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My Personal Theory of Learning

How do I Approach Design?

My personal learning theory is grounded in constructivist traditions and an iterative design process suited to realistic contexts.
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When approaching instructional opportunities, I believe in an iterative design strategy that allows for movement, flexibility, and high collaboration with stakeholders. To accomplish this, I follow the parameters of the Successive Approximation Model (SAM) to prepare, create, evaluate, and refine my work, as a gardener cares for their plants by analyzing what they need to thrive and adapting accordingly. My experience as an instructional designer for Orlando Utilities Commission (OUC) demonstrates that a flexible, refinement-based strategy is optimal for realistic collaboration, rapid changes, and end-user-centered goals. 

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​Additionally, I have found in my graduate studies and internships that constructivist learning experiences, where the learner builds unique knowledge through active engagement, real-world application, and self-reflection, yield the greatest outcomes for behavior change and real-world transfer. Just as a gardener must allow their seedlings to sprout independently to eventually grow into strong-rooted plants. Drawing inspiration from the curriculum futurist Marc Prensky, I often implement skill-based strategies that provide learners with a toolkit for problem-solving, critical thinking, and collaboration, rather than rote memorization and recall. By doing this, I attempt to create sustainable learning that evolves with experience, even beyond training, instead of plateauing.

 

To accomplish this, I incorporate activities such as simulations, educational games, and maker-based opportunities into my learning experiences. I believe that by providing learners with opportunities to explore concepts through experience, they may engage in unique personal reflection and schema assimilation, helping them make sense of new concepts through their own mental models. Moreover, by encouraging social learning through collaboration, critique, and discussion, I have found that learners may develop deep perspectives informed by both their personal experiences and those of their peers. For example, in the SMART in-person simulation workshops I am facilitating at OUC, I leverage the sharing of learner perspectives and experiences through group discussions, allowing everyone, including myself, to learn as deeply and empathetically as possible. Centralizing the experience on the learner and their peers through a student-centered approach also helps establish intrinsic self-responsibility that can translate into genuine student effort and accountability.

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​I am currently researching the strategic link between artificial intelligence in educational experiences and user autonomy. In other words, I aim to answer the question: how can instructional designers create immersive, personalized learning experiences that leverage artificial intelligence while also giving learners high control over their own experience? What is the balance between technology and the learner? How does user autonomy enhance the learner's educational experience despite the industry's movement toward automation?

 

How can I create learning experiences that deliver AI-driven, adaptive personalization at a moment's notice while also giving the learner control?

 

 

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