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Instructional DesignResearch University

AI-Powered Instructional Design for Research Universities

Streamline course design, faculty support, and accessibility compliance across your entire research university with purpose-built AI agents. ibl.ai integrates with your existing LMS and SIS — no rip-and-replace required.

The Problem

Instructional design teams at research universities are stretched thin. With 15,000–60,000 students, hundreds of faculty, and complex compliance mandates, small ID teams can't scale manually.

Siloed departments, legacy LMS platforms, and inconsistent course quality create bottlenecks that delay course launches and frustrate faculty. Accessibility audits alone can consume weeks of staff time per semester.

AI changes the equation. ibl.ai's purpose-built agents handle repetitive design tasks, surface compliance gaps automatically, and give every faculty member on-demand instructional support — freeing your team to focus on high-impact work.

Understaffed ID Teams, Overwhelming Demand

Most research universities have 1 instructional designer per 150–300 faculty. Demand for course redesigns, new online programs, and LMS support far exceeds capacity.

1:200 average ID-to-faculty ratio at R1 universities

Accessibility Compliance Backlogs

WCAG and ADA compliance reviews are manual, time-consuming, and inconsistent. Courses with inaccessible content expose institutions to legal risk and harm student outcomes.

Up to 40% of course materials fail initial accessibility audits

Slow Course Development Cycles

Building a single online course from scratch can take 6–12 months. Faculty wait months for ID support, delaying program launches and reducing institutional agility.

Average new online course development: 6–9 months

Inconsistent Assessment Design

Without scalable review processes, assessment quality varies widely across departments. Misaligned learning objectives and assessments undermine accreditation readiness.

Over 60% of course assessments lack documented alignment to learning outcomes

Legacy LMS Integration Complexity

Research universities run Canvas, Blackboard, Banner, and PeopleSoft simultaneously. ID teams waste hours on manual data migration, course copying, and cross-system troubleshooting.

ID staff spend 30–40% of time on LMS administration vs. design work

AI Capabilities

AI-Assisted Course Design

Generate course outlines, learning objectives, module structures, and instructional scaffolding in minutes. AI agents align content to accreditation standards and institutional templates automatically.

Automated Accessibility Compliance

Continuously audit course materials for WCAG 2.1 and ADA compliance. AI flags issues, suggests remediation, and tracks resolution — reducing legal risk and manual review time.

Faculty Support AI Agent

A dedicated AI agent answers faculty questions about LMS tools, course design best practices, and instructional strategies 24/7 — reducing ID team support tickets by up to 50%.

AI-Powered Assessment Builder

Design rubrics, formative assessments, and summative evaluations aligned to Bloom's Taxonomy and course outcomes. AI validates alignment and suggests improvements before publishing.

Agentic Content Adaptation

Automatically adapt existing course content for different modalities — online, hybrid, HyFlex — and reading levels. Repurpose lecture materials into interactive modules, quizzes, and summaries.

LMS Integration & Workflow Automation

Connect directly to Canvas, Blackboard, Banner, and PeopleSoft. Automate course shell creation, enrollment syncing, and reporting — eliminating manual administrative overhead.

Implementation Timeline

1

Discovery & Systems Integration

2–3 weeks

Audit existing LMS, SIS, and content repositories. Map ID team workflows, identify compliance gaps, and configure secure integrations with Canvas, Blackboard, Banner, or PeopleSoft.

  • Workflow and systems audit report
  • LMS and SIS integration configuration
  • Data governance and FERPA compliance review
  • AI agent deployment architecture plan
2

AI Agent Configuration & Pilot

3–4 weeks

Deploy and configure purpose-built AI agents for course design, accessibility auditing, and faculty support. Run a pilot with 2–3 departments to validate workflows and gather feedback.

  • Configured course design AI agent
  • Accessibility compliance agent with audit dashboard
  • Faculty support AI agent (LMS-integrated)
  • Pilot department onboarding and training
3

Full Deployment & Faculty Enablement

4–5 weeks

Roll out AI agents institution-wide. Train instructional designers and faculty liaisons. Launch self-service faculty support portal and automated accessibility monitoring across all active courses.

  • Institution-wide agent deployment
  • Faculty and ID team training sessions
  • Self-service instructional design portal
  • Accessibility compliance monitoring dashboard
4

Optimization & Continuous Improvement

Ongoing

Analyze agent performance data, refine prompts and workflows, and expand AI capabilities to new departments or use cases. Quarterly reviews ensure alignment with accreditation and compliance requirements.

  • Quarterly performance and compliance reports
  • Agent refinement and workflow updates
  • Expansion roadmap for new departments
  • Accreditation-ready documentation exports

Expected Outcomes

-70%
Course Development Time
6–9 months per new online course6–10 weeks with AI-assisted design
+35%
Accessibility Compliance Rate
~60% of courses pass initial audit95%+ courses meet WCAG 2.1 standards
-60%
ID Team Support Ticket Volume
200+ faculty support tickets per monthUnder 80 tickets with AI agent deflection
+125%
Assessment Alignment Score
Less than 40% of assessments documented as outcome-aligned90%+ assessments aligned and documented

Before & After AI

Before

ID team manually builds course outlines, objectives, and module structures from scratch for each faculty request — taking weeks per course.

After

AI agents generate draft course structures, objectives, and scaffolding in minutes. ID team reviews and refines, cutting design time by 70%.

Before

Accessibility audits are manual, inconsistent, and reactive — often triggered only by complaints or legal notices.

After

Continuous automated accessibility monitoring flags issues in real time, with AI-suggested remediation and a compliance dashboard for the entire course catalog.

Before

Faculty email or call the ID team for LMS help, instructional questions, and design advice — creating bottlenecks and long response times.

After

A 24/7 AI faculty support agent answers LMS and instructional design questions instantly, escalating only complex cases to human ID staff.

Before

Assessments are created ad hoc by faculty with little alignment review, creating accreditation documentation gaps.

After

AI assessment builder validates alignment to learning outcomes and Bloom's Taxonomy before publishing, generating accreditation-ready documentation automatically.

Before

ID staff manually create course shells, sync enrollments, and troubleshoot cross-system issues between Canvas, Banner, and PeopleSoft.

After

Automated LMS-SIS integration handles course shell creation, enrollment syncing, and reporting — freeing ID staff for high-value design work.

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