Shyam Barr

Blog

 

PREFACE

This blog discusses topics that exist between the fields cognitive psychology and leadership, teaching and learning. Although I make connections between research and personal experience (my attempt at bridging the age-old ‘theory-practice’ gap), I write for a general audience. It is as Mihaly Csikszenmihalyi stated in the preface of his book FLOW:

“To take this step is somewhat dangerous, because as soon as one strays from the stylised constraints of academic prose, it is easy to become careless or overly enthusiastic about such a topic” (p. xi)

To avoid carelessness, I will endeavour to include references to journal articles, books and alike (as commonly expected in academic writing), but not at the expense of accessibility and ease of reading. This will be a delicate balance and one I will endeavour to achieve.

To end, I chose the word ‘discusses’ in the first sentence of this preface, to highlight that although the blog articles themselves are very much a dialogue between myself and what I read, I encourage you to share your comments and questions, so that we may start a more authentic discussion. 

 
 

Metacognitive Accuracy and the Self-Regulated Learner: What Teachers Can Do

Confidence is not competence 

— But try telling that to a student who thinks they’ve got it covered.

A student self-assures that they’ve “got it,” that they understand the material, yet how they manage their learning journey and the work they produce tells a different story. It leaves you wondering: how do I help this learner see what I see? This mismatch between a student’s confidence and their actual performance is more than a frustrating moment—it’s a metacognitive blind spot. And it matters because accurate self-perception is foundational to self-regulated learning. If students can't judge their capability for learning or managing a learning process, they can’t adjust their strategies, effort, or focus. In this blog, I’ll unpack why metacognitive accuracy is essential, how it influences students’ ability to self-regulate, and what you can do to support it.

Metacognitive accuracy, also known as metacognitive calibration, calibration accuracy or judgment accuracy, refers to how well learners can assess their understanding or performance (Immundo et al., 2025; Jang et al., 2020). Indeed, metacognitive accuracy is a critical skill for making effective study decisions and becoming a self-regulated learner. When students overestimate what they know, they may stop studying too soon; when they underestimate, they might waste time reviewing already-mastered material. Accurate self-judgments enable learners to allocate effort wisely and adjust strategies for deeper, more effective learning.

At last year’s University of Queensland’s Learning Lab Symposium (Nov, 2024), I had the pleasure of hearing Professor Paul Dux present findings from the Horizon Project — highlighting why metacognitive accuracy matters so deeply for students’ academic wellbeing. In this research, students self-rated their capability to monitor and control their learning, and then completed an objective measurement tool for their strategic knowledge. Findings revealed three distinct metacognitive profiles (refer Figure 1).

Figure 1 (Graph from presentation slides - Dux, 2024) reports the three metacognitive profiles: Overconfident (high perceived monitoring and control, low actual strategy knowledge), Underconfident (moderate perceived monitoring and control, high strategy knowledge), and Low Functioning (low perceived monitoring and control and low strategy knowledge). Crucially, students in the overconfident category—those who believed they were managing their learning well but lacked the strategic know-how—were shown to struggle the most with academic wellbeing. As Professor Dux shared, metacognitive ability was the strongest predictor of academic well-being, a construct that includes academic achievement, academic stress, and academic satisfaction (Shek & Chai, 2020). These findings reinforce the risks of poor metacognitive accuracy: when students overestimate their abilities, they may underprepare, misallocate effort, and experience increased stress and dissatisfaction. Helping students improve the accuracy of their self-monitoring is not just a cognitive skill—it's a well-being imperative.

To improve students’ metacognitive accuracy, you can:

Encourage overt retrieval of knowledge.

Immundo et al. (2025) explored how different flashcard-based learning conditions influence students’ metacognitive accuracy—specifically their ability to judge their own learning accurately. Across three experiments with undergraduate students, participants either used flashcards individually or with a partner to learn vocabulary-definition pairs and then made predictions about their future test performance (judgments of learning). While actual recall performance was similar across conditions, those who studied with a partner consistently demonstrated greater metacognitive accuracy, showing less overconfidence and more accurate predictions of their test outcomes. The researchers found that this improved calibration was likely due to the use of overt retrieval in paired learning, which encouraged deeper engagement and reduced illusions of knowing. These findings highlight the value of collaborative retrieval practice for fostering more accurate self-assessment, a critical component of effective self-regulated learning.

Incorporate opportunities for judgments of learning.

Studies have also shown that integrating opportunities for students to predict, test and adjust their judgments can improve metacognitive accuracy. For example, Jang et al. (2020) examined the relationship between students’ trait-level metacognitive ability and their metacognitive accuracy, specifically the accuracy of their judgments of learning. Across three study-test cycles involving concrete and abstract word pairs, students predicted their likelihood of recall and then completed a memory test. The study found that students with higher metacognitive awareness were more accurate in their predictions, but that this relationship was indirect— metacognitive accuracy improved most when students had prior opportunities to test and adjust their judgments. These findings suggest that while metacognitive ability supports early monitoring, experience-based feedback is key to refining metacognitive accuracy over time.

Based on the Jang et al (2020) study, you CAN:

  1. Get students to make predictions about their performance before a quiz or retrieval practice activity. This could be a binary judgement of learning such as “Will I remember this - yes or no?” Or “Do I know this well enough to explain it without notes?”

  2. Teach students about the difference between feeling of knowing and actual knowing. 

    1. For example, students often rely on unhelpful cues (like how easy something feels when reading) rather than valid cues (like successful retrieval) when making judgements of learning (linked to Koriat’s, 1997 cue-utilzation framework). To help them, try sharing examples of common illusions of learning (e.g., “It feels familiar, so I must know it”) and contrast them with strategies like self-testing and explaining ideas aloud, which provides more accurate feedback.

  3. Invite the student to engage in a low-stakes quiz or retrieval practice.

  4. Then get them to compare their predictions to their results. You can also include some metacognitive prompts to support this process:

    1. “Was your performance what you expected?”

    2. “What strategy did you use and how well did it work?”

    3. “What will you do differently next time?”

Improving metacognitive accuracy isn’t about eliminating student confidence—it’s about aligning that confidence with reality. When students learn to judge their learning accurately, they become better equipped to regulate it. Whether it’s through retrieval practice, binary predictions, or reflective prompts, the classroom can become a space where students not only learn more, but learn how to learn better. As the research shows, supporting students to see themselves clearly isn’t just a learning goal—it’s a wellbeing one too.

References:

Imundo, M.N., Zung, I., Whatley, M.C. et al. When two learners are better than one: using flashcards with a partner improves metacognitive accuracy. Metacognition Learning 20, 3 (2025). https://doi.org/10.1007/s11409-024-09406-w

Jang, Y., Lee, H., Kim, Y. et al. The Relationship between Metacognitive Ability and Metacognitive Accuracy. Metacognition Learning 15, 411–434 (2020). https://doi.org/10.1007/s11409-020-09232-w

Koriat, A. (1997). Monitoring one's own knowledge during study: A cue-utilization approach to judgments of learning. Journal of Experimental Psychology: General, 126(4), 349–370. https://doi.org/10.1037/0096-3445.126.4.349

Shyam Barr