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Documentation Index

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Nebula gives universities and academic programs a way to move professional readiness training beyond the classroom. Rather than asking students to imagine how they would handle a workplace situation, Nebula puts them inside one — with real AI-powered coworkers, competing priorities, and decisions that have consequences. Students develop and demonstrate professional skills through repeated practice across a semester, and their growth is tracked longitudinally using the same scoring and skill framework that employers use for candidate assessment.

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Why universities use Nebula

Experiential learning at scale

Run corporate simulations across an entire cohort without logistical overhead. Every student gets a personalized, AI-adaptive session inside a consistent company world.

Career readiness evidence

Generate measurable, evidence-backed performance data that goes beyond grades — showing how students handle workplace pressure, stakeholders, and decisions in context.

Interview and internship preparation

Students practice the exact skills assessed in professional interviews: structured decision-making, communication under pressure, and stakeholder navigation.

Longitudinal skill tracking

Skills and XP persist across every session. Instructors can track how individual students or cohorts develop over an entire semester or academic year.

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The four supported domains

Nebula’s simulations are organized into four professional domains, each aligned to common business and management programs. All twelve companies in Nebula’s corporate world support activity across these domains.

Product Management

Students take on product roles — managing roadmaps, navigating stakeholder trade-offs, and making prioritization decisions inside technology and innovation companies.

Marketing

Students work in brand, growth, and marketing operations roles — handling campaigns, messaging decisions, and cross-functional pressures inside consumer and B2B companies.

Data Analysis

Students operate as analysts and data strategists — interpreting information, presenting findings to stakeholders, and advising business decisions under uncertainty.

Consulting

Students work in consulting and advisory roles — managing client relationships, building recommendations under time pressure, and navigating engagement complexity.

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Student journey in a university program

1

Students join via the university program

Students access Nebula through your institution’s program link or access configuration. Each student creates their individual account, which will track their progress throughout the program.
2

Complete platform onboarding

During their first session, the AI onboarding coordinator assesses each student’s background and experience. Students entering as beginners are identified and calibrated to a beginner or intermediate difficulty level — ensuring the simulation is challenging but not discouraging.
3

Choose a company and domain aligned to their major

Students select from Nebula’s twelve fictional companies and choose a domain that matches their coursework. A marketing student might choose Silverline Media in the Marketing domain; a data student might choose Prism Analytics in the Data Analysis domain.
4

Complete simulations across the semester

Students run sessions at whatever cadence fits your program structure — weekly, bi-weekly, or tied to specific course modules. Each session generates a fresh scenario inside the same persistent company world, so the environment is familiar but the challenge evolves.
5

Track skill progression over time

Skills, XP, and performance data accumulate across every session. Students can see their own development over time, and instructors can access session analytics to monitor cohort progress or identify students who need support.

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Key features for academic use

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Adaptive difficulty calibrated to student level

The AI onboarding coordinator infers each student’s experience level during their first session and recommends a starting difficulty. Most students begin at beginner or intermediate. As skills grow and XP accumulates, students advance naturally through intermediate, advanced, and eventually expert difficulty — with each level introducing more complex scenarios, faster-moving dynamics, and higher-stakes decision checkpoints.

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Persistent skill tracking across sessions

Every skill score and XP gain is stored against each student’s account and accumulates across all sessions throughout the semester. This longitudinal record is what makes Nebula useful for measuring growth — a single session shows a snapshot, but a semester’s worth of sessions shows a trajectory. The six skill categories tracked in every session are: Communication, Decision Making, Stakeholder Management, Technical Acumen, Leadership, and Time Management.

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Evidence-based session reports

At the end of every session, Nebula generates a structured session report containing:
  • An overall score from 0–100
  • Skill scores per category reflecting session performance
  • Decision patterns capturing how the student approached key choices
  • Strengths and improvement areas drawn from the session record
  • Evidence highlights — specific moments cited as the basis for scores
  • A readiness signal narrative summarizing the student’s professional maturity
These reports can be used as assessment artifacts, portfolio pieces, or the basis for instructor feedback conversations.

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Session analytics access

Instructors and program administrators can access student performance data through the session analytics interface. This includes individual session reports as well as aggregate skill data across your cohort, making it possible to identify both high performers and students who may benefit from additional support.
Align company and domain selection to your course curriculum. If your program covers product strategy in one module and data-driven decision-making in the next, assign students to companies in the Product Management domain first, then switch to Data Analysis. Nebula’s twelve companies span all four domains, giving you flexibility to match simulation context to what students are studying at any given point in the semester.
Students at beginner level face scenarios calibrated to their experience — the complexity of the case study, the demands of AI personas, and the pace of disruption events are all adjusted to be appropriate for someone early in their professional development. This ensures the simulation is challenging without being overwhelming, and that skill scores reflect realistic growth rather than repeated failure.

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Responsible use and data governance

Using Nebula in an academic program involves student data. The following guidance covers your institution’s obligations.

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FERPA compliance (US institutions)

Student session data in Nebula — including performance scores, decision logs, and session reports — may constitute education records under FERPA (Family Educational Rights and Privacy Act) if linked to an identifiable student and maintained by your institution. Institutions using Nebula in graded or formally evaluated academic programs should:
  • Ensure students are informed that their session performance may be reviewed by instructors or program administrators
  • Treat session reports shared with instructors as education records subject to FERPA access and disclosure rules
  • Not share individually identifiable student session data with third parties (including employers) without student consent, unless a FERPA exception applies
  • Consult your institution’s legal or compliance team before using session data for formal academic evaluation
If you intend to share a student’s Nebula session report with employers, recruiters, or external parties as part of a career placement or capstone program, obtain the student’s written consent first.
Students should be informed at program enrollment that:
  • Their Nebula sessions are recorded and scored
  • Session reports are accessible to the instructor or program administrator
  • Performance data persists across sessions and may be used for academic assessment or program evaluation
Present Nebula as a formal assessment tool, not a casual learning exercise, when it is used in a graded or evaluated context.

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Grades and academic decisions

Nebula session scores are performance indicators derived from AI evaluation, not traditional academic grades. If your program incorporates Nebula scores into formal academic records:
  • Define in your syllabus exactly how Nebula performance will contribute to a grade
  • Ensure a qualified instructor or evaluator reviews session data before any grade is assigned
  • Do not assign a grade based solely on a Nebula composite score without instructor review
No automated Nebula score should serve as the sole basis for a consequential academic decision (course failure, academic probation, program dismissal, etc.).

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Data minimization and retention

Collect only the student data necessary for your program’s stated purpose. Avoid storing student session exports beyond the academic term unless required for accreditation, program review, or longitudinal research (with appropriate IRB or ethics approval where required).

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Accessibility

Ensure that all students in your program can meaningfully participate in Nebula simulations. If a student requires accommodations (extended time, assistive technology, or modified interaction modes), contact the Nebula support team to discuss available options before the program begins.
Session reports contain detailed behavioral and performance data about individual students. Handle this data with the same care you apply to any other student academic record.