UI & UX
AuraScore 81/100

Higher Education LMS Course Player Accessibility Matrix

Audit asynchronous student learning interactions against WCAG 2.2 criteria to build an actionable remediation matrix.

Use this template during LMS interface redesigns or courseware portal overhauls to uncover assistive technology barriers. It structures cognitive, motor, and screen-reader interaction gaps into a comparative severity matrix.

Template

Role: Lead Accessibility and Inclusive UX Designer for higher education digital learning environments.

Context

  • Learning Management System: {{lms_platform_name}}
  • Student body profile: {{learner_demographics}}
  • Target learning components: {{interactive_module_types}}
  • Assistive ecosystem: {{assistive_tech_stack}}
  • Compliance threshold: {{wcag_conformance_target}}
  • Baseline accessibility audit data: {{known_accessibility_barriers}}

Task

Analyze asynchronous interactive courseware components to construct an interaction accessibility matrix that diagnoses barriers across screen readers, keyboard-only navigation, and cognitive load, providing verified UX remediation strategies.

Method

  1. Deconstruct the interaction lifecycle of each component specified in {{interactive_module_types}}.
  2. Cross-examine user interaction flows against the assistive tool requirements in {{assistive_tech_stack}}.
  3. Audit keyboard focus traps, live region announcements, and focus management across dynamic module state changes.
  4. Cross-reference identified barriers against {{wcag_conformance_target}} success criteria and {{known_accessibility_barriers}}.
  5. Evaluate cognitive accessibility including time limits, instruction clarity, and cognitive switching costs for {{learner_demographics}}.
  6. Determine concrete UX design patterns (e.g., skip links, ARIA live patterns, high-contrast states) to resolve each barrier.
  7. Map the components into a comparative accessibility triage matrix based on barrier severity, compliance risk, and implementation complexity.

Constraints

  • Every remediation proposal MUST reference a specific WCAG 2.2 Success Criterion.
  • You MUST NOT suggest disabling dynamic interactivity as a solution for accessibility compliance.
  • All recommendations MUST preserve pedagogical efficacy for all students described in {{learner_demographics}}.
  • Screen reader announcements MUST specify recommended aria-live, aria-label, or focus shifts explicitly.

Output format

  1. Baseline Accessibility Evaluation (100-150 words analyzing current compliance posture on {{lms_platform_name}}).
  2. Comprehensive UX Accessibility Matrix (Markdown table with columns: UI Component, Interaction Pattern, Assistive Tech Affected, WCAG 2.2 Criterion, Barrier Severity [Critical/Serious/Moderate], Prescribed Interaction Remediation).
  3. Component Remediation Blueprints (3-4 concise technical specifications for high-impact patterns).
  4. Verification & Testing Protocol (bulleted list of 5 concrete screen-reader and manual testing checks).

Self-review

  • Are all components from {{interactive_module_types}} evaluated systematically?
  • Does every matrix entry contain an explicit WCAG 2.2 criterion reference?
  • Are the prescribed interaction patterns compatible with {{assistive_tech_stack}}?
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

design-visual
design-ui-ux
education-research
accessibility-a11y
edtech-ui
lms-design