Acquire, Analyze, Act (AAA)
A process to support feedback
The Acquire, Analyze, Act process (below) is a flexible process when engaging in feedback, as it can incorporate AI at any stage; making it a different approach than the other processes shared in this book up until this point.
This ongoing loop, provides structure for creating feedback processes with specific, actionable steps. And the great thing is that AI could serve as a learning partner to construct meaning. The three steps are an attempt to summarize the best practices mentioned earlier in this book.
Acquire. We begin by intentionally seeking feedback.
Analyze. We pause to make sense of the information, verify its accuracy, identify what is actionable, and construct coherent meaning with the people or AI we are working with.
Act. We implement the feedback, then engage in metacognition before moving forward by reflecting on what was helpful, what shifted our thinking, and how the process itself could be more effective, informing the next cycle.
AI does not need to be integrated into all of this process. You might choose to incorporate it into one single step, two, all three, or none at all. It’s up to you where AI could be helpful.
Acquire
With a feedback-seeking mentality, consider what you want to learn.
Set clear goals: Decide about what you want to learn, and define success using criteria that matter to you. It could be a personal goal, a learning objective from a class, or another source.
Develop feedback-seeking behavior: Expect revision, regulate emotions, and build trusting environments where critique is welcome.
Seek diverse perspectives: Collect timely feedback from multiple sources (AI, peers, teachers, self).
Time it strategically: Seek input early and often, when you can still implement meaningful changes.
How could AI be used in this step of the process?
Idea 1: Create a bot in which the learning objectives are entered by the student or teacher. The students share their work and discuss the desired outcome. In this way, AI acts as a confidant in a safe environment in which it’s safe to take risks and explore unknown ideas. Learners could then turn to other sources like peers, teacher, experts, themselves as additional sources of data.
Idea 2: Use a bot and discuss how one might cultivate a feedback-seeking mindset. What dispositions should I have before starting the feedback process?
Analyze
Intentionally pause and construct knowledge by examining the data
Interpret: Look for patterns, agreements, and contradictions across feedback.
Unpack: Pursue “why?” and “show me?” until the data is crystal-clear.
Identify takeaways: Select the most impactful actionable insights.
How could AI be used in this step?
Idea 1: Upload a summary of feedback, annotated work, etc. and ask for a summary of and actionable next steps to a large language model like Chat GPT. Have a conversation with the bot about what the next steps might be.
Idea 2: This could be paired with the first idea. Have an ongoing conversation to more deeply understand why certain data might be present during the Acquire step.
Act
Take time to implement your takeaways
Iterate promptly: Apply insights while they’re fresh and check revisions against original objectives.
Repeat as necessary: Return to seeking feedback and continue the cycle until your goals are achieved.
Reflect: Consider how the feedback process helped your thinking and encouraged growth. What would be helpful to seek feedback on during the next cycle?
How could AI be used in this step?
Idea 1: Students could take action in unlimited ways. For example, they might use AI to vibe code (when we code with the support of AI) and ask it to support our vision based on the feedback we received.
Idea 2: AI could act as a thought partner; students chat with the bot about the process of learning. The students could discuss the process itself, whether they might need another cycle and what the goal they could collaboratively set could be.