Using Personalized Learning to Promote Lifelong Learning

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As a professor with a research history in personalized learning, I have witnessed the transformative power of tailoring education to individual needs, preferences, and interests. While personalized learning has been a part of education for centuries, recent advancements in instructional technology have paved the way for a more accessible and effective approach. The slides accompanying this blog post demonstrate that both teachers and students recognize and appreciate the affordances of personalized learning, marking a crucial shift in educational paradigms.

The evolution of personalized learning, underscores its potential as a gateway to lifelong learning. The 2017 U.S. National Education Technology Plan redefined personalized learning to emphasize the learner's role in tailoring instruction, emphasizing activities that are meaningful, relevant, and often self-initiated. This learner-centric approach aligns with the call for a dynamic, personalized learning strategy capable of providing a unique and effective learning experience for each individual, fostering the skills needed to promote a lifelong commitment to learning.

Technological advancements have given educational institutions the tools to customize learning experiences, but the true power lies in the pedagogical knowledge required to leverage personalized learning effectively. My research, drawing on frameworks and findings presented by experts like Horn and Staker (2014), Graham et al. (2019), and Shemshack et al. (2021), has emphasized the importance of tailoring the time, place, pace, path, and goals of learning. By incorporating learner profiles, previous knowledge, personalized learning paths, and flexible self-paced environments, educators can empower learners to take charge of their education and enhance their self-efficacy.

The five dimensions of personalized learning (goals, time, place, pace, and path), illustrate the multifaceted nature of this pedagogical strategy. Understanding what is being personalized, how it is being personalized, who or what is providing personalization, and what the personalization is based on allows educators to create tailored, effective learning experiences. While the potential of personalized learning is vast, ongoing research, as highlighted by Short (2022), Bulger (2016), Watters (2023), and Zhang et al. (2020), is necessary to explore outcomes and ensure technology fulfills its promise of transformational, individualized learning.

Read more foundational information about Personalized Learning in my chapter on the topic in EdTechnica co-authored by the brilliant Atikah Shemshack: https://edtechbooks.org/encyclopedia/personalized_learning

Short, C. R. & Shemshack, A. (2023). Personalized Learning. EdTechnica: The Open Encyclopedia of Educational Technology. https://dx.doi.org/10.59668/371.11067

Bulger, M. (July 7, 2016). Personalized learning: The conversations we're not having. Data and Society 22(1), 1-29. https://edtechbooks.org/-jkKy

Graham, C. R., Borup, J., Short, C. R., & Archambault, L. (2019). K-12 blended teaching: A guide to personalized learning and online integration. Provo, UT: EdTechBooks.org. https://edtechbooks.org/-TiF

Horn, M. B., & Staker, H. (2014). Blended: Using disruptive innovation to improve schools. Jossey-Bass.

Shemshack, A., Kinshuk & Spector, J. M. (2021). A comprehensive analysis of personalized learning components. Journal of Computers in Education, 1(19). https://edtechbooks.org/-Uwr

Short, C. R. (2022). Personalized learning design framework: A theoretical framework for defining, implementing, and evaluating personalized learning. In H. Leary, S. P. Greenhalgh, K. B. Staudt Willet, & M. H. Cho (Eds.), Theories to Influence the Future of Learning Design and Technology. EdTech Books. https://edtechbooks.org/-GBqb

Watters, A. (2023). Teaching machines: The history of personalized learning. The MIT Press.

Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational Research Review, 31(100339). https://edtechbooks.org/-RLV

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