OER Integration at UC San Diego

Institutional Infrastructure & Systems Research (Ongoing)

I am currently working on institutional research and infrastructure planning for Open Educational Resource (OER) adoption at UC San Diego through SPACES. The project focuses on identifying technical, organizational, and policy bottlenecks that limit large-scale adoption, and on designing integration pathways for a centralized OER resource hub serving instructional staff.

The Problem: Why OER Adoption Stalls

Open Educational Resources, freely accessible textbooks, course materials, and learning tools, have proven benefits:

• Cost Savings: Eliminates textbook costs for students ($300–$1,200 per year)
• Equity: Removes financial barriers to course materials
• Pedagogy: Enables customization, iteration, and open collaboration

Yet adoption at scale is surprisingly difficult. The challenge isn’t technical viability, it’s systems integration:

• Instructors don’t know OERs exist or how to find quality resources
• Departments lack standardized evaluation criteria for course materials
• Library systems and course management platforms aren’t designed for OER workflows
• Policy frameworks assume traditional publisher relationships

This project treats OER adoption as an infrastructure challenge, not just a content availability problem.

My Role: Systems Research & Integration Planning

My work centers on three areas:

1. Bottleneck Identification

Research Question: What prevents instructors from adopting OER at scale?

I’m conducting:

• Stakeholder Interviews: Faculty, librarians, department chairs, instructional designers
• Workflow Mapping: Document current course material selection processes
• Policy Analysis: Identify misaligned incentives and structural barriers
• Technical Assessment: Evaluate existing discovery, hosting, and distribution infrastructure

Goal, Produce a comprehensive map of adoption blockers, technical, organizational, and cultural.

2. Infrastructure Design

Design Challenge: What does a centralized OER hub need to do?

Based on research findings, I’m developing proposals for:

• Discovery Platform: Search and recommendation system for OER by course, discipline, topic
• Quality Assurance: Peer review process, instructor ratings, usage analytics
• Integration with LMS: Seamless linking from Canvas to OER resources
• Hosting Infrastructure: Local repository for curated, UCSD-specific OER
• Support Services: Training, conversion assistance, technical help desk

Goal, Translate user needs into actionable technical requirements.

3. Cross-Departmental Coordination

Organizational Challenge: OER adoption requires buy-in from:

• Academic Senate (policy)
• Library (discovery + hosting)
• ITS (technical infrastructure)
• Instructional & Faculty Development (training)
• Student Affairs (equity advocacy)

I’m helping coordinate across these groups to ensure:

• Proposals align with existing strategic priorities
• Technical solutions fit into current IT ecosystems
• Policy recommendations are feasible within university governance
• Equity outcomes are measurable and tracked

Goal, Make OER integration institutionally viable, not just technically possible.

Current Deliverables (In Progress)

1. Bottleneck Analysis Report: Synthesis of interview findings + workflow diagrams
2. Infrastructure Proposal: Technical architecture + implementation roadmap
3. Policy Recommendations: Changes to course material selection, faculty evaluation, budgeting
4. Pilot Program Design: Phased rollout strategy with measurable outcomes

Why This Matters for ML/Space Roles

This project is less code-heavy than my others, but it reflects systems-level thinking essential in large engineering organizations:

• Requirements Engineering: Translating user needs → technical specifications
• Stakeholder Management: Coordinating across teams with different priorities
• Constraint Analysis: Understanding what’s technically possible vs. organizationally feasible
• Infrastructure Planning: Designing systems that integrate with existing workflows
• Impact Measurement: Defining success metrics that align with institutional goals

These are the same skills required for:

• Mission Planning: Coordinating science, engineering, operations, and policy teams
• Systems Engineering: Designing spacecraft systems that meet user requirements
• Program Management: Translating technical capabilities → mission objectives
• Infrastructure Scaling: Growing data pipelines, compute resources, team capabilities

The Space Industry Parallel

In space programs, technical excellence alone doesn’t ensure mission success. You also need:

• Cross-functional coordination (science, engineering, operations, budget)
• Institutional knowledge (NASA processes, DoD acquisition, international partnerships)
• Stakeholder alignment (Congress, international partners, scientific community)
• Long-term sustainability (maintenance, knowledge transfer, funding continuity)

This OER project operates in the same mode: building systems that work within institutional constraints, not just building systems that work in theory.

Technical vs. Systems Work

I’m highlighting this project because space industry roles increasingly require systems-level thinking, not just coding:

• ML engineers at JPL coordinate with mission planners, not just write algorithms
• Data scientists at SpaceX translate engineering constraints into optimization problems
• Software engineers at NASA integrate with legacy systems and multi-decade programs

Strong technical skills are necessary, but understanding how to operate in complex organizations is what separates junior from senior engineers.

Current Status

Ongoing, Reports and proposals in development (expected completion: Spring 2025)

The project is progressing through iterative stakeholder engagement, draft proposal reviews, and coordination with UCSD leadership.

Outcomes & Lessons

Even before final deliverables, this project has reinforced key lessons:

1. Technical Solutions Must Fit Institutional Context, The best design on paper fails if it doesn’t align with how people actually work.
2. Bottlenecks Are Often Organizational, Not Technical, Most OER blockers are process/policy problems disguised as technical problems.
3. Measurement Matters, Without clear metrics, equity initiatives lose momentum.
4. Change Requires Coalition-Building, No single department can implement large-scale infrastructure alone.

These are the same principles that make space missions succeed or fail.

---

Key Insight, Engineering isn’t just about building things, it’s about building things that fit into larger systems. The best engineers understand technical constraints and organizational reality.