Abstract
We studied factors shaping polarization within the population of the United States in order to examine the complexity of building and evaluating adaptive-inclusive learning environments. Our approach evolved from prior research and used “Thought Experiments” and literature reviews of educational as well as cognitive, developmental, psychosocial, and social psychology research. The goal has been to understand critical barriers to inclusivity and adaptivity within blended and totally online learning environments. We analyzed the political and sociological diversity of the United States as a conceptual framework for delineating critical elements of AI designs that could result in truly adaptive and inclusive teaching-learning environments across grade levels from Kindergarten to graduate work but also essential to the emerging needs for life-long learning and adaptation to shifts in technology use by the American workforce. As the research that led to this paper unfolded, we studied promising AI applications such as ChatGBT, focusing on how elements of such applications could become part of an adaptive-inclusive learning environment as well as what adaptations would be needed for them to have inclusive and adaptive capacities that serve diverse learners.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tashiro, J., Hebeler, A.: An evidence-based model of adaptive blended learning for health education serving families with a parent or child who has a medical problem. Int. J. Innov. Learn. 29(3), 300–321 (2021)
Tashiro, J., Hung, P.C.K., Vargas Martin, M.: Can an evidence-based blended learning model serve healthcare patients and adult education students? In: Cheung, S.K.S., Kwok, L.-F., Kubota, K., Lee, L.-K., Tokito, J. (eds.) ICBL 2018. LNCS, vol. 10949, pp. 17–42. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-319-94505-7_2
Tashiro, J., Hung, P.C.K., Martin, M.V.: Evidence-based educational practices and a theoretical framework for hybrid learning. In: Kwan, R., Fong, J., Kwok, L.-F., Lam, J. (eds.) ICHL 2011. LNCS, vol. 6837, pp. 51–72. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22763-9_6
Tashiro, J., Hung, P., Vargas Martin, M., Hurst, F., Brown, A.: Personalized-adaptive learning—an operational framework for developing competency-based curricula in computer information technology. Int. J. Innov. Learn. 19(4), 412–430 (2016)
Tashiro, J., Hung, P.C.K., Martin, M.V., Tashiro, R.R.: What really works in hybrid learning: a cognitive perspective. In: Cheung, S.K.S., Kwok, L.-F., Yang, H., Fong, J., Kwan, R. (eds.) ICHL 2015. LNCS, vol. 9167, pp. 15–35. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20621-9_2
Tan, J., Hung, P., Dohan, M., Trojer, T., Farwick, M., Tashiro, J.: Gateway to quality living for the elderly: charting an innovative approach to evidence-based e-health technologies for serving the chronically ill. Proceedings of the 13th IEEE International Conference on Computational Science and Engineering (CSE-2010/December 11–13 2010), Hong Kong (2010)
Schaul, K., Chen, S.Y., Tiku, N.: Inside the Secret List of Websites that Make AI Like Chat GPT Sound Smart. The Washington Post. https://www.washingtonpost.com/technology/interactive/2023/ai-chatbot-learning/
Alpert, J., Krist, A., Aycock, R., Kreps, G.: Applying multiple methods to comprehensively evaluate a patient portal’s effectiveness to convey information to patients. J. Med. Internet Res. 18(5) (2016)
Irizarry, T., DeVito Dabbs, A., Curran, C.: Patient portals and patient engagement: a state of the science review. J. Med. Internet Res. 17(6) (2015)
Ammonwerth, E., Schnell-Inderst, P., Hoerbst, A.: The impact of electronic patient portals on patient care: a systematic review of controlled trials. J. Med. Internet Res. 14(6) (2015)
Healthcare Toolbox: Basics of trauma-informed care. http://healtcaretoolbox.org/for-parents-and-children.html. Retrieved 25 Jan 2019
Wald, H., Dube, C., Anthony, D.: Untangling the web—the impact of internet use on health care and physician-patient relationship. Patient Educ. Couns. 68, 218–224 (2007)
Centola, D.: How Behavior Spreads—The Science of Complex Contagions. Princeton University Press, Princeton and Oxford (2018)
Smedley, B.B., Stith, A.Y., Nelson, A.R. (eds.): Unequal Treatment—Confronting Racial and Ethnic Disparities in Health Care. The National Academies Press, Washington, D.C. (2003)
Committee on Quality of Health Care in America: Crossing the Quality Chasm: A New Health System for the 21st Century. National Academy Press, Washington D.C (2001)
Wilkerson, I.: Caste—The Origins of Our Discontents. Random House, New York (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Tashiro, J.S., Hartman, Q. (2023). Key Complexities Inhibiting Design and Implementation of Adaptive-Inclusive Learning Environments. In: Li, C., Cheung, S.K.S., Wang, F.L., Lu, A., Kwok, L.F. (eds) Blended Learning : Lessons Learned and Ways Forward . ICBL 2023. Lecture Notes in Computer Science, vol 13978. Springer, Cham. https://doi.org/10.1007/978-3-031-35731-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-031-35731-2_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-35730-5
Online ISBN: 978-3-031-35731-2
eBook Packages: Computer ScienceComputer Science (R0)