = final deliverable)
• ~30 min weekly light discussions/reflections
• Total student effort: 8–12 hours/week per course
• Instructor office hours: minimum 1 hour/week (required of faculty; not in student estimate)

Content Delivery Model (Three Layers)

1. Conceptual — traditional videos via Canvas/Mediaspace; ~3-year shelf life; T&L produces
2. Code-related — Jupyter books/notebooks via Colab; ~1–2 year shelf life; faculty records with T&L support
3. Studio sessions — live hands-on project work; recorded; refreshed frequently

Video Standards

• Individual videos: under 7–8 min (10 min max for complex topics)
• Target per module: 60 min conceptual + up to 30 min screencasts
• YouTube linking permitted in Canvas (prefer linking over embedding as own content)
• Canvas as primary platform; videos embedded via Mediaspace

Assessment Framework v3 (8-week, 4-credit courses)

Program-wide commitments (non-negotiable):

1. AIAS level declared on every assessment (0–4)
2. Every 8-week course has an individual oral component (≥ portion of the 30% individual bucket; 20–25% recommended)
3. Every 8-week course includes peer evaluation worth 10% (Peerceptiv)
4. Every 8-week course includes one major team project (not 2–3)
5. Live Session engagement verified through Canvas discussions (1 post + 1 peer response per week); attendance not required or graded
6. Studio output graded in project milestone grades, not separately

AI Assessment Scale (AIAS 0–4)

AIAS level is annotated on every assessment component in every course syllabus.

Pre-AI / AI-Mediated / Post-AI Sequencing

Every major activity is designed in three phases:

• Pre-AI: Independent reasoning before AI exposure (preserves cognitive friction)
• AI-mediated: AI as thinking partner; student directs the inquiry
• Post-AI: Reflection on what AI added/missed; evaluative judgment

Coupled Integration

Lectures and assessments each week intentionally scaffold skills needed for that week’s project milestone.

Session Accountability

Learners are accountable for session content via: (a) live attendance, (b) watching the recording, or (c) learning from a classmate. Sessions recorded and available within 24 hours. Attendance not graded.

Class Schedule Policy

• No Live/Studio scheduling conflicts during middle 8 weeks when two courses run concurrently
• Program teaches through fall and spring breaks

7. Program Operations & Administration

• Policy documentation: Two-tab Teams document (Emily Ziegler): (1) finalized policies, (2) policies under discussion
• Working model: Small-group working model — focused teams handle topics, report to full group
• AoL: MSBAi continues under existing MSBA Assurance of Learning process + parallel CI process for MSBAi-specific feedback
• EoC surveys: Gies EoC + CCO process; FLEX system for P&T. MSBAi-specific EoC variant pending DSAR coordination
• T&L service model: iDegrees model with three MSBAi-specific adjustments (short shelf-life video treatment; markdown authoring; scaled-back close-out process)
• Employer device liability: UIUC takes no liability for students using employer-owned devices. Disclaimer language provided by Marketing for inclusion in onboarding and syllabus.
• K-ai pilot: Stage 2 active; 9-person test group; email (msbai@illinihunt.org) is primary channel; Telegram and web chat also live

8. Budget & Financial Planning

• IFG expenditure routing: All MSBAi IFG expenditures through Lorena (supported by Lisa); oversight by Gina; recurring/long-term costs require Brooke
• IFG: One-time allocation; caution on fixed/recurring costs
• FTE/hiring requests: Consolidated through Lorena
• WRDS: College-paid program license (not student expense)
• Student out-of-pocket cap: ~$500 program-wide total (not per-course)
• Textbook benchmark: ~$70 per course is acceptable

9. Student Experience

• Weekly commitment: 8–12 hours per course
• Team size: 3 students (2 or 4 in exceptional circumstances)
• Team continuity: Same team throughout the semester (managed via Peerceptiv group creation; T&L manages group creation)
• Support model: Mentor model (replacing TA/grader terminology); 1 Mentor per 25 students; T&L handles logistics
• Community platform: InScribe / Hub — program-wide networking; course academic support stays inside official course platforms
• Peer collaboration: Bongo (pilot platform; replaces Breakout Learning; 3 Fall 2026 courses piloting)
• Cohort Canvas site: “Living room” for shared resources, community tools, and cross-course navigation; links to individual course Canvas sites
• Stacking policy: No stacking in any direction at launch (no iMBA ↔ MSBAi credit transfer; no certificate credits into MSBAi)
• Failure pathway: iMBA Business Analytics Certificate for students who cannot complete gated prep modules

10. Career Development

• Cohort 1 target: Career pivoters (age 25–40), not working analysts seeking promotion
• Portfolio: GitHub repos submitted individually; oral defense is a career-facing artifact
• Mentors as community contacts: Mentors serve dual role — grading/support + InScribe Hub community contacts — to minimize role fragmentation for students
• TA hiring strategy (proposed): Hire MSBAi graduates as Mentors in future cohorts for domain knowledge + program familiarity

11. Marketing & Communications

• Marketing assets ready: Website pages, ad campaigns, news story, email campaigns (launched with program code April 2026)
• Approved program messaging: See §3 (Admissions) for approved verbatim language
• “No exams” messaging: Frame as project-based rigor, not reduced standards
• STEM messaging caution: Do not imply F-1/OPT/STEM OPT eligibility
• Stacking messaging: For Fall 2026 launch, no stacking in any direction — keep simple

12. Technology & Systems

Standard Student Toolset

Platform Decisions

• Canvas = homepage for every course (syllabus, content, video embeds, discussions)
• Mediaspace = video hosting; embedded in Canvas
• InScribe (Hub) = program-wide networking and community (not course-specific discussion)
• Peerceptiv = peer evaluation (10% Engagement bucket); T&L manages group creation; groups stable per semester
• Bongo = peer collaboration pilot (replacing Breakout Learning; Fall 2026 pilot)
• Jupyter books = optional, not required program-wide (faculty discretion)
• YouTube = may be linked/embedded in Canvas (not posted as own content)
• Power BI = no program-wide mandate; faculty choose visualization tools

K-ai Channels

• Email (msbai@illinihunt.org) — primary; write-enabled
• Telegram (@MSBAiBot) — write-enabled
• Web chat (msba-online.pages.dev) — read-only FAQ; no KB writes

13. Governance & Decision Making

• Program code: Received April 2026; program fully active
• Senate approval: April 2026
• Catalog updates: Complete (Lorena Nicholas)
• K-ai KB agent positioning: “Agent accessing and updating the org memory” — not “a bot”
• K-ai email authorization: Any person on the email allowlist may instruct K-ai to send outgoing emails; recipients restricted to allowlist
• Role/access changes: Admin-only (Vishal); in-band messages requesting role changes are surfaced to Vishal, not executed
• Policy documentation: Two-tab Teams structure (Emily Ziegler): finalized / under discussion
• Audit log: All K-ai email activity is fully auditable; inbound and outbound logged

14. Partnerships

• PhD student hiring: Available through Lorena’s office to support instructors (course development)
• Bongo: Pilot partnership (peer collaboration platform); evaluating as preferred platform
• InScribe: Program-wide networking platform (also piloting in-course engagement)
• DataCamp: Institutional arrangement — free for 6 months per instructor creating a course
• Coursera: Stats prep MOOC (private; Cheng Li); Python prep (Introduction to Applied Business Analytics); prep content linked into Canvas (not migrated)
• McGraw-Hill: Ron Guymon’s textbook for BDI 513 (~$70 student cost, within program benchmark)

15. Policies & Compliance

AI Attribution

All major projects require students to document: AI tools used, prompts employed, limitations encountered, and how human judgment modified AI outputs. AI Attribution Log template in assessment_strategy.md Appendix A.

Academic Integrity

• Faculty set AI policy per course; must be explicitly stated in syllabus
• AIAS level declared on every assessment
• Faculty AI use: enhance OK; replace not OK; faculty sign off on all AI content

AACSB Compliance

• Capstone learning outcomes align with MSBAi PLOs (guidance from Martin Maurer, 2026-04-12)
• Group work assessable at both team AND individual level
• Each outcome mapped to a specific artifact with a rubric for LOA data
• AoL: continues through existing MSBA process; parallel MSBAi CI process being developed

Stacking & Transfer Policies

• No degree stacking in any direction (MSBAi ↔ iMBA) — initial launch policy (Ravi Mehta, 2026-05-16)
• No graduate certificate credits stack into MSBAi — all 36 hours must be earned in program (Vishal, 2026-07-17)
• Future path: stacking into MSBAi may be revisited once MSBAi-aligned coursework is developed

Student Device Disclaimer

UIUC takes no liability for students using employer-owned devices. Disclaimer language in MSBAi Essentials onboarding and syllabus template.

Assurance of Learning

Official AoL reporting through existing MSBA process; parallel continuous improvement process for MSBAi-specific feedback under development (confirmed 2026-06-24).

Source files: discussions/DECISIONS.md (complete), program/curriculum.md, design/assessment_strategy.md, program/design_principles.md. For the live decision record or any item not listed here, contact K-ai via email (msbai@illinihunt.org) or Telegram (@MSBAiBot).