Listen and learn: Edtalk 
Recorded Session
Virtual Session
By the end of our presentation, participants will be able to design classroom assignments or activities to increase personalized learning. We will focus on personalization through learner choice and voice. To increase choice, we will provide strategies aligned to four autonomous preferences that students may fall into when learning. To increase voice, we provide strategies for how to take advantage of learners’ perceived technological affordances to help them utilize technology in ways that fit their needs.
Our content focuses on instructional design strategies that promote personalized learning through increased opportunities for choice and voice. To promote personalization through choice, we will focus on how instructors can support diverse learners by recognizing and designing for four autonomous preferences. To promote voice, we will focus on strategies that help instructors design activities to tap into potential technological affordances (i.e., possibilities) learners perceive.
We focus on supporting choice by addressing four autonomous preferences likely held by learners in online environments. These preferences include efficiency, structure, depth, and experimentation. These preferences reflect students’ natural autonomy or ways they would control their learning. We will provide definitions and examples for each autonomous preference. We indicate how each learner approaches control.
We focus on supporting voice by offering strategies that tap into learners’ perceived technological affordances or possibilities made possible by the technology. These affordances include accessibility and adaptability. We offer potential strategies to help instructors utilize students’ natural technology preferences. Today’s learners are constantly wired and connected, and we, as instructors, can leverage these technologies to enhance the learning experience.
After providing definitions and examples of the four autonomous preferences and the two perceived affordances, we will provide specific ways instructors can use these lessons in their classrooms. We offer instructional strategies that promote small changes to increase learner choice and voice. We will utilize the most significant chunk of our session to work interactively with participants to help them identify small changes they could make that would increase students’ choice and voice and personalization.
In a 45-minute webinar, the time would be divided as follows:
5 minutes - intro and welcome
10 minutes - breakdown of differences in 4 autonomous preferences
10 minutes - breakdown of perceived affordances
20 minutes - integration & application + Q/A
We will use Mentimeter, an online software that lets us present our information and embed polls, word clouds, and other activities directly into our content. We will use polls to document our participants’ current practices; we will use word clouds to capture challenges and to facilitate application in this format. We anticipate 2-5 opportunities for interaction with the audience during the 45-minute EdTalk; notably, the last segment of our EdTalk would be an opportunity for participants to integrate, apply, and ask lingering questions.
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Czerkawski, B. C. (2016). Blending formal and informal learning networks for online learning. International Review of Research in Open and Distributed Learning, 17(3), 138-156.
Walkington, C., & Bernacki, M. L. (2020). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of Research on Technology in Education, 52(3), 235-252. https://doi.org/10.1080/15391523.2020.1747757
Watkins, K. E., Marsick, V. J., Wofford, M. G., & Ellinger, A. D. (2018). The evolving Marsick and Watkins (1990) Theory of Informal and Incidental Learning. New Directions for Adult and Continuing Education, 159, 21-36. https://doi.org/10.1002/ace.20285
Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational Research Review, 31, 100339.
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