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The debate over AI in education centers on its impact on learning. Critics say tools like ChatGPT may tempt students to skip the struggle, weakening their critical thinking. Some call for stronger AI literacy to curb overreliance and cheating. An approach suggested itself to me while I discussed this with my colleague, Diana Benner.
But what if we approached this issue from a different angle? Instead of resisting AI’s role, we could explore how it aligns with pedagogical frameworks like SOLO Taxonomy, which maps the progression of learning from surface to deep understanding and application.
SOLO Taxonomy: A Framework for Learning Growth
SOLO (Structure of Observed Learning Outcomes) Taxonomy describes learning across five stages. Here are my notes on the subject, poorly adapted from Geoff Petty’s Evidence-Based Teaching:
- Prestructural: The learner struggles with the task, providing irrelevant information and missing key points.
- Unistructural: The learner addresses the task from a single perspective, lacking a broader or integrated view.
- Multistructural: The learner explores multiple aspects of a topic but fails to connect or reconcile conflicts between them.
- Relational: The learner integrates perspectives, understands relationships, and resolves inconsistencies, forming a coherent view.
- Extended Abstract: The learner transcends the immediate context, applying principles to novel situations, weighing conflicting evidence, and creating new frameworks.
This progression aligns with the natural cognitive and metacognitive processes in disciplines like science, where learners hypothesize, test, analyze, and ultimately synthesize data into general principles. You can see this in action via the PRISM framework series.
In the meantime, this infographic incorporates an AI Connection into the SOLO Taxonomy:
Matching AI Tools with Learning Phases
John Hattie’s insights on learning phases—surface, deep, and transfer—are key to understanding how and when to incorporate AI. They serve as ways to broadly describe the levels of the SOLO Taxonomy. Let’s take a look at these:
- Surface Learning: At this phase, students need exposure to foundational knowledge. AI tools like Edulastic or Quizlet can provide scaffolded retrieval practice and basic quizzes to build their schema.
- Deep Learning: Here, students begin to see patterns and relationships. AI can facilitate discussions, prompt deeper questioning, or curate diverse perspectives on a topic. Tools like Google Keep, MS OneNote, markdown editors can assist students in structuring notes or synthesizing key ideas. Again, which digital tools you use (or not) should take into account student age and grade level. It’s even better to rely on handwritten notes to activate the brain. After all, “What the hand does, the mind remembers.”
- Transfer Learning: Students apply their understanding to solve problems or innovate. AI shines here, supporting complex tasks like generating alternative hypotheses or testing scenarios. Tools like ChatGPT can serve as a sparring partner for debating ideas or running simulations.
Classroom Strategies: AI Meets SOLO in Action
Wondering what this might look like in the classroom? Here are some suggestions that focus on the use of digital tools. Please note that paper-n-pencil activities can work as well, or better. AI tools are not always necessary and can be a distraction at the early levels of concept attainment, formation, and connection.
1. Prestructural and Unistructural Levels
- Activity: Introduce a topic using AI-generated questions for retrieval practice. Tools like Blooket or Knowt gamify this phase, making foundational knowledge acquisition engaging.
- Outcome: Students solidify basic concepts, building a base for deeper inquiry.
2. Multistructural Level
- Activity: Use AI tools to curate diverse viewpoints or data sets about a controversial topic. For instance, students might analyze AI-summarized articles to compare arguments.
- Outcome: Learners practice comparing perspectives, though they may struggle to resolve contradictions.
3. Relational Level
- Activity: Guide students in reconciling conflicting viewpoints with AI as a brainstorming assistant. Tools like ChatGPT can suggest frameworks or connections they may not have considered. For both this level and the next (i.e. Extended Abstract), you can take advantage of trained AI thought partners.
- Outcome: Students construct a coherent understanding and begin to apply it across contexts.
4. Extended Abstract Level
- Activity: Challenge students to design a solution to a real-world problem, with AI assisting in generating models, testing hypotheses, or refining presentations.
- Outcome: Learners demonstrate mastery by applying principles innovatively and defending their approach against scrutiny.
Addressing AI Overreliance
To prevent overreliance, educators should:
- Assess Learning Phases: Align AI use with the phase of learning, gradually reducing support as students progress.
- Teach Critical Evaluation: Empower students to question AI outputs, identifying biases or inaccuracies.
- Model Ethical Use: Show students how to integrate AI responsibly into their workflows, using it as a tool rather than a crutch.
Exploring SOLO and AI in the Context of the Writing Classroom
One of the questions I have going around in my mind? What does this look like in the writing workshop I facilitated at elementary and secondary grade levels? One possibility might be allowing AI in these ways, as well as keeping focus on key concepts. It might look like this:
SOLO Stage | Activity | AI Guidelines | Community Building |
---|---|---|---|
Prestructural Lacks understanding or prior knowledge. | – Quizzes to gauge understanding. | Allowed: Basic prompts or vocabulary lists. Focus On: Student explanations and connections to the topic. | – Sharing Circle: Discuss connections. |
Unistructural Single ideas with limited connections. | – Write thesis statements or summaries. | Allowed: None. Focus On: Peer and teacher feedback for developing independent writing skills. | – Talk Read, Talk Write: Group discussion before writing. |
Multistructural Multiple ideas but no integration. | – Collect and analyze evidence. | Allowed: None. Focus On: Independent research, analysis, and organizing ideas manually. | – Sharing Circle: Share sources and justify choices. |
Relational Ideas are connected into a coherent whole. | – Draft essays linking multiple arguments. | Allowed: AI for outline refinement after a full draft. Focus On: Building connections and arguments independently. | – Talk Read, Talk Write: Peer feedback on outlines. |
Extended Abstract Applies knowledge creatively or to novel situations. | – Apply writing to new scenarios. | Allowed: AI for brainstorming refinements or counterarguments post-draft. Focus On: Original ideas and creative problem-solving. | – Sharing Circle: Peer Q&A on solutions. |
Do you think this is too strict? I find myself agreeing with this perspective from educator Thomas Hummel:
A Parting Thought
AI gives teachers and students a chance to dive deep into their work. With tools like SOLO Taxonomy, we can push students to master skills and think for themselves.