Updated on
September 24, 2026
Metacognition in Science Education: A Teacher's Guide
Teaching metacognition in science: the POE strategy, inquiry-based learning and lab techniques that build scientific thinking from KS2 to KS4.
Metacognition in science education is learners directing their own scientific thinking: choosing a method, handling evidence and changing a conclusion. The predict-observe-explain routine carries it: a written prediction gives the class something to test and a gap to explain when the result differs.
Metacognition in science education means teaching learners to plan investigations, monitor evidence and evaluate conclusions as they work. It is not a reflection sheet added after the practical. It belongs within prediction, observation, explanation and revision.
Metacognition in science education means learners think about their own scientific thinking. They plan, monitor and review how they choose a method, test an explanation, handle evidence and change a conclusion during science lessons. The general term is explained in our metacognition and cognition explainer.
In a science lesson, this can mean asking learners to identify the variable they are controlling, pause when the data looks surprising, or explain why a conclusion has changed. The thinking is tied to the subject content, not separated from it.
Used well, these routines help learners cope with the uncertainty of scientific inquiry. They make practical work more purposeful. Learners predict, test, check the evidence and decide what their next explanation needs.
Key Takeaways
- Metacognition in science is planning, checking and reviewing: Learners plan an investigation, watch the evidence as it comes in and review what their conclusion rests on (Flavell, 1979).
- Predict, observe, explain makes thinking visible: A prediction written before the practical gives the class something to test, and a gap to explain when the result differs (White and Gunstone, 1992).
- Prior ideas have to be surfaced, not skipped: Learners hold their own models of forces, matter and heat; naming them first is what lets a new explanation replace them (Vosniadou and Brewer, 1992).
- Assess the thinking as well as the answer: Think-alouds, reflection journals and a four-question display show you where the reasoning went, not only whether the result was right (Schraw, 1998).
Metacognition In Science Education
Metacognition in the Science Classroom
Researchers found that science learning improved when teachers used specific strategies (White & Gunstone, 1989; Zohar, 2004; Hodson, 1998). Learners form hypotheses and draw on what they already know (Driver, 1983).
Klahr and Dunbar (1988) described scientific reasoning as a coordinated search across two spaces, hypotheses and experiments. Teachers give live feedback as learners check their progress (Black & Wiliam, 1998). Structured frameworks help learners weigh evidence and reflect (Schön, 1983).
When learners do not check their understanding, they often fall back on rote learning. Conscious reflection on learning is therefore key (White, 1998).
Science learners have to link their gut sense of things to scientific ideas. Conceptual change means rebuilding the ideas they came in with (Vosniadou, 1994; Chi, 2008). See also: How to develop metacognition.
Science learners have to rethink their ideas, unlike subjects where knowledge builds up in a straight line. When learning about forces, learners should challenge the common idea that heavier objects fall faster. Vosniadou and Brewer (1992) showed that children can hold mental models that differ from the scientific ones. Making those prior ideas explicit can support conceptual change.
This deep reflection helps learners understand how knowledge is made (Kuhn, 2005; Zimmerman, 2000). Learners who check their thinking are better at telling observation from inference. They spot the limits of what they know and look for evidence against their assumptions (Schraw, 1998).
Science teachers can use these strategies in class. Learners can keep journals on what they understand and what confuses them (Whitebread et al., 2009). Think-aloud protocols ask learners to say their reasoning out loud as they solve a problem (Veenman et al., 2006). This makes thinking visible to everyone.
Self-questioning helps learners with new science, say researchers (King, 1992; Rosenshine et al., 1996). Learners activate prior knowledge by asking "What do I know?" and "How does this connect?". Predicting outcomes and reflecting builds understanding (White & Gunstone, 1989; Baird & White, 1982).
Several studies back this up (Whitebread et al., 2009; Zohar & Barzilai, 2013). Being aware of their own thinking helps learners manage their learning (Flavell, 1979).
This self-regulation improves scientific reasoning and understanding (Kuhn, 2000; Zimmerman, 2002).
Predict-Observe-Explain (POE) Strategy
In a Predict-Observe-Explain sequence, learners first write down what they expect to happen and why. Next, they observe the outcome and compare it with their predictions. Then they explain any differences between what they predicted and what they observed (White & Gunstone, 1992). This process makes each learner's thinking visible.
Learners notice the gap between their prediction and what happened. This creates cognitive conflict, which drives learning. Learners then close the gap by saying clearly why their prediction was right or wrong (White & Gunstone, 1989).
Take density. Learners predict whether a can of diet cola and a can of regular cola will float or sink in water. Most predict both will sink because they are both heavy cans. When the diet cola floats and the regular one sinks, learners have to explain the surprise. That leads to a deeper grasp of density and dissolved substances.
POE helps learners use mistakes to improve understanding, making errors useful. When learners get predictions wrong, they can see gaps in knowledge (White & Gunstone, 1992). This approach makes prediction errors productive, not shameful.
How Scientific Inquiry Develops Metacognition
Scientific inquiry needs metacognition. During an experiment, learners have to check their own decisions as they go.
The display below turns that self-monitoring into four questions a class can ask of any claim: what is claimed, what the evidence is, what else could explain it, and what to check next. Print it, or draw it on the board for one investigation.
They can ask: Did I control variables well? Is the sample size big enough? Did observer bias affect results (Klahr, 2000)? What else explains findings (Zimmerman, 2000; Kuhn, 2005)?
Teachers can make this thinking explicit by talking about the reasoning behind each step of an inquiry. When designing an experiment, ask learners: "How do you know this is a fair test?" or "What assumptions are we making here?" These questions move attention from following the procedure to understanding the reasons for it.
When learners collect data, ask them to keep two kinds of record. They write down what they observe, and a short note on their thinking. For example: "Why did I decide to measure temperature every 30 seconds rather than every minute?" This helps them see that scientific choices need reasons.
Analysis gets sharper when learners question their own interpretations. "Am I seeing a pattern because it is really there, or because I expected to find it?" That healthy scepticism, turned on your own thinking, is the mark of scientific metacognition.
Using Concept Maps for Self-Reflection
This process can help learners understand and remember scientific information (Novak & Cañas, 2006). Research shows that concept mapping helps learners organise knowledge for themselves (Ausubel, 1968; Mintzes, Wandersee, & Novak, 2000). Concept maps also show how ideas connect, so learners can check what they know (Novak, 1990).
Concept mapping asks learners to recall ideas and sort them by importance. As they find the links, they can see gaps in their knowledge (Novak & Cañas, 2006). Use this with retrieval practice. Karpicke and Blunt (2011) found that retrieval practice beat concept mapping for long-term retention in their study. So concept maps should support organising and diagnosing, not replace recall.
For example, a concept map about photosynthesis can show that a learner knows the inputs and outputs. However, it may also show that they cannot explain the actual mechanism. The visual structure makes this gap clear, which can guide targeted learning.
Concept maps show learner progress. Looking at maps over time gives useful feedback on how their knowledge grows. Learners see their understanding grow more complex, as Novak and Gowin (1984) argued. Maps reveal many connections, showing subtler links between concepts (Kinchin, Hay, & Adams, 2000).
Concept mapping works best when learners make maps often. A first map shows what a learner already knows (Novak & Gowin, 1984). A revised map shows how understanding has grown. Learners should add questions to their maps about anything unclear (O'Donnell, Dansereau, & Hall, 2002).
Concept mapping helps learners compare and talk about ideas (Novak & Cañas, 2006). It also helps them spot gaps in their knowledge and find other ways to organise it.
For example, one learner may focus on the chemical processes in photosynthesis. Another may focus on the environment around the plant. These discussions build a richer picture of how ideas connect (Ausubel, 1968).
Structured reflection protocols can also improve self-assessment. Give learners guiding questions such as "Which connections surprised you?" or "What concepts still feel unclear?" Ask them to colour-code their maps, one colour for confident knowledge and another for uncertain areas. This makes their awareness easier to see. It also helps learners plan how to close gaps in their scientific thinking.
Lab Report Reflection Sections
Researchers (e.g., White, 1998; Baird & Northfield, 1992) show that reflection builds learning. Adding reflection to a lab report gives learners practice at thinking about their thinking. It helps them understand science concepts better (e.g., Schön, 1983).
This section should ask learners to reflect on their experimental design, data analysis, and conclusions. What challenges did they meet? What surprised them?
How could they improve the experiment next time? When learners critically analyse their own work, they strengthen the scientific process and build a growth mindset.
Reflection questions spark metacognition. For example: "What was hard?" or "What surprised you?" Teachers prompt reflection, which helps learners see gaps (Flavell, 1979). Learners then pick out the areas that need work (Nelson & Narens, 1990).
Good prompts include "What would you change about your method if you repeated this investigation?" Or "How confident are you in your conclusions, and what evidence supports that confidence?" These focused questions ask learners to judge their scientific thinking, not just describe what happened. A related problem is the feeling of knowing (FOK). Learners think they understand a scientific idea because it feels familiar, but cannot explain it or use it accurately in a test.
Try peer reflection: learners review each other's lab reports and give feedback on methods and results. This builds communication skills and awareness (Topping, 1998). Learners spot problems in others' work, which sharpens how they judge their own (Sadler & Good, 2006).
Connect reflection to science. Ask learners to link lab work to real world uses or research. "How would scientists fix our problems?" This question helps learners see uncertainty and changes as key to science (Schwartz et al., 2004). Learners will develop resilience and analysis skills (Bransford et al., 2000).
Thinking Aloud During Problem-Solving
Modelling metacognitive thinking is important if learners are to build these skills themselves. Teachers can show their own thinking by thinking aloud while they solve a science problem. That means saying out loud the questions they ask themselves, the strategies they weigh up, and the problems they get past.
For example, when reading a graph, a teacher can say: "I notice the line is curving upwards, which suggests a non-linear relationship. I wonder if this is exponential growth? Let's see if the data supports that hypothesis." Saying this out loud makes the teacher's thinking visible to learners.
Teachers can also model how to handle mistakes and uncertainties. "This result doesn't quite make sense. I must have made an error in my calculations. Let me go back and check my work." By demonstrating this type of self-correction, teachers show that mistakes are a natural part of the scientific process, not a sign of failure.
Learners can also gain from thinking aloud in pairs or small groups. It gives them a chance to put their own reasoning into words, hear other views, and get useful feedback from their peers.
Practice table · Build It · Science
What it looks like in practice
Nine routines teachers described on social media.
| Routine, as teachers describe it | What you would notice | What the evidence says |
|---|---|---|
| Predict, explain, then observe Learners write a prediction and a reason. Every idea goes on the board. Then they observe. The mismatch is the work.
|
Reasons on the board before the demo starts. A copper-and-ice surprise named out loud. UK secondary science, Let's Think / CASE. Teachers write predict, explain, observe. They do not write the acronym. | White and Gunstone (1992) published Predict Observe Explain with the observation in the middle. The live UK move puts the explanation first, so the observation has a written idea to correct. That sequence is a teacher report, not a trial of this classroom. |
| Teach, demo, hypothesise, then decide Fully teach the theory. Demo. Ask for a hypothesis. Do the practical only if it is still useful.
|
A hypothesis after the idea is taught, not instead of teaching. UK science teacher, reporting a CogSciSci slot. | Abrahams and Millar (2008, DOI 10.1080/09500690701749305): in 25 English secondary practicals, learners reliably did the right things with the kit and far less reliably thought with the intended ideas. A practical used to introduce the idea is the thing that paper found weak. |
| The Slow Practical Gather the class at a demo desk. Teach one step. Learners do only that step. Repeat. No method sheet to race through.
|
A queue at the demo desk, not twenty different paces. Questions on the idea at each step. UK science teacher and vendor. | Boxer set the steps out in Education in Chemistry (26 Aug 2020). Abrahams and Millar (2008) is the paper underneath the claim that kit-work does not by itself produce the idea. |
| Rushed required practicals objection Run the required practical at pace so the kit is done, then hope the written-paper items follow two years later.
|
A crowded lesson. Skills named as not honed. UK science lead practitioner. Nobody said “no time for metacognition” as a phrase. | Ofqual (March 2015): at least 15 percent of GCSE science marks are questions that draw on practical experience, in written papers, not a coursework mark. A rushed kit lesson is a high-cost way to miss those items. The time objection is this, not a missing reflection sheet. |
| Hinge item, then say the reason At ASE 2026, Ed Walsh is heard on hinge questions to make practical science more effective. Do not stop at a flashed letter. Ask for the next step or the reason.
|
A four-option item mid-practical. Then talk. The same month, a North London science teacher says he does not believe in the term and prefers check and consolidate. | EEF Improving Secondary Science (2018) recommendation 2c asks for metacognitive talk and dialogue. The report names diagnostic questions at hinge points, and BEST as a source of those questions. It does not use the phrase hinge question. Keep the item if it forces a reason. A letter on a board is retrieval. The reason is the consolidate half. |
| Concept cartoon, then one variable Show a concept cartoon. Learners pick a viewpoint and say why. Then change one variable to test the hypotheses they just gave.
|
Speech bubbles, then a small circuit test. Greater Manchester Year 6. The classroom photographs are not used. | EEF Improving Primary Science (2023), recommendation 2: encourage learners to explain their thinking, verbally or in writing. The report names concept cartoons as cartoon-style drawings that put forward a range of viewpoints, including everyday misunderstandings. |
| Predict, test, change your thinking (US) Ask a question. Write a prediction. Test it. Look at the evidence. Change the idea when the evidence tells you to.
|
An 8th grade lab script in those verbs. North Carolina charter. The named phrase Predict Observe Explain barely appears in US K-12 science posts. | This is the US variant of the UK predict-explain-observe move, in classroom English, not in White and Gunstone's acronym. Labelled United States. Not a UK diary. |
| Inquiry as the default (US) objection Run NGSS inquiry PD, or unguided Gizmos, on the grounds that science must be discovered.
|
A US science teacher arguing that novices lack the knowledge experts use. @DrLauraReames says Gizmos help with explicit instruction and scaffolding. | Abrahams and Millar (2008) found few English practicals were designed to link observables to ideas. That is a UK classroom study, not an NGSS trial. The objection is about mandated inquiry, not that reflection is only for honors classes. |
| Science probe, then recorrect (US) Open the week with a science probe. On Friday, revisit it. Learners correct the old idea, then tell a partner who they now agree with and why.
|
A board prompt: after the new learning, who do you agree with and why, write your new thinking. Texas 3rd grade. The photographed board is not used. | Page Keeley probes are NSTA products, so district PD that names her is vendor-adjacent. The classroom scene is the teacher's own account. EEF Improving Secondary Science (2018) cites BEST-style diagnostic questions for the same job in UK secondary: surface the everyday idea, then force a reason. |
The evidence includes Abrahams and Millar (2008), DOI 10.1080/09500690701749305; Ofqual’s 15 per cent rule from 3 March 2015; and EEF Improving Primary Science recommendation 2 from the 2023 guidance. These routines are teachers' own accounts, not trial evidence. @adamboxer1 is a classroom teacher and a vendor.
What it looks like in a Year 5 science lesson
Metacognition in primary science is a child saying what they expect before they look, and saying what they will check next after they have looked. Here is one lesson on plants and light, written as it runs, so you can see where the thinking moves sit.
Before the practical, the class sees two trays of cress: one grown on the windowsill, one grown in the dark of a cupboard. Every learner writes a prediction on a whiteboard and one reason: "The cupboard cress will be shorter because plants need light." Collect three reasons and put them on the board without saying which is right. That is the predict step, and the reason matters more than the prediction.
During the observation, learners record what they see and one note about a choice they made. Why did they measure the tallest shoot rather than the average? Why count leaves at all? Walk the room asking "How do you know?" and "What else could explain that?" Those two questions are on the wall display shown earlier. They are most of scientific metacognition at this age.
The explain step is where the surprise lands. The cupboard cress is often taller and yellow, not shorter, and half the class predicted the opposite. Do not rescue them.
Ask them to write one sentence that fits the evidence, then one thing they would check next. "Do the cupboard shoots stay taller if we leave them another week?" Learners who wrote the wrong prediction and can now say why have learned more than the ones who guessed right. That is the point of the routine, and it is worth saying to the class.
Close with a two-minute journal, not a worksheet. "What did I expect, what did I see, what will I check next time?" Three lines, in their own words. Read them before the next lesson and start from the misconception most of them still hold.
Two things not to do. Do not run this on a topic the class has never met, because a prediction with no knowledge behind it is a guess, and a guess teaches nothing about monitoring. And do not add a reflection prompt to every stage. One prediction, one choice noted and one next check is enough for nine and ten year olds; more than that and the science drowns.
Assessing Learner Metacognitive Development
Learners get better at solving science problems when they explain their reasoning. So assess their metacognition alongside the content.
Learning journals and questionnaires help teachers assess metacognition over time. Learners record how they solve problems and mark the topics that confuse them. They also judge how well they use scientific methods. These tools, with teacher feedback, show growth in thinking beyond content knowledge (Veenman et al., 2006; Flavell, 1979). For more on this topic, see Growth mindset metacognition.
Learners should often reflect on their thinking, (White, 1998). Ask them: "What strategy am I using?", (Carr et al, 1994).
Add prompts to lessons so you can check understanding with ease. Teachers can then give feedback and adapt teaching, (Flavell, 1979). This aids learners' metacognition alongside science knowledge.
Adapting Metacognitive Strategies for Diverse Learners
Metacognitive teaching adapts to each learner's needs (Flavell, 1979). Younger learners gain from visual tools (Novak, 1990). These tools help them map out problem-solving (Higgins et al., 2004). Learners with additional needs may need strategies broken into steps (Vygotsky, 1978). Model and guide them before they work alone (Rosenshine, 2012).
Sweller's (1988) cognitive load theory says that too much information can harm learning. Teachers can reduce this cognitive burden by using structured reflection templates. Unlike open questions, these templates can help learners who find it hard to focus. For instance, instead of "What did you think?" use prompts such as "What was your hypothesis?" (e.g. Flavell, 1979; Nelson, 1996).
Learners can show metacognition in many ways.
Giving choice helps all learners understand their thinking in science (Flavell, 1979).
Overcoming Implementation Challenges
Time pressure can squeeze metacognition out of science. Teachers often focus on content and miss chances for reflection. Flavell (1979) supports the wider need to help learners monitor their thinking. A two-minute journal is a classroom routine that makes this monitoring visible.
Learners may resist new ways of thinking if they expect to sit and listen. Gaps in knowledge can also get in the way of reflection. Scaffold metacognition with prompts, worked examples and shared language. Then pull the support back as learners gain subject knowledge and self-awareness.
Researchers suggest starting with small changes in class (Wiliam, 2011). Use simple questions to help learners explain how they are thinking (Black & Wiliam, 1998). As the class grows in confidence, add more complex strategies (Hattie, 2012).
Next Steps For Science Teachers
Learners think about how they learn, and gain both grasp and control. That builds scientific thinking for life.
POE, concept mapping and think-alouds make learner thinking visible (Veenman et al., 2006). These tactics deepen understanding and build problem-solving skills (Zohar & Dori, 2003). Learners become critical thinkers, ready for science and for more besides (White & Gunstone, 1992).
Start with simple reflections after activities. Learners name the strategies that helped them and the difficulties they faced.
Then bring in think-aloud protocols (Ericsson & Simon, 1993). Peer discussion can open up reasoning (King, 1993). Classroom displays of strategies remind learners to talk about their thinking.
Metacognition helps learners in more ways than test scores or lab work. It helps them feel more confident with new science, (Flavell, 1979). It also helps them change their ideas when new evidence appears, (Kuhn, 1999).
These skills support progress in science courses and future careers. Teaching metacognition helps learners succeed in school and become thoughtful citizens, (White, 1998).
Putting it into practice · Build It · Science
The questions teachers raise
Use the questions below to decide whether each science routine reveals a learner's reasoning or only completes the practical.
question
“Issue with required practicals is how rushed we are. Are we really giving opportunities to hone skills?”
What the replies and the evidence say. @Cazalineuk asked first, on social media: “What evidence do you have that the skills became embedded?” That is a challenge, not agreement. Sciantificnew then named the rush. A later post in the same thread, @Cazalineuk, says “I agree we need more time to embed skills but if the kids can't retain those skills they are not embedded.” Those two posts are not the same claim. Nobody answered with a longer reflection sheet. The move in this circle is the Slow Practical (Boxer, Education in Chemistry, 26 Aug 2020). Ofqual already scores practicals mainly through written papers, at least 15 percent of GCSE marks, so a rushed kit lesson misses those items too.
question
“if you want students to learn some kind of theoretical idea (e.g. Hooke's Law), then doing a practical is a bad way to get them to learn that.”
What the replies and the evidence say. In the same thread @MistypeaTam reports Bill Wilkinson’s CogSciSci slot: teach the theory, demo, hypothesise, then do the practical only if it is useful. Abrahams and Millar (2008) found the same shape in 25 English lessons: kit right, ideas less so. The disagreement is not whether practicals happen. It is what they are for.
question
“no, straight retrieval. i dont really believe in “hinge questions””
What the replies and the evidence say. The same month @cleverfiend posted from ASE Conference 2026: “Listening to one of my heroes Ed Walsh talking about using hinge questions to improve the effectiveness of practical science.” @theASE posted the Ed Walsh session. Boxer, asked separately, prefers check and consolidate so learners verbalise the new knowledge, not only flash a letter. Teachers split two ways: keep a four-option item if it forces a reason. A letter on a mini whiteboard is not the consolidate half.
question
“Science coursework. I know many will disagree but I think we should bring it back.”
What the replies and the evidence say. @Mr_Raichura writes: “Ofqual concluded that Controlled Assessments not only narrowed the curriculum but skewed marking.” A post-practical reflection sheet will not match how GCSE currently scores practicals. A short what-I-thought, what-I-saw, what-that-does-to-the-idea card, used in the Slow Practical cycle, would.
question
“The most common misconception in science education is that it must be inquiry-based.”
What the replies and the evidence say. In the same thread she writes: “...a student may not even be familiar with the vocab words. Expecting them to "discover" concepts without guidance sets set them up for failure.” @DrLauraReames says Gizmos help “if used in conjunction with explicit instruction and scaffolding.” Her 30 Nov 2024 blog, Why We Need to Rethink Inquiry-Based Learning, argues for about 80 percent explicit teaching first, then inquiry. Do not write this as an honors-only fight.
question
“I have over 80 students in my 6th grade SS/science class. We have to offer test corrections, so all of the tests are on paper.”
What the replies and the evidence say. The live US load is weekend marking when corrections are mandatory, not “exam wrappers”. Named exam-wrapper posts were a PubMed trivia bot about US nursing studies, not K-12 science teachers. If we ship a long wrapper into a US science page we will be talking past the classroom. A short where-I-lost-points line that does not add a second pile is the useful artefact.
@adamboxer1 is a classroom teacher and a vendor.
Limitations and Critiques
Metacognition has strong value in science education, but it is not a simple add-on to every lesson. One criticism is that generic prompts can overload novice learners during demanding practical work. Cognitive load research on the expertise reversal effect shows that guidance which helps beginners can stop helping as expertise grows. The reverse also happens: novices asked to reflect while handling too much new information can be overloaded (Chen, Kalyuga, and Sweller, 2015). In science lessons, learners may need secure knowledge of variables, apparatus and concepts before they can usefully monitor their strategy.
A second criticism is measurement. Many studies rely on self-report questionnaires. These often capture what learners believe about their learning, not how they regulate it during a task.
Veenman et al. (2006) argued that offline questionnaires can differ from online measures such as observation, think-aloud protocols and behavioural traces. This matters in science. A learner may report strong planning skills and still miss odd data during an experiment.
There are also cultural and methodological limits. Written reflection routines can favour confident, highly verbal learners. They can also misread the practical reasoning of EAL or neurodivergent learners as weak metacognition. Researchers have warned that metacognition is hard to separate from motivation, prior knowledge and classroom norms (Dinsmore, Alexander, and Loughlin, 2008).
New AI lab assistants add a further concern. If software watches for errors and picks the next step, learners may hand over parts of self-regulation they need to develop themselves (Lodge et al., 2023). Despite these limits, Flavell's core insight still holds. Science learners gain when they learn to plan, monitor and evaluate their thinking on real scientific problems.
Try the predict step in your next practical before anything else changes. Put the equipment on the front bench, give every learner a whiteboard, and ask for a prediction with a reason before anyone touches a thing. Collect three reasons and leave them on the board through the practical. The explain step will write itself, because the reasons are already there to argue with.
Frequently asked questions
Metacognition in science education
Metacognition means learners think about their own thinking during science (Veenman et al., 2006). They check their understanding and notice conflicts between ideas and evidence (White, 1998). When learners consciously reshape their mental models, they can infer, not just observe (Zohar, 2004).
Using The POE Strategy In Science Lessons
Teachers can use the Predict, Observe, Explain framework in three clear steps. First, learners state what they think will happen in an experiment and why. During the practical demonstration, they watch closely for differences between their prediction and reality. Finally, they explain any discrepancies, so they can reconcile their first beliefs with the new scientific evidence.
Benefits During Science Experiments
Teach learners metacognition to improve scientific reasoning and concept understanding (Zohar, 2006). Learners should monitor progress and question assumptions, rather than only follow steps (White, 1998). This approach reduces misconceptions and improves evidence evaluation (Kuhn, 2005).
Educational Research On Metacognition In Science
Learners must reshape their thinking in science, as intuitions often conflict with facts. Studies show epistemic cognition helps learners understand how science knowledge is built and checked (e.g., Kuhn, 2005). This understanding is vital for tackling misconceptions, like those about force or density (e.g., Vosniadou, 1994; Driver et al., 1994).
Common Mistakes In Scientific Inquiry
A common mistake is to let learners do experiments by following steps, without knowing why the method matters. Teachers need to ask why learners chose that approach, or how they know the test is fair. Without this metacognitive reflection, practical work may not change learners' underlying misconceptions.
References
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