Martin, P. P., Kubsch, M., Yik, B. J., Burlingham, B. T., & Graulich, N. (2026). Adaptive, but Equitable? Exploring the Impact of Machine Learning-Based Adaptive Support on Educational Debts in Undergraduate Chemistry. Science Education, 110(3), 928. https://doi.org/10.1002/sce.70042
Chicago Style (17th ed.) CitationMartin, Paul P., Marcus Kubsch, Brandon J. Yik, Benjamin T. Burlingham, and Nicole Graulich. "Adaptive, but Equitable? Exploring the Impact of Machine Learning-Based Adaptive Support on Educational Debts in Undergraduate Chemistry." Science Education 110, no. 3 (2026): 928. https://doi.org/10.1002/sce.70042.
MLA (9th ed.) CitationMartin, Paul P., et al. "Adaptive, but Equitable? Exploring the Impact of Machine Learning-Based Adaptive Support on Educational Debts in Undergraduate Chemistry." Science Education, vol. 110, no. 3, 2026, p. 928, https://doi.org/10.1002/sce.70042.
