2026-2027
Graduate Research Assistant, Cyber Sentinel Co-Pilot (Reachy Mini Social Robot Learning Environment)
Adaptive Design of Immersive e-Learning (ADIE) Lab, The University of Alabama, Tuscaloosa, AL
Evidence-based learning innovation across XR, AI, and analytics.
Case studies showing how research design, instructional design, and evaluation work together.
Studying how immersive technologies and AI-supported instruction reshape how learners experience knowledge.
Research Agenda
Project work organized as case-based evidence.
These studies show how David approaches design, evaluation, and scholarly contribution across immersive learning, AI literacy, and multimodal analytics.
Core Roles
Appointments that shaped the project portfolio.
These roles provide context for the design and research work described below.
2023-present
Graduate Research Assistant
Adaptive Design of Immersive e-Learning (ADIE) Lab, The University of Alabama, Tuscaloosa, AL
2016-2022
Research and Instructional Design Assistant
Federal University of Technology, Minna, Nigeria
May-July 2026
Instructor and Course Co-Designer, AI Fluency for the Workforce (CIE 499)
Undergraduate, The University of Alabama
Selected Case Studies
Projects that best represent the research story.
Each case study sets out the problem context, the design contribution, the methods and tools, and the outcomes.
01
Immersive STEM Learning
AI-Enhanced XR Learning for STEM Education: VR Hazard Identification in Civil Engineering
University of Alabama · Civil engineering safety training · Mixed-methods design and analytics
Problem Context
Construction safety instruction often depends on low-immersion demonstrations that make hazard recognition difficult to practice authentically before students enter high-risk settings.
Stakeholders and Context
- Civil engineering students and instructors
- Lab researchers designing VR learning tasks
- Programs preparing students for safety-critical work
Frameworks
- Multimedia learning and immersive cognition principles
- Design-based research for iterative refinement
- Performance-centered assessment for hazard identification
Methods and Tools
- VR simulation design
- Behavioral analytics
- Microgenetic analysis
- Bayesian cognitive diagnostics
Design Contribution
The project uses generative-AI-supported virtual environments and structured hazard-identification tasks to study how learners notice risks, shift strategies, and develop safer decision patterns in authentic contexts.
Outcomes
- Produced publishable work on immersive technology-enhanced learning and safety training.
- Strengthened a research program connecting XR design with measurable performance evidence.
Critical Reflection
This case anchors a broader research direction: immersive environments become more valuable when they are not only engaging, but also analytically transparent enough to reveal how expertise develops over time.
02
AI Literacy Curriculum
AI-WISE: Industry-Informed Artificial Intelligence Literacy Curriculum for Higher Education
University of Alabama · Undergraduate AI literacy design · Cross-disciplinary curriculum development
Problem Context
Students increasingly encounter AI tools in academic and professional settings, yet many programs still lack structured, ethical, and workforce-relevant AI literacy experiences.
Stakeholders and Context
- Undergraduate students across disciplines
- Faculty embedding AI in coursework
- Industry partners shaping competency expectations
Frameworks
- Backward design for outcome-aligned curriculum planning
- Universal Design for Learning for multimodal access
- Culturally responsive pedagogy for inclusive participation
Methods and Tools
- Industry competency mapping
- Co-design workshops
- Pilot curriculum implementation
- Feedback and thematic analysis
Design Contribution
AI-WISE organizes practical AI skills, ethical reasoning, and reflective evaluation into modular learning experiences that faculty can adapt without needing deep technical specialization.
Outcomes
- Created a reusable curriculum model for broader AI literacy integration.
- Supported conference dissemination around practical and equitable AI education design.
Critical Reflection
The strongest lesson here is that AI literacy is not only about tools. It is about helping learners interpret, question, and apply AI systems responsibly in disciplinary and civic contexts.
03
Physiological Learning Analytics
Beyond Self-Report: Using Eye-Tracking and Physiological Data to Evaluate Learning in Computing Environments
NSF ITEST context · Elementary computing experiences · Multimodal evaluation and broadening participation
Problem Context
Traditional evaluation methods often miss moment-to-moment evidence of attention, cognitive load, and engagement, especially with younger learners who may not fully articulate what they experienced.
Stakeholders and Context
- Elementary learners in computing activities
- Researchers collecting multimodal evidence
- Programs focused on equitable STEM pathways
Frameworks
- Mixed-methods evaluation design
- Cognitive load theory
- Learning analytics for multimodal evidence integration
Methods and Tools
- Eye-tracking and pupil-dilation analysis
- Physiological sensing
- Cross-case comparison
- Quantitative and qualitative synthesis
Design Contribution
This work integrates physiological and behavioral data with more familiar assessments to create a richer view of how learners experience computing tasks and where instructional support is needed.
Outcomes
- Contributed to NSF-supported research on computing participation and learner experience.
- Extended evaluation practice beyond self-report toward more responsive evidence models.
Critical Reflection
The project reinforced an important design belief: evaluation should not be an afterthought. It should be built into how we understand learning as it unfolds, especially in novel technology environments.
04
Arts-Integrated GenAI Literacy
Arts-Integrated GenAI Literacy Development Program for Pre-Service Teachers
University of Alabama · Music and theater modules on Blackboard LMS · Mixed-methods online study
Problem Context
Pre-service teachers are entering classrooms where generative AI is reshaping how learners create, evaluate, and share knowledge, yet few have a structured opportunity to develop GenAI literacy through their own creative practice before they teach.
Stakeholders and Context
- Pre-service teachers across content areas
- Teacher educators preparing future classroom innovators
- Arts and STEM faculty designing integrated learning experiences
Frameworks
- Arts-integration pedagogy for transferable creative competencies
- GenAI literacy framework spanning prompting, evaluation, and ethics
- Backward design for outcome-aligned online professional development
Methods and Tools
- Two-module Blackboard course (four lessons each in Music and Theater)
- Mixed-methods evaluation: pre-/post-lesson assessments, usability and engagement surveys
- Reflective discussion-board submissions of learner-produced digital art
- Optional follow-up interviews and consent-based participation
Design Contribution
The program engages pre-service teachers in hands-on creative work with GenAI tools, SUNO AI, Boomy, Animake, Invideo AI, Synthesis AI, Soundtrap, across four music and four theater lessons. Each lesson scaffolds prompt engineering, AI feedback evaluation, and AI ethics reasoning alongside the artistic output: songs, soundtracks, animated performances, digital choreography, and dramatic storytelling.
Outcomes
- Designed and deployed a complete online professional-development module set with structured pre/post measures, reflective tasks, and discussion-board sharing.
- Built evidence connecting arts-integrated GenAI engagement with growth in computational thinking, prompt engineering, problem-solving, AI feedback evaluation, AI ethics literacy, creativity, and collaboration.
- Ran a participant cohort April 22, June 20, 2025 with completion incentives and a multi-instrument data set ready for thematic and statistical analysis.
Critical Reflection
Arts integration turns GenAI literacy into something pre-service teachers DO rather than something they read about, and that change of stance is what makes the competencies transferable to their own future classrooms.
Current Project
Funded work now under way.
A newly funded project that extends the research program toward embodied AI and social robotics.
Funded, 2026 to 2027
Cyber Sentinel Co-Pilot: social robotics for cybersecurity teacher training
Funded by the College of Education RisingTide Grant Program ($30,000, 2026 to 2027; Lead PI Dr. Jewoong Moon), this project builds a large-language-model co-pilot on the Reachy Mini social robot to deliver cybersecurity professional development for Alabama secondary teachers. I developed the browser-based middleware that gives the robot voice, text, and visual interaction across five guided cybersecurity lessons, engineered on-robot deployment with automated startup and fault recovery so it runs in classrooms without technical support, and designed the data-collection architecture for a planned mixed-methods study across a five-robot fleet.
This work connects my interests in immersive and emerging technologies, teacher professional development, and broadening participation in computing, extending them toward human–robot interaction as an instructional medium.