Publications &
Research Outputs
Explore the peer-reviewed research, policy work, public scholarship, foundational studies, and patents that inform Learnology Labs’ work in learning science, AI, early mathematics, and evidence-based education.
Research That Informs the Field
A collection of Learnology Labs’ publications, policy contributions, public scholarship, foundational research, and patents advancing the science of learning.
RESEARCH OUTPUT
Selected Bibliography
Learnology Labs Research Outputs: Peer-Reviewed & Conference Papers
Betts, A., Ryon, B., Laski, E. V., & Gunderia, S. (in press). Designing for the just-right moment: Driving human behavior through temporal scaffolding in PAL. In Proceedings of HCI International 2026. Springer.
Betts, A., Gunderia, S., & Pullen, P. (in press). The evidentiary chain: Extending Mislevy’s evidence-centered design across learning for children, educators, and families. In E. Tucker & M. E. Oliveri (Eds.), Modeling What Matters: The Research and Legacy of Robert J. Mislevy. [add publisher at proofs]
Betts, A., & Hughes, D. (accepted). The promise of personalization: Operationalizing mathematical knowledge models in the age of AI. PME-NA 48, 2026.
Betts, A., Ryon, B., Laski, E. V., & Gunderia, S. (2026). Agentic PAL: Designing human-empowered AI partnerships for early childhood mathematics learning. In Proceedings of the Learning Engineering Research Network Convening (LERN 2026). EdTech Archives. https://doi.org/10.59668/2551.25418
Betts, A., Ryon, B., & Laski, E. V. (2026). “Smart” nudges, real gains: Family engagement for kindergarten math readiness. Paper presented at the Annual Meeting of the American Educational Research Association, Los Angeles, CA.
Betts, A., Ryon, B., Laski, E. V., & Gunderia, S. (2026). Learning in the wild: PAL’s new tools and methods for research in early childhood mathematics. International Society of the Learning Sciences.
Betts, A., Ryon, B., Laski, E. V., Gunderia, S., & Hughes, D. (2026). Partnering with purpose: A research–practice–developer model for evidence-driven innovation. International Society of the Learning Sciences.
Betts, A., Laski, E. V., & Ryon, B. (2026). When the child is not the user: Leveraging AI to support early childhood well-being via adult–child interactions. Interaction Design and Children (IDC).
Betts, A., Ryon, B., & Laski, E. V. (2025). Beyond screens: Human-mediated “smart” systems for early math learning. PME-NA 47, State College, PA.
Betts, A., Gunderia, S., Hughes, D., Owen, L., & Bang, H. J. (2025). Beyond measurement: Assessment as a catalyst for personalizing learning and improving outcomes. In Handbook on Assessment in the Service of Learning, Vol. III (pp. 383–415). Springer.
Betts, A., Hughes, D., & Gunderia, S. (2024). The best start: A Bloomsian perspective on AI-powered innovations in mathematics education. PME-NA 46.
In Preparation
Betts, A., Ryon, B., & Laski, E. V. (manuscript in preparation). Every message matters: PAL dosage exposure and children’s early mathematics growth. Target: AERA 2027.
Learnology Labs Policy & Public Scholarship
Betts, A., Gunderia, S., Hughes, D., & Lenihan, E. (2024). GenAI in Education Research Accelerator (GenAiRA). Federation of American Scientists, Day One Project.
Betts, A. (2025). The AI mirror: How GenAI reflects and amplifies gaps in early math expertise. The Cutting Ed, The Learning Agency.
Betts, A. (2025). Human-AI partnerships in education: Entering the age of collaborative intelligence. The Cutting Ed, The Learning Agency.
Betts, A. (2025). Learning vs. mastery: Rethinking “smart” learning systems for optimal growth. LinkedIn.
Betts, A. (2024). Reimagining education: How knowledge models and AI can help teachers address the learner variability challenge. Learnology Labs.
Betts, A. (2024). The path to AI-driven learning: Building critical knowledge infrastructure. Learnology Labs.
Betts, A. (2024). The knowledge model imperative: Why human expertise is essential for AI in education. Learnology Labs.
Betts, A. (2024). The future is now: Accelerating learning through knowledge space theory and AI-driven personalization. Learnology Labs.
Foundational Work by Our Researchers (prior to or outside Learnology Labs; selected)
The research program at Learnology Labs builds on a foundation of earlier scholarship by its researchers.
Betts, A. (2024). Examining critical factors in parent–child math engagement. Doctoral dissertation, State University of New York at Buffalo.
Betts, A., Son, J.-W., & Bang, H.-J. (2024). Dismantling deficit-based perspectives of the pre-primary home math environments of African American and Multiracial families. AERA Annual Meeting.
Betts, A., Hughes, D., Plache, L., & Smith, K. (2024). Stretching the zone of proximal development: Accelerating learning through ZPD elasticity. IAFOR International Conference on Education.
Betts, A., & Son, J.-W. (2024). Toward an understanding of “Math Parenting Identity”: Parent perceptions of the home math environments of young children. International Society of the Learning Sciences.
Betts, A., Son, J.-W., & Bang, H.-J. (2023). Learning to parent mathematically: Critical factors in parent–child math engagement. PME-NA 45.
Betts, A., & Son, J.-W. (2022). Why parents do what they do: Developing and validating a survey for the mathematical lives of parents and children. Paris Conference on Education.
Betts, A., & Thai, K. P. (Eds.). (2022). Handbook of Research on Innovative Approaches to Early Childhood Education and School Readiness. IGI Publishing.
Thai, K. P., Betts, A., & Gunderia, S. (2022). Personalized mastery-based learning ecosystem: A new paradigm for improving outcomes and defying expectations in early childhood. In Handbook of Research on Innovative Approaches to Early Childhood Education and School Readiness (pp. 665–694). IGI Publishing.
Betts, A., Thai, K. P., & Gunderia, S. (2021). Personalized Mastery Learning Ecosystems (PMLE): Using Bloom’s four objects of change to drive learning in Adaptive Instructional Systems. In HCII 2021 Proceedings, LNCS (pp. 29–52). Springer.
Betts, A. (2021). The RESET framework: Examining critical factors in parent–child math participation. IAFOR International Conference on Education.
Betts, A., Thai, K. P., Gunderia, S., Hidalgo, P., Rothschild, M., & Hughes, D. (2020). An ambient and pervasive personalized learning ecosystem (APPLE): “Smart learning” in the age of the Internet of Things. HCII 2020 Proceedings, LNCS. Springer.
Betts, A., & Son, J.-W. (2020). Fostering parent–child math talk with the 4Cs. Mathematics Teacher: Learning and Teaching PK–12. NCTM.
Betts, A. (2019). Mastery learning in early childhood mathematics through adaptive technologies. IAFOR International Conference on Education.
Patents
Dohring, D. C., Hendry, D. A., Gunderia, S., Hughes, D., Owen, V. E., Jacobs, D. E., Betts, A., & Salak, W. (2022). Personalized mastery learning platforms, systems, media, and methods (U.S. Patent No. 11,380,211). U.S. Patent and Trademark Office.
Dohring, D. C., Hendry, D. A., Gunderia, S., Hughes, D., Owen, V. E., Jacobs, D. E., Betts, A., & Salak, W. (2021). System and method for dynamically editing online interactive elements architecture (U.S. Patent No. 11,151,887). U.S. Patent and Trademark Office.
Dohring, D. C., Hendry, D. A., Gunderia, S., Hughes, D., Owen, V. E., Jacobs, D. E., Betts, A., & Salak, W. (2019). Personalized mastery learning platforms, systems, media, and methods (U.S. Patent No. 10,490,092). U.S. Patent and Trademark Office.
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