Universidades
A connected campus for learning, teaching and supporting student journeys.
Executive summary
A student journey starts before the first class: programme discovery, application, documentation, payment, digital identity and orientation. Admissions, academic records, learning and support services need shared, defined states without spreadsheet duplication.
Relevant signals can trigger human support for connectivity, tutoring, financial aid or scheduling. An alert must never become a judgement about a student. Faculty and wellbeing teams need separate permissions and traceable interventions with routes for data correction.
Adoption proceeds by faculty, cohort and process. Identity and a test admissions flow precede course, assessment and support connectors. Baselines cover enrolment time, request handling, engagement and retention. The university retains control of curriculum, assessment policy and data.
The challenge
Large institutions have many programmes, cohorts and calendars. Enrolment, LMS and wellbeing may disagree about a student state. The challenge includes inconsistent course codes, changing curricula and special assistant roles. Discovery measures rework, delayed course access, duplicate identities and accessibility barriers.
Architecture
Federated identity connects applicant, student and alumni states. Academic systems remain authoritative for grades and requirements. Versioned APIs and events build a unified view with provenance. Queues absorb enrolment peaks; idempotency prevents double payment or registration.
- A headless LMS compatible with SCORM and xAPI, built on Node.js microservices with NestJS.
- Federated authentication with SAML 2.0, Shibboleth and OAuth2.
- An admissions portal with real-time validation and online payments.
- Hybrid classrooms with WebRTC and LiveKit, automatic recording and transcoding.
- A dropout-prediction model built with scikit-learn.
- Integration through REST APIs, webhooks and Kafka, on AWS EKS, RDS Aurora, S3 and CloudFront.
- WCAG 2.2 AA certified accessibility, with a Lighthouse score above 95 and TTFB under 200ms.
Six modules
Six modules cover admissions; enrolment; an accessible virtual campus; assessments and rubrics; human-led student support; and institutional cohort analytics. Shared identity, catalogues and audit support phased adoption by faculty.
Engineering decisions
Each data domain has an authoritative source. Events propagate changes; synchronous calls serve decisions needing an immediate answer. Predictive scores may prioritise human review, never automatically block enrolment or decide scholarships. Curriculum rules are versioned and reviewed by academic owners.
Security
Applicants, students, faculty, assistants, coordinators and wellbeing staff have separate rights. Grades, counselling notes and financial details have different access controls. Encryption, audit, backup restore and retention must be tested. Risk indicators require privacy and fairness review.
Performance
Admissions, grades and enrolment create peaks. Representative load tests include mobile connections. Static programme content can be cached; seats, grades and payments require fresh authoritative data. Authentication, application confirmation and assignment submission are tracked with human accessibility tests.
Observability
Sentry collects application errors without student details. Grafana tracks latency, delayed events, SSO health and LMS sync. Correlation identifiers trace applications and registrations. Alerts distinguish a delayed video from a widespread course-access failure.
Results and measurement
The comparison describes capabilities, not verified dropout results. A pilot tracks time from acceptance to course access, manual rework, tutoring uptake, semester continuity and enrolment accessibility. Comparable cohorts and external factors must be disclosed for retention analysis.
| Before | After | |
|---|---|---|
| Admissions and LMS | Separate systems, no shared data | Integrated through APIs and events |
| Dropout risk | Reactive detection | Predictive, with early alerts |
| Site performance | Variable | Targets measured during the pilot |
Use cases
Admissions tracks documents and status; academic records enforce prerequisites; faculty publishes once to the right class; low-bandwidth students access materials; tutors assess support alerts; the library links licensed resources; postgraduate seminars track milestones; continuing education validates certificates.
Roadmap Q1 / Q2 / Q3 2026
Q1 2026: inventory systems, identity and admissions flows. Q2: pilot admissions, registration and virtual courses with accessibility and security checks. Q3: add support analytics and expand once data quality is proven. Dates are illustrative until agreed with an institution.
Frequently asked questions
Must the current LMS be replaced?
No. It may be connected where APIs and contracts allow.
Who sets grading rules?
Academic units retain authority over assessment, attendance and programme requirements.
Does the dropout model make decisions?
No. It prioritises human review and requires explanation and correction routes.
How are tutoring notes protected?
Support records have separate roles and retention from grades and general analytics.
Can multiple campuses be supported?
Yes. Campus, calendars and offers vary while student identity remains unified.
What about historical data?
Map it by cohort and validate a sample before migrating ambiguous records.
How is accessibility tested?
Automated checks are combined with tasks performed by assistive-technology users.
Where does the project start?
Bring admissions, records, teaching, IT and students together to define a focused pilot.
Let’s talk
Let us map the application, enrolment and learning journey, select a pilot faculty and agree on measurable indicators while preserving academic control.