eLearning · UX Research · Social Impact
Nuances of Forced Migration
An interactive e-learning course unpacking the systems behind forced displacement.
Overview
Nuances of Forced Migration is an interactive e-learning course designed to unpack the how, why, and systems that fuel forced displacement across the globe. Unlike traditional educational resources that focus on surface-level causes, this course dives into the layered complexities of forced migration — including conflict, persecution, climate disasters, economic hardship, and the policies that trap people in motion.
Crafted to feel accessible yet emotionally resonant, this course blends UI/UX storytelling, real-world data, ELSI Principles, and intuitive learning modules to educate high school and college-level audiences on the multidimensional nature of migration.
Design Goals
- Simplify complexity without compromising depth
- Apply ELSI Principles to the topic
- Represent lived experiences with dignity and nuance
- Create a UI/UX that feels conversational, modular, and digestible
- Empower users to think critically about systems — not just symptoms
- Build a framework for layered learning: from personal impact to global
My Contributions
- Designed UI wireframes and visual flow for modular navigation, including sidebar transitions, onboarding entry point, and progressive module reveal
- Wrote and structured introductory module language to establish tone and contextual framing
- Applied ELSI principles to make the lesson easier to process and help evoke empathy
- Developed a scenario-based branching narrative system within select modules that let learners step into the role of displaced individuals
- Built consistent narrative framing across modules to center empathy, agency, and systems-level understanding
- Conducted internal usability tests to assess for information overload, emotional fatigue, and navigational clarity
- Created text-to-visual mappings and illustrative graphic elements to reduce cognitive load while increasing retention
Evaluation Methodology
Learning outcomes were tested using a pre/post-test design with 6 participants. Each participant completed a questionnaire before and after the course to measure knowledge gain and empathy shift across three learning objectives.
(pre + post)
measured
Recruitment
Participants were recruited from the HCI 520 cohort — graduate students with varying prior knowledge of forced migration. The sample was intentionally kept small to respect time constraints, with the trade-off of limited statistical generalizability.
Instruments
- Pre-test (8 questions): Multiple choice, mapped to LO1 (foundational knowledge of forced migration causes and affected populations)
- Post-test (10 questions): Multiple choice + Likert scale (confidence rating 1–5) + open-ended reflection question, mapped to LO1, LO2, and LO3
- The Likert and open-ended questions weren't in the original design — they were added mid-process, after early testing showed the multiple-choice-only instrument couldn't capture whether the course was actually shifting empathy, only whether it was transferring facts
That revision is the methodological decision I'd point to first: recognizing an instrument doesn't measure what you actually care about, and fixing it before running the full study rather than after.
Findings
Knowledge (LO1)
Most participants entered with pre-existing foundational knowledge. Post-test responses revealed nuanced shifts rather than dramatic gains — for example, one participant shifted from "All of the above" to a more specific cause (persecution and political instability), suggesting the course deepened rather than introduced understanding. Some question-level variance pointed to areas where content clarity could be improved.
Emotional Understanding (LO2)
The scenario-based Module 5 — which placed learners in the role of a displaced individual facing survival decisions — was the primary driver of LO2 outcomes. Post-test responses showed a shift from factual recall to personal and emotional reflection.
Empathy & Behavioral Insight (LO3)
2 out of 6 participants explicitly expressed empathy in their open-ended post-test responses. Several expressed a desire to create safer spaces for displaced people — a behavioral intention shift that went beyond the course's stated knowledge objectives.
Limitations
Small sample size (n=6) limits statistical significance and generalizability. Convenience sampling from one cohort may not reflect how more diverse learners would respond. Self-reported empathy is also difficult to validate on its own terms — these responses reflect stated intention, not observed behavior, and I'd want a behavioral or longitudinal follow-up before treating the empathy findings as more than directional.
Key Learnings
- Scenario-based learning drives affective outcomes — Module 5's choice-based immersion produced the strongest empathy responses, outperforming informational modules
- Instrument design is iterative — The initial questionnaire lacked depth for measuring empathy; adding Likert + open-ended questions mid-process was the right call
- Cognitive load and emotional load must be balanced — Keeping the course to 15–30 min with segmented modules prevented fatigue on a heavy topic
- Pre-existing knowledge shapes learning goals — With an informed audience, the design goal shifted from teaching facts to deepening perspective