By Jacinta Browning, Assessment & Analytics Consultant (EA)
Listening to a recent podcast by Dr Selina Fisk prompted me to pause and reflect, not just on data itself, but on how we engage with it. It made me consider how schools might be using data they collect from tools like Essential Assessment and whether that data is helping them act, or simply react.
In education, we’re surrounded by data. But how often do we use it to support deep thinking, challenge assumptions, or prompt better questions? Too often, data becomes a mirror for what we already believe, especially when we’re under pressure to respond quickly.
In a world that rewards speed, it’s tempting to respond to data immediately: to act quickly, to solve, to move. But what if slowing down is actually the smartest thing we can do?
When we engage with data, whether as school leaders, educators, or system planners, we’re not just crunching numbers. We’re interpreting patterns, making meaning, and deciding what matters next. And that process, if we’re honest, is deeply human. It’s influenced by emotion, prior experience, and bias. This is where AI can become not a threat, but a powerful partner.
Why Fast Thinking Isn’t Always Smart Thinking
Psychologist Daniel Kahneman’s concept of Thinking, Fast and Slow helps us understand why our brain isn’t always our best decision-making tool. Our System 1 thinking is fast, automatic, and instinctive. It likes to leap to conclusions. It offers explanations quickly, even when they’re flawed or incomplete.
Our System 2 thinking is deliberate and reflective, is slower to engage and takes real effort to activate.
In education, System 1 thinking plays out through confirmation bias. We may interpret data in ways that affirm what we already believe: about our students, our programs, or even ourselves. We might glance at a graph and say, “I knew that already,” without probing further. By inviting reflection instead of reaction, AI can help us turn data into insight, and insight into impact.
Where Generative AI Comes In
Used intentionally, generative AI can help break through our cognitive shortcuts. It slows us down just enough to pause, to see new patterns, and to offer alternative perspectives. It helps us think bigger, not just faster.
Whether it’s producing a first-draft summary or drawing attention to trends we may have overlooked, AI offers a neutral lens, free from ego or emotion. It doesn’t replace the wisdom of human judgment, but it nudges us toward our System 2 brain: analytical, purposeful, curious.
Watch Out for Action Bias
A common pitfall in working with data is what psychologists call action bias, our tendency to do something, anything, rather than sit with ambiguity. But taking action without insight can lead to ineffective or misaligned strategies. When we rush in, we risk mistaking motion for progress.
Pausing to reflect, explore multiple interpretations, and consult a range of evidence isn’t inaction. It’s wise leadership.
Building a Stronger Data Narrative
Put simply, a data narrative is the story your evidence tells, when it’s organised, examined, and reflected on with purpose. Every effective data narrative begins with a baseline. But it doesn’t stop there. A data narrative is more than a report, it’s a structured, reflective journey that:
- Clarifies the ‘why’ behind the data
- Supports next-step planning
- Unpacks trends and inconsistencies
- Highlights what we value by what we choose to collect
- Encourages intentionality around how we measure growth
As Tom Davenport reminds us in his book on the subject, data should make our work easier, not harder. While setup takes time, the clarity it brings is invaluable. A well-structured data narrative can provide an accurate snapshot that supports professional judgment and forward planning. It clears the fog and helps us ask better questions, not just get quicker answers.
Final Thought
The best decisions in education aren’t always the fastest. With AI as a companion tool, not a replacement, we have an opportunity to slow down, confront bias, and engage deeply with our data. When we pause to understand rather than react, we build a culture of reflection, precision, and progress.
References
- Fisk, S. (2025). Episode 30: Using AI for data storytelling [Audio podcast episode]. The Educator’s Data Podcast. Retrieved from [insert podcast URL]
- Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
- Davenport, T. H. (2014). Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press.
- Prodigy Education. (2025). Australian Teacher Wellbeing Survey Report. The Educator Online. Retrieved from https://www.theeducatoronline.com/k12/news/teachers-say-2025-is-their-most-stressful-year-yet/287211
- Netolicky, D. (2025). The effects of AI on human cognition and connection. The Eduflaneuse. Retrieved from https://theeduflaneuse.com/2025/06/22/ai-human-cognition-connection/
