Course Learning Outcomes Platform (CLOAP)
CAA Accreditation · Learning Outcomes · R Shiny · UAE Higher Education
Case Study # Course Learning Outcomes Platform (CLOAP)
CAA Accreditation · Learning Outcomes · R Shiny · UAE HE
✓ Live Deployment ✓ CAA-Aligned ✓ Evidence Upload ✓ Accreditation Reports
Platform at a Glance
3 Mapping Levels (CLO → PLO → ILO)
4 User Roles
Auto CAA-Format Report Generation
100% Evidence Audit Trail
1. Problem Statement
UAE higher education institutions are required by the Commission for Academic Accreditation (CAA) to demonstrate that programme and course learning outcomes are defined, measurable, and evidenced through student assessment. Prior to CLOAP, institutions managed this obligation through a fragmented combination of:
- Separate Word documents for each course’s CLO specification (no central repository)
- Excel workbooks for assessment-to-CLO mapping (inconsistent formats across departments)
- Manual aggregation to programme-level outcome (PLO) attainment data each semester
- No structured evidence repository — documents scattered across departmental drives
- Accreditation report assembly taking 4–6 weeks per review cycle
The institution needed a single, structured platform to manage the entire CLO lifecycle: definition, assessment mapping, attainment data entry, evidence collection, and accreditation-format reporting.
2. Solution Architecture
CLOAP is a hierarchical R Shiny platform managing three levels of learning outcome: Course Learning Outcomes (CLOs), Programme Learning Outcomes (PLOs), and Institutional Learning Outcomes (ILOs) — with automated roll-up from course to programme to institution level.
2.1 Technology Stack
| Component | Technology | Purpose |
|---|---|---|
| Application | R Shiny + bslib | Modular outcome management interface |
| Database | SQLite (12 tables) | CLOs, PLOs, ILOs, mappings, evidence |
| Evidence Storage | File system + metadata DB | PDF/image evidence with structured metadata |
| Visualisation | ggplot2 + plotly | Attainment charts, mapping matrices |
| Reporting | R Markdown + LaTeX | CAA-format course and programme reports |
| Access Control | RBAC (4 tiers) | Role-appropriate data entry and approval |
| Hosting | shinyapps.io | Production deployment |
2.2 Learning Outcome Hierarchy
Institutional Learning Outcomes (ILOs)
▲
│ auto-aggregated
│
Programme Learning Outcomes (PLOs)
▲
│ mapped many-to-many
│
Course Learning Outcomes (CLOs)
▲
│ assessed through
│
Assessment Tasks (Exams, Assignments, Projects)Every assessment task is mapped to one or more CLOs. CLO attainment is calculated from student grade distributions against the mapped assessment components. PLO attainment aggregates automatically from contributing CLOs.
2.3 Key Modules
🗂️ Outcome Definition Module
Structured authoring of CLOs, PLOs, and ILOs with Bloom’s Taxonomy classification, active-verb validation, and mapping matrix generation. CLO changes trigger re-mapping alerts to affected assessments.
📊 Assessment Mapping Module
Many-to-many mapping of assessment components to CLOs with weighting. Automatic Bloom’s level alignment checking — warns if assessment cognitive level does not match CLO expectation.
📈 Attainment Dashboard
Real-time CLO and PLO attainment visualisation from grade data entry. Threshold alerts (typically 70% of students achieving ≥60% on each CLO), drill-down to individual student performance.
📎 Evidence Repository
Structured upload of accreditation evidence: sample marked assessments, rubrics, grade distribution sheets, and peer review records — all linked to specific CLOs, assessment tasks, and academic terms.
3. CAA-Format Report Generation
The platform generates CAA-compliant course file reports automatically at semester end:
- CLO specification table (with Bloom’s classification and weighting)
- Assessment mapping matrix (CLO × Assessment cross-table)
- Attainment summary table (mean score, threshold attainment %, trend vs. prior term)
- Evidence checklist with upload status
- Continuous Improvement Plan (CIP) template pre-populated with underperforming CLOs
Reports are generated as LaTeX → PDF in CAA-specified layout. A programme-level summary aggregates across all courses for PLO attainment reporting.
4. Outcomes
✅ Accreditation Outcomes
- CAA course file preparation time reduced from 4–6 weeks to 2–3 days per review cycle
- First structured CLO-to-PLO-to-ILO attainment mapping in institution’s history
- Evidence repository providing an auditable, timestamped document chain for all accreditation claims
- Automated generation of Continuous Improvement Plans for underperforming CLOs
📋 Operational Outcomes
- Single repository for all course CLO data (eliminated 400+ separate Word/Excel files)
- Real-time attainment dashboards replacing semester-end manual spreadsheet compilation
- Faculty self-service data entry replacing coordinator-managed data collection
- Programme-level PLO reports generated automatically from course-level data
5. Lessons Learned
Bloom’s Taxonomy classification requires institutional policy alignment first. Different faculty understand Bloom’s levels differently. Before building the classification module, BRASS ran a 2-hour workshop to establish the institution’s standard Bloom’s verb list. This prevented inconsistent classification across departments.
The attainment threshold (70/60 rule) varies by institution and accreditor. CAA has specific thresholds; institutional policy may differ. The platform makes attainment thresholds configurable parameters in the admin module — not hardcoded values.
Evidence linking must be mandatory, not optional. Early prototype allowed evidence upload without linking to a specific CLO/assessment. Auditors require structured linking. The schema was revised to enforce mandatory evidence linkage before submission is permitted.