Exploring the Psychomotor Taxonomy with an AI Bot

While developing other ‘learning bots’, I was reminded of the psychomotor domain. Last year, we had that fantastic training with Mike Gershon that introduced me to the psychomotor taxonomy.

While initially created for physical tasks, I realised that the taxonomy’s principles could be applied beyond that to other subjects. In my computer science lessons, used the psychomotor taxonomy to help students practice and advance their programming skills. Similar to a dancer repeating moves to perfect their form, my students revisited code to refine its efficiency and functionality.

Progressing through the taxonomy’s levels, it became evident that repetitive practice is critical for building expertise and enabling innovation.

Inspired by this experience, I crafted an AI bot prompt aimed at integrating more hands-on, physically engaging activities across diverse subjects.

The Bot Prompt:

You are an expert in Dave’s Psychomotor Taxonomy (1970). Your expertise covers the five levels of the taxonomy. Please follow these detailed steps.

Ask me to provide the following information:

  • The Year Group of the students
  • The Subject being taught
  • The specific Learning Objectives for the lessons

After I have provided the Year Group, Subject, and Learning Objectives, suggest activities that align with each level of Dave’s Psychomotor Taxonomy:

  • Imitation – Observing and copying someone else.
  • Manipulation – Guided via instruction to perform a skill.
  • Precision – Accuracy, proportion, and exactness in skill performance without the presence of the original source.
  • Articulation – Combining, sequencing, and consistent performance of two or more skills.
  • Naturalisation – Combining, sequencing, and effortless performance of two or more skills, resulting in an automatic response with minimal physical or mental exertion.

Make sure all suggestions are tailored specifically to the Year Group, Subject, and Learning Objectives I provide.

NB: When testing this prompt, Claude said it wasn’t an expert 50% of the time. But when asked to imagine it was, it could run the prompt fine. Likely its ethical training at play.

While skill-based subjects like art, music, and PE intuitively align with the psychomotor domain, it can be applied across disciplines. Engaging in hands-on activities and repetition reinforces muscle memory while also resonating more with students compared to passive learning.

My goal is to use this AI bot to enrich our curriculum, making it more interactive and impactful. Integrating psychomotor activities can cultivate active student involvement and learning. Studies confirm that physical movement and repetition invigorates the brain, facilitating knowledge assimilation. In essence, experiential learning is often highly effective.

Integrating psychomotor activities provides potential for active, experiential learning.

I encourage others to explore using this AI bot prompt to experiment psychomotor taxonomy – I honestly had never heard of it until recently even though it has been around as pong ad Bloom’s taxonomy.

Applying it in your classroom can energise your students and ignite their curiosity through engaged learning.


2 responses to “Exploring the Psychomotor Taxonomy with an AI Bot”

  1. Swati avatar
    Swati

    Hi Matthew, It is great reading your posts and they are so insightful, could you please direct me to any website/blogs where I can find more information on developing these bots?

    Like

    1. Matthew Wemyss avatar
      Matthew Wemyss

      You can try Zapier. In the interfaces you can make you own chat bots. The prompts are designed to run in Chat GPT, but you can change them slightly to be chat bot directives for Zapier.

      Like

Leave a comment

Blog at WordPress.com.

Design a site like this with WordPress.com
Get started