Alex Garrido

Teaching philosophy · Alex Garrido

The Make-It-Yours
Learning Loop.

AI-assisted creation. Human-owned understanding.

I want students to leave my classroom with the confidence and judgment to create something useful, explain their decisions, and adapt when a situation changes.

The answer is the starting point.

Imagine two students using AI to develop the same marketing plan. One submits the response because it sounds professional. The other questions its assumptions, checks its claims, changes the recommendation, and explains why the strategy fits the audience. The documents might look similar. The thinking behind them is not.

My goal is to make that thinking visible. AI can help create the answer. The student still has to create the understanding.

A loop you can put to work.

  1. Frame the problem

    Identify the audience, the decision, and the constraints. Write down what you are trying to understand before asking a tool for an answer.

  2. Co-create possibilities

    Explore approaches with your notes, classmates, and any tools permitted for the assignment. Ask for alternatives and examine the assumptions behind them.

  3. Reconstruct the idea

    Put the explanation in your own words. Make a diagram, a short comparison, or a set of notes that shows how the pieces connect.

  4. Discuss the reasoning

    Explain your decision to someone else. Let their questions reveal what needs a stronger explanation or another look.

  5. Refine the work

    Use feedback to make a specific revision. Name what changed and why the revision improves the result.

  6. Transfer the learning

    Apply the concept to a new audience, example, or situation. Try it independently so you can see what remains available without the original support.

Understanding becomes visible.

Let people see the reasoning.

As a practitioner and instructor, I explain what I would do and why, including the tradeoffs and situations in which I might choose differently. This connects to cognitive apprenticeship: modeling expert reasoning, coaching practice, and gradually increasing independence (Collins et al., 1991).

Reconstruct instead of copying.

I use handwritten notes and worksheets to create a pause for selecting, organizing, and explaining. Research finds an average achievement advantage for taking and reviewing handwritten rather than typed lecture notes, but handwriting is not the best option for every learner or task (Flanigan et al., 2024). Accessible alternatives belong in this approach. Thoughtful reconstruction is the essential requirement.

Explain it to another person.

A classmate asking “Why would that work?” can expose an assumption you have not examined. Research on self-explanation and structured peer discussion supports making space for this kind of reasoning (Bisra et al., 2018; Smith et al., 2009).

Use feedback while it can still change the work.

I want students to leave a discussion knowing their next step. Feedback becomes useful when it informs a revision, rather than remaining a comment on a finished page (Wisniewski et al., 2020). We critique the reasoning and the work, not the person.

Try it with a marketing decision.

Suppose you are planning a social media campaign for a local organization. Define the audience and the action you want people to take. Explore a few messages, then choose one and explain why it fits. Ask a classmate what feels unclear. Revise it. Finally, adapt the idea for a different audience without reopening the original answer.

That last step matters. Performing well with support today is not the same as retaining understanding for later use (Soderstrom & Bjork, 2015).

The assignment is not the final destination. The more capable person is.

I bring these research-informed practices together as a teaching philosophy. The loop itself has not been tested as a single intervention. Follow each assignment’s instructions for AI use and use the loop to examine your own understanding.

Back to student resources ↗

Research & references

  • Bisra, K., Liu, Q., Nesbit, J. C., Salimi, F., & Winne, P. H. (2018). Inducing self-explanation: A meta-analysis. Educational Psychology Review, 30, 703–725. https://doi.org/10.1007/s10648-018-9434-x
  • Collins, A., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: Making thinking visible. American Educator. Read the article.
  • Flanigan, A. E., Wheeler, J., Colliot, T., Lu, J., & Kiewra, K. A. (2024). Typed versus handwritten lecture notes and college student achievement: A meta-analysis. Educational Psychology Review, 36, Article 78. https://doi.org/10.1007/s10648-024-09914-w
  • Smith, M. K., Wood, W. B., Adams, W. K., Wieman, C., Knight, J. K., Guild, N., & Su, T. T. (2009). Why peer discussion improves student performance on in-class concept questions. Science, 323(5910), 122–124. https://doi.org/10.1126/science.1165919
  • Soderstrom, N. C., & Bjork, R. A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10(2), 176–199. https://doi.org/10.1177/1745691615569000
  • Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, Article 3087. https://doi.org/10.3389/fpsyg.2019.03087