Culture-based AI Research
Culture-Based Artificial Intelligence
My research investigates how artificial intelligence can serve diverse learners equitably. For seventeen years, I have tracked technologies and continue to notice that a culture-based framework that minimizes algorithmic bias is needed.
The Challenge
AI systems often embed the assumptions and biases of their designers resulting in technologies that serve some populations well while failing others. My work addresses fundamental questions: How do we integrate culture in the design of AI and all technologies for learning? How do we build technological systems that minimize bias? How can AI recognize diverse learning patterns as valid?
Research Trajectory
2008 | Foundational Framework "Integrating Culture in the Design of ICTs" (British Journal of Educational Technology) established a broader design space from culture-neutral to culture-specific technologies. Winner, Outstanding Journal Article Award, Association for Educational Communications & Technology.
2009 | The Culture Based Model Instructional Design Frameworks & Intercultural Models introduced a comprehensive framework with 1,500 questions and 70 design factors for building culture-based information and communication technologies. Recognized in Survey of Instructional Design Models (Dousay & Branch, 2022).
2011 | Application to AI "The Significance of the Culture Based Model in Designing Culturally-Aware Tutoring Systems" (Artificial Intelligence & Society) demonstrated how systematic cultural frameworks prevent designer bias from becoming embedded in intelligent tutoring systems.
2014-2022 | Learning Analytics Built Proticy, a cloud-based learning analytics platform enabling instructors to make pedagogical decisions based on real-time data collection and analysis. This work revealed the need for AI capabilities to advance from analytics to truly adaptive personalization.
2021 | AI and Human Specialization Human Specialization in Design & Technology tracks the global shift toward specialized designs. Chapter 5, "The EdTech of Things," examines AI's evolution toward human-centered specialization and critiques algorithmic bias. Winner, 2021 Outstanding Publication Award, Association for Educational Communications & Technology.
Public Scholarship on AI
I engage broader audiences on AI's implications for education:
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"Should AI be permitted in college classrooms? 4 scholars weigh in" (The Conversation, 2023)
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"The future of college will involve fewer professors" (The Conversation, 2021)
Current Work
I am currently a fellow on a variety of Handshake projects, training AI tutors—experience providing direct insight into the practical challenges of developing AI learning systems. I am also generating publications from Proticy, my cloud-based learning analytics platform, analyzing data on human learning in technological contexts. This ongoing research bridges my previous work in learning analytics with my future research agenda of digitizing the Culture Based Model for AI training.
Future Research
My next phase of research will digitize the Culture Based Model converting its 1,500 questions and 70 design factors into datasets that can train AI learning systems to recognize and respond to diverse cultural approaches to learning. Once a culture-based database is established, designers can build products, services, or environments from the same dataset—scalability that positions digitized CBM as foundational infrastructure for equitable AI in education.