Unlocking High-Quality Teaching

Cognitive engagement refers to the mental state in which learners put forth a sufficient and sustained effort to persist in understanding a complex idea or solving challenging, unstructured problems. Its particular value lies in supporting students to develop a deep understanding of content and an ability to apply this flexibly and adaptively to new situations or challenges (Blumenfeld, Kempler and Krajcik, 2005[1]; Pellegrino and Hilton, 2012[2]).

Cognitive engagement is situational in classrooms, which means it is not simply automatic, but rather occurs in a particular situation and context. Teachers can strive to create these situations in which learners can become cognitively engaged by drawing upon the core practices. These are united by creating challenge, sparking interest and curiosity, and connecting to students’ prior skills and knowledge.

Engaging students in higher-order thinking is an important feature of instructional quality (Creemers and Kyriakides, 2006[3]; Creemers and Kyriakides, 2013[4]; Dunlosky et al., 2013[5]; Hattie, 2012[6]). Research in mathematics (Baumert et al., 2010[7]; Lipowsky et al., 2009[8]; Li et al., 2021[9]) and science (Keller, Neumann and Fischer, 2017[10]; Fauth et al., 2019[11]) has consistently shown that cognitive activation is positively associated with student achievement.

Research also suggests that there are notable benefits to non-cognitive outcomes such as student motivation and self-esteem (Fredricks, Blumenfeld and Paris, 2004[12]). Furthermore, when students are cognitively engaged, they also tend to be more interested (Fauth et al., 2014[13]).

Fostering students’ cognitive engagement in the classroom is a fluid and ongoing process. After all, what is engaging might be different to every student and may change as students learn and progress. This means there needs to be sustained and careful attention to how cognitive engagement is facilitated in a classroom. To foster cognitive engagement, teachers can make use of the following practices:

• ensuring appropriate levels of challenge

• meaningful context and real-world connections

• facilitating first-hand experiences

• working with multiple approaches and representations

• metacognition.

All these practices are important and inter-connected, and teachers might draw upon them simultaneously. Ensuring appropriate levels of challenge is a practice that tends to be present throughout the teaching and learning process with teachers carefully attending to the cognitive load that learning opportunities present and their alignment with students’ prior learning. Teachers may draw on practices such as providing meaningful contexts and real-world connections, working with multiple approaches and representations, and facilitating first-hand experiences, depending on the learning goal. They also selectively create opportunities for students to think metacognitively, enabling them to self-evaluate their learning progress and self-direct it forward, sometimes extending beyond a particular activity, task or lesson.

Each of these practices are outlined one-by-one below. Each section presents a definition for the practice and other associated terms on how it might also be referred to; key research findings on its impact on student outcomes; main implementation challenges identified by researchers and schools in designing the structure of the activity, task or content, role of students and role of teachers. Then, it looks into the complexity for teachers to understand whether students are cognitively engaged in the classroom. The final section builds on schools’ insights to provide an indication about the complexities of implementation and provides reflection questions for instructional and school leaders.

The appropriate level of challenge relates to the opportunities for students to regularly engage in work that is demanding, thoughtful and complex. This is aligned to learning goals and informed by the subject matter as to how best to challenge students. It is also aligned to students’ needs, including where they are in their learning, in order to ensure that all students, and not just some, are activated by hard, challenging work and being pushed forward in their thinking.

Associated Terms: Demanding subject matter; Thinking critically; Intellectual challenge; Concept development; Cognitive activation; Ambitious teaching for all; High expectations

Research on features of effective teaching has consistently identified a correlation between students being engaged in rich learning opportunities that activate hard thinking and student learning outcomes (Coe et al., 2020[16]; Klieme, 2006[17]; Neumann, Kauertz and Fischer, 2012[18]). Similarly, Chi and Wylie (2014[19]), whose work has focused on the synthesis of large bodies of research, including laboratory and classroom studies, on associations between learning outcomes and different teaching practices and classroom features, have argued that as students become more cognitively engaged, their understanding of the content deepens.

These arguments are supported by empirical studies too, such as recent work on the sequencing and scaffolding of challenging tasks when learning programming, which found benefits to student learning and self-reported engagement (Ma et al., 2023[20]), and work on immersing students in a state of ‘flow’ – where the use of high degrees of skills in challenging tasks results in deep concentration (Hamari et al., 2016[21]; Hsieh, Lin and Hou, 2016[22]).

The level of challenge needs to be carefully pitched; too easy for students and it is not a challenge, yet too hard and it is not achievable and potentially demotivating. To get the level of challenge right, teachers need to ensure there are appropriate entry points to the task alongside a clear progression in cognitive demands (McNeill et al., 2006[23]). This also demands careful consideration of students prior knowledge to build new connections (Coe et al., 2020, p. 33[16]) and progress to greater abstractions (Braithwaite and Goldstone, 2015[24]).

Insights from schools:

To help students get going, it can be helpful to sometimes ‘thinly slice’ complex challenges into multiple smaller steps that provide incremental challenge, so students experience a sense of success, rather than frustration, early on.

Consider students starting certain challenges working in groups, so they can use each other as learning resources if they are struggling and so they feel less daunted by the scale of the challenge. They can then progress to a trying a similar challenge independently.

Ensure that there is a quick route to increasing the level of challenge when designing a task, such as by having multiple correct answers that can be investigated or an open-ended aspect where students can seek out new applications of the challenge, so you can readily adapt.

Numerous subject-specific studies have explored what engaging students in challenging work may look like. Whilst there is a degree of subject-specificity, some features are reasonably consistent such as critically and creatively engaging in analytical work, particularly involving using evidence and justifications. For instance, in mathematics, particularly demanding tasks include engaging in analyses and creation or evaluation work that requires thoughtfulness (Mishra and Koehler, 2006[25]; Nunokawa, 2010[26]; Lipowsky et al., 2009[8]). Similarly, in literature, a common theme has been the close analysis of texts to identify and evaluate patterns, connections, and contradictions with evidence (Beers and Probst, 2012[27]; Beers and Probst, 2016[28]) while in the social sciences and history, identifying and evaluating evidence has been argued as central too (Grant, Lee and Swan, 2017[29]; Monte-Sano, De La Paz and Felton, 2014[30]).

Insights from schools:

Build in a routine of students providing justifications with supporting evidence, whether it is with follow-up questions that ask “why?” of students or “justification boxes” in written activities. Asking students to solve an equation is distinct from additionally asking them to explain why the method used is the most effective to solve it.

Provide a clear model or scaffold of how to evaluate evidence and accordingly build an argument, so students will know what to aim for. Indeed, it could be that this can be aligned with colleagues to provide a model or scaffold for handling evidence that can be used by students consistently across subjects.

Challenge students to give constructive feedback to their peers on their use of evidence during tasks, which both trains students to systematically analyse a project using a rubric, and also emphasises the need for collaboration and feedback to refine one’s thinking.

A key feature of challenging work, such as problem-solving, is that it demands sustained thinking from students (Mayer, 1990[31]). This means students need to struggle and be stretched over a prolonged period. But what counts as challenging is subjective to every student and ever evolving in the classroom. This is, ironically, challenging for the teacher. Teachers need to balance the amount of guidance and support they provide in a flexible and adaptive way.

Insights from schools:

Monitor students’ work and thinking in an ongoing way, so that that there is plenty of information to draw upon when judging if more or less guidance is needed.

Provide feedback on the processes and attempts, even if wrong, when tackling complex challenges to encourage students to sustain their efforts and make them still feel a sense of success even if a problem isn’t solved.

Provide time for students to pose their questions to each other first before intervening as a teacher, say by collecting questions or challenges from individual students or groups, and asking the class “who can help their peers overcome this obstacle?”

Use prompts that provide directions rather than simply the solutions. For instance, encourage students to look for patterns or “similarities and differences”, both when they are struggling or in need of progression, or to summarise what they do know about a topic if they are looking for an entry point.

Students’ learning is tied to its broader context and applications, including contexts that students find meaningful, important, and valuable. Teachers may create clear and detailed connections between what is being learned in the classroom to something outside of the lesson. This may use a concrete real-life example, a relevant problem, or students’ personal experiences. In each case, these decisions are informed by the teacher’s consideration of students’ cultures and backgrounds.

Associated Terms: Authentic learning; Application; Purpose; Problem- or project-based learning; Inquiry-based learning

A recent systematic review of approaches to primary science teaching identified that context-based and cross-curricular/interdisciplinary approaches can have a positive effect on pupil attainment and on attitudes (Bennett et al., 2023[32]). Whilst the review considered a small sample of studies (six), all were quasi-experimental or randomised control trials. The majority were rated as of moderate quality and spanned several different countries. Specifically, the review included four studies specifically related to context-based approaches, defined as those in which scientific concepts and process skills are applied in real-life contexts relevant to pupils from diverse backgrounds. That said, there can be variation in how ‘context’ is interpreted with it being a broad term, meaning that critical, sensitive engagement with the evidence is needed by teachers and school leaders. Similar findings emerge at the secondary level too; a review of secondary science foregrounds the importance of building on students’ preconceptions and ideas (Nunes et al., 2017[33]): the ideas about the world that students already have and bring to the classroom. Conversely, research on the use of ‘not-real’ examples, for instance using fictional places in geography or fictional historical events, in subject content may limit the usefulness of the knowledge students learn, as well as their curiosity and inquiry (Puttick, 2017[34]).

Elsewhere, the use of meaningful, complex real-world problems or authentic inquiry questions has also been a notable feature of interventions on project-based learning approaches. This body of research provides some indirect evidence that when students engage in building their understanding by working with and using ideas in real-world contexts this can be impactful for their learning (National Research Council, 2007[35]). For instance, there is evidence from large-scale randomised control trials in the US suggesting that contextualised project-based learning in science can be impactful; one trial with primary students suggested it can contribute to student learning gains (Krajcik et al., 2023[36]) and another at the secondary-level found effects on students’ motivation to learn (Schneider et al., 2022[37]). As noted, this means that empirical evidence is primarily indirect in this body of research, with it rare that studies isolate the specific effects of contextualised learning. Rather, the use of meaningful context and real-world connections is often one feature of several combined approaches (Sweller et al., 2023[38]). Similarly, the consistency of these findings has also been mixed, with a need for further rigorous research still (Menzies et al., 2016[39]).

A diversity of examples and experiences can help students understand how ideas, knowledge or skills apply to different situations. It can also support equity and inclusion by ensuring that all students have opportunities to engage in learning that is meaningful to them, which has been an area of much research recently in different international contexts in relation to historically under-resourced or disadvantaged communities (Sánchez Tapia, 2020[40]). Empirical studies have suggested that contextualising learning in a culturally relevant way may support learning gains for the target students (Krajcik, Miller and Chen, 2020[41]; Sánchez Tapia, Krajcik and Reiser, 2017[42]).

Insights from schools:

Ensure representation when choosing content and topics, for instance books, primary sources, or real-life figures, so that students can see themselves in the content.

Enlarge students’ thinking by introducing students to cultures and backgrounds other than their own, if possible building upon the diversity in the classroom.

Encourage students to think about whose story or perspective is missing, and how this could add additional value to their understanding.

One means of ensuring that learning is authentic and engaging for students is to give them a role in shaping the types of connections that are made and the direction that their learning takes. This use of student agency can help to ensure that learning aligns to their interests and encourage their cognitive investment (Deci and Ryan, 2016[43]; Fu, Liu and Zhang, 2023[44]; Parker et al., 2021[45]). Teachers balance student agency with their own supervision, to monitor alignment with learning goals and prior learning, and help manage potential risks (OECD, 2024[46]).

Insights from schools:

Use student voice to design questions that students want to investigate and answer during a topic. They can come up with individual questions about things they care about in the world, or find peers with similar questions to develop a shared focus to investigate.

Give students responsibility to work for real purposes and real audiences – such as on local issues – where they can have real-world impact by sharing the outcomes of their work with different stakeholders.

Encourage students to pursue their interests and curiosity outside of the classroom, such as by challenging them to seek out additional resources or perspectives that can then be shared with their peers.

If teachers are to be able to connect students’ learning to their lives and the real-world, it is important that they understand students’ starting points. Connecting the subject matter with students’ initial ideas about the world by using relevant and accessible real-world examples has scope for generating rich cognitive engagement. More broadly, it is important that new learning is connected to prior knowledge to reinforce and deepen it (Rogers and Thomas, 2022[47]).

Insights from schools:

Ask students at the beginning of a new topic about their backgrounds, perspectives and how they relate personally to the subject at hand in order to be able to build connections with their learning.

Choose the right balance of open- or closed-ended opportunities; open-ended opportunities, such as essays or one-to-one meetings, take more time but let students express themselves in detail in their own words, whilst close-ended opportunities like pre-surveys are more direct and efficient but lack some detail.

Consider creating ongoing opportunities for understanding who students are, such as talking circles at the start of certain days to share personal stories and build connections, because both students’ interests and real-world connections may evolve over time.

First-hand experiences refers to individuals learning through experiencing, seeing, feeling, and modelling phenomena that occur in the world. However, it is not just students observing what happens: first-hand experiences should involve students making sense of the phenomena. They should have the opportunity to explore questions like why does a phenomenon occur, or can they predict when the phenomenon will occur again?

Associated Terms: Problem- or project-based learning; Inquiry-based learning; Authentic learning; Experiential learning; Participatory learning; Play-based learning; Hands-on learning; Application

First-hand experiences have been investigated in different fields of research. One is the aforementioned body of research on the use of inquiry-based activities, particularly in science education. Some research has suggested that instructional approaches focusing on investigations and first-hand experiences (e.g. conducting investigations and using data to build models and explanations), integrated with content learning, are more effective and stimulate greater student interest in science compared to when students follow predefined procedures (e.g. memorisation and demonstration activities) (National Research Council, 2007[35]). A meta-analysis of experimental and quasi-experimental studies suggests that inquiry activities which combine procedural, epistemic, and social elements, can have a significant positive impact on student learning (Furtak et al., 2012[48]). However, it is worth noting that some questions have been raised regarding studies showing more mixed results and more work with the use of rigorous design features still being needed internationally (Menzies et al., 2016[39]).

A second field of research is that related to the concept of ‘play’. There has been a notable amount of research in this field with younger students, both at the primary and early years levels. However, the evidence base is diffuse, with a strong conceptual basis from research in developmental theory on the use of guided play (Zosh et al., 2017[49]). It is only more recently that a more coherent, systematic evidence base has started to emerge (Baron et al., 2017[50]; Whitebread et al., 2019[51]), though demands further examination. A recent meta-analysis on lower primary students (ages 1 to 8) examining the use of ‘guided play’ (constituted by a clear learning goal, a degree of student agency, and flexible teacher support, with students) found that it had a greater positive effect compared to direct instruction on executive function and mathematics (Skene et al., 2022[52]). As mentioned, research is heavily concentrated among primary age students or younger.

A particularly important debate relates to when first-hand experiences may be most appropriate. There is reasonable consensus on the importance of ensuring that students have sufficient prior knowledge for engaging in more student-led first-hand experiences such as inquiry approaches (de Jong et al., 2023[53]; Sweller et al., 2023[38]). Thus, it is only with sufficient mastery of the knowledge or skills underpinning a first-hand experience that a student can engage with more inquiry-orientated work. Even then, the role of teacher guidance remains important – as set out further below. In particular, there is a need to further examine how variation may exist across different age groups, as the question of prior knowledge is especially relevant for younger students which in turn raises the question of their ability to engage effectively in certain first-hand experiences.

It is important that first-hand experiences have a clear purpose that is focused on the learning goals. Otherwise, first-hand experiences may become a distraction and add unnecessary cognitive load (Kolb, 2014[54]; Willingham, 2009[55]). Again, this connects to the need to ensure that students have the right type of prior knowledge and skills for engaging in any processes where they must explore a topic and try to make sense of it or solve a particular question (de Jong et al., 2023[53]; Sweller et al., 2023[38]). Experiences need to align to students’ prior knowledge and skills so they can successfully apply them and that all students can access the experience.

Insights from schools:

Start with a clear articulation of the ‘why’ behind the experience that links together what students are learning with the relevance of the experience to give authenticity and meaning to it, as well as any keys skills or knowledge they have previously worked on.

Activate prior knowledge on key concepts or ideas first, such as through recap activities, so that students retrieve previous learning and are ready to use it before they start engaging in a new inquiry or exploration.

Keep coming back to the goals regularly during the experience, by embedding student reflection in a regular, sustained manner so they link back to the ‘why’ that underlies an experience.

Wrap up experiences with students explaining clearly what they have learnt from the experience in relation to the learning goal, such as by creating individually or collectively a mind-map of their learning.

Opportunities for students to play or engage in exploring and experimenting with ideas may support their ability to think in creative and iterative ways (Zosh et al., 2017[49]). There are many forms of play-based learning that are informed by the age of students, and there can be varying degrees of teacher involvement. They are typically united by a focus on students having agency to be creative and iterative in their thinking, around an underlying meaningful context.

Insights from schools:

Ensure students have opportunities to experiment with trying out different ideas, such as when modelling certain phenomena or using certain research methods, as these can be chances to reflect, think iteratively, and refine their inquiry approaches.

Give students the agency to choose how they communicate outcomes from an experience in new, original ways, for instance how they present the outcomes from an inquiry (e.g. presentations, posters, videos).

Draw upon relevant forms of gamification, for example by inserting activities like word clouds, multiple choice quizzes, or fill in the blanks, that may be particularly relevant for practising specific knowledge, or more open-ended gamification like role-play that demands more creativity.

In recent years, the important role of the teacher as a guide and facilitator for activities relating to inquiry has become increasingly clear. Evidence suggests that teacher guidance through an inquiry process has an additional positive effect, a result that has been reasonably consistent across various meta-analyses of inquiry-, problem- and project-based approaches (Lazonder and Harmsen, 2016[56]; Belland et al., 2017[57]). This suggests that first-hand experiences that have high levels of student agency still demand careful facilitation and support from the teacher.

Insights from schools:

Provide students with clear definitions and model examples of the key command terms and skills the experience is using (e.g. evaluate, justify, discuss, demonstrate), so that students can easily refer back to them.

Build consistency across the schools using inquiry-based language, the terms should be the same across subjects and across age groups, so that students consistently know what we mean by key terms like ‘hypothesis’.

Facilitate peer exchange – sometimes the direct guidance is not explicitly from the teacher but insofar as the teacher facilitating the connections between students so they can share some of their approaches and early findings. This peer feedback can disseminate ideas but also refine those ideas.

Students have the opportunity to consider information or concepts in different representations to deepen understanding and support the retention of key ideas. This may look different across subjects, including students considering different approaches to solving problems or achieving particular learning goals, or considering different perspectives when it comes to interpreting information or concepts.

In each case, to be impactful students should focus on understanding the connections between these different representations or the different approaches to problems and challenges; students are not merely seeing multiple perspectives but critically thinking about them and where there are similarities and differences.

Associated Terms: Multiple representations; Multiple approaches or strategies; Multiple perspectives

There is a large body of theoretical work on the use of multiple representations and approaches and how the brains function (Mayer, 2002[58]; Paivio, 1990[59]). These are grounded in a range of primarily small-scall empirical studies, though meta-analytical research suggests this practice can be impactful for student learning. A meta-analysis of 11 studies found that combining texts and images leads to deeper and more useable knowledge as compared to when only text and images are used alone (Mayer, 2002[58]).

There is a notable body of research on mathematics education. Rau et al. (2015[60]) conducted experiments with some 250 students on the learning of fractions in mathematics, finding that the use of multiple graphical representations may support better learning than single graphical representations, provided that students are supported in relating graphical representations to key concepts. Similarly, in mathematics students can be encouraged to consider ‘multiple solution paths’ and consider the validity of different approaches (Baumert et al., 2010[7]), with the depth at which these are considered potentially shaping what students learn (Baumert et al., 2013[61]).

The potential impacts of using multiple representations and approaches seemingly stretches across subjects. There is a long history of considering ‘multi-perspectivity’ in subjects such as history (Stradling, 2003[62]; Wansink et al., 2018[63]), and some empirical evidence with older students in college when they are engaged in working with contrasting cases (Schwartz and Bransford, 1998[64]). Similarly, the use of constructing multiple representations of content in the teaching of science, particularly visual representations, is also well-established (Ainsworth, 2014[65]).

Teachers’ careful and selective use of multiple representations, such as both verbal and non-verbal representations simultaneously (Mayer, 2002[58]; Paivio, 1990[59]), can be beneficial for students by deepening their understanding of content and supporting its retention. However, teachers need to avoid unnecessary cognitive load on students that may confuse them by scaffolding the connections between different representations or approaches (Kirschner, 2002[66]; Willingham, 2009[55]).

Insights from schools:

Introduce different representations of an idea one-by-one at first, so students can develop a good understanding of them in isolation first.

Show two different representations of an idea, or different perspectives or approaches to a problem, side-by-side when moving to consider multiple representations, so that students can look across and identify specific similarities or differences.

When students develop their own multiple representations of content it can give them practice opportunities to express what they know and can do (Schwarz, Passmore and Reiser, 2017[67]). In particular, it allows them to try make connections, which can be helpful as students have to retrieve and apply their knowledge to new situations.

Insights from schools:

Challenge students to transform content into new forms, such as a text into a new visual form, or rewriting material for a different audience or from a different perspective.

Encourage students to think in an interdisciplinary way, such as by bringing in similar representations that they have used in another subject, or by pushing students to make a connection with another topic.

Sustain a classroom culture that values difference where students are encouraged to see the multiple ways of approaching ideas or problems and feel safe to try things out.

Supporting students to consider multiple approaches and generate alternative solutions can promote flexible thinking (Li et al., 2024[68]). While students may sometimes identify connections themselves, complex relationships often require modelling and explanation (Ainsworth,  Wood and  Bibby, 1996[69]; Van Meter et al., 2020[70]). For instance, a meta-analysis of 27 studies found that signals highlighting connections between text and pictures can support comprehension, suggesting it is a relevant design principle for the use of multiple representations, especially for learners with lower prior knowledge (Richter, Scheiter and Eitel, 2016[71]). The teacher validating these connections is crucial to avoid confusion or misconceptions.

Insights from schools:

Use selective prompts and signals that help draw students’ attention to key features of a representation to reduce cognitive load.

Demonstrate the relationship between different representations by showing how they vary when key features slightly change, such as how changing an equation impacts a graphical and algebraic representation in maths or science, or how different extracts of sources can lead to different perspectives.

Bring students together to discuss their different representations or perspectives of a shared focus, such as their different interpretations of an artefact.

Metacognition refers to students having opportunities to think about or reflect upon their own thinking and learning. Students do this by applying different metacognitive strategies depending on the learning context, and students should have opportunities to learn about these strategies and to practise applying them. In general, metacognitive strategies comprise metacognitive knowledge and metacognitive skills, with the former emphasising deeper understanding of their own learning habits and the latter focused on using such understanding to enhance cognitive learning.

Associated Terms: Self-regulation; Self-monitoring; Metacognitive strategies; Metacognitive knowledge; Metacognitive skills; Learning about learning

There is a strong body of research on the use of metacognitive strategies in the classroom. A meta-analysis of 246 studies observed positive effects across both, primary and secondary pupils, and various subjects, with approaches in mathematics and science being particularly successful (Education Endowment Foundation, 2021[72]). This is a reasonably consistent finding in meta-analytic work on a range of subjects and age groups over the past decade (Credé and Phillips, 2011[73]; Ohtani and Hisasaka, 2018[74]). In particular, students’ active use of metacognitive strategies, such as think-aloud methods, seems particularly relevant; for instance, a recent meta-analysis on mathematics studies found that this type of metacognitive thinking during math problems was associated with increased performance (Muncer et al., 2021[75]).

More broadly, evidence on the use of metacognitive strategies is generally limited by small sample sizes, which weaken their statistical power and the generalisability of their findings. Additionally, analysing a more diverse range of metacognitive approaches is needed to ensure the effectiveness of various cognitive strategies, fostering more comprehensive and adaptive learning techniques. One ongoing measurement challenge in metacognition relates to capturing in-the-moment metacognition and retrospective metacognition (often referred to as “online” or “offline” metacognition). Some studies have found a disconnect between these types of measurements (Fleur, Bredeweg and van den Bos, 2021[76]).

Research evidence indicates that metacognitive strategies can be explicitly taught, and that doing so is beneficial for students (Perry, Lundie and Golder, 2018[77]; Schraw, 2001[78]). For instance, positive correlations have been found between the explicit teaching of metacognitive strategies and language mastery and writing performance (Colognesi et al., 2020[79]), biology learning (Ministry of Education, Nuray Tuncay Kara Science and Art Center, 2021[80]), and self-efficacy in mathematics (Amal and Mahmudi, 2020[81]). In particular, disadvantaged pupils may be less likely to use metacognitive strategies without being explicitly taught these strategies (Education Endowment Foundation, 2021[72]).

Insights from schools:

Provide concrete examples of the type of impactful metacognitive thinking that students should be aiming for when they are critically thinking about their learning.

Model thinking out loud to show how one can actually navigate challenges and struggles, so students don’t just see ‘successful examples’. For instance, when hitting an obstacle in problem-solving or inquiry processes, and the strategies that could be used to move forward.

It is important that students actively apply and practise metacognition as part of their learning (Allen and Hancock, 2008[82]). Metacognitive reflection during or upon task completion can improve students’ academic performance (Peters and Kitsantas, 2010[83]; Michalsky, Mevarech and Haibi, 2009[84]). Teachers need students to develop their own acumen on how they should respond to the wide range of learning situations they encounter within each subject matter.

Insights from schools:

Develop clear routines for thinking metacognitively, such as at the end of lessons or topics (e.g. “I used to think… and now I think…”; or “I can now use… but I need to do more of…”) or during ongoing inquiry process (e.g. revisiting, redrafting, critiquing).

Provide variation in how students communicate and log their metacognitive thinking, such as peer-to-peer or whole-class dialogue, or different written and multimedia formats that document their learning journeys, to sustain interest and engagement in the process.

Be mindful of student attention shifting to only the negative aspects – such as shortcomings or things as yet unachieved – as some students can spiral into obsessing on perfection, and there needs to be a support to ensure the reflection is not overwhelming and counter-productive.

Prompt students to think back to similar learning experiences when they are exercising choices and decisions, such as by asking them to consider “What was a challenge when you adopted this approach though last time?” or “What was a main takeaway on this topic last semester?”.

It is important to contextualise the use of metacognitive strategies to the content and subject matter that students are focusing on (Muijs and Bokhove, 2020[85]). This can help to make strategies more tangible and explicit. Students who use metacognitive strategies effectively on a particular subject matter might not do so as effectively for tasks of a different subject matter (Education Endowment Foundation, 2021[72]).

Insights from schools:

Co-develop with students a ‘toolbox’ or ‘logbook’ of the subject’s key problem-solving strategies, methods and processes, revisiting this to add in the scenarios and topics where students have used the subject’s different ‘tools’ so they can refer back to it when struggling with a new scenario.

Encourage students to explicitly immerse themselves in the thinking process of experts, such as ‘thinking like a Historian or a Mathematician’, or by using examples from real-world experts.

Because students’ cognitive engagement can be malleable and unpredictable, it demands constant monitoring (Symonds, Schreiber and Torsney, 2021[86]). Teachers are constantly looking for signals from students to gauge whether their implementation of teaching practices is effective or not. Teachers use their professional judgement in the classroom to perceive and process these signals.

Schools’ insights on the in-situ classroom signals for cognitive engagement (Table 2.1) provide an indication of the cognitive load that teachers undergo in noticing, processing and responding to them when teaching. These signals can be thought of as the short-term, in-class manifestation of the long-term knowledge, skills, values, and attitudes that teachers seek to encourage.

• Knowledge: Teachers need to be adept at recognising when students demonstrate deep understanding, evidenced by well-reasoned ideas, the ability to make real-world connections, and the effective transfer of knowledge to different contexts. Some of these aspects might be easy to interpret, such as when students provide a response, but others might require more cognitive load from teachers, such as discerning how well students connect concepts across different disciplines or apply knowledge in novel ways.

• Skills: Teachers must notice when students exhibit critical thinking, cognitive flexibility and problem-solving skills. This requires a sophisticated understanding of the processes behind learning and an ability to observe not just outcomes, but the strategies students employ. These seem particularly tied to specific actions from the teacher to bring them to the surface, such as how a task is designed or the particular questions that are asked.

• Values and Attitudes: Recognising students' motivation, sense of purpose, openness to new ideas, and respect for diverse perspectives demands that teachers pay close attention to students' affective state in the classroom. It might also need a higher level of differentiated attentiveness to avoid being driven by only overt signals from, for example, high achieving or extrovert students.

Notably, large class sizes, diverse student needs, and external distractions can all hinder a teacher's ability to accurately assess student signals.

Cognitive engagement is shaped by the actions of teachers in the classroom and is also informed by broader actions at the school- and system-levels. A deeper exploration of the complexity of engaging students cognitively can shed light on how school and system leaders can create supportive environments for quality cognitive engagement in classrooms.

For instance, how teachers are allocated to learners, including factors like class size and classroom composition, or any additional support from teaching assistants, can make a significant difference. Each student is unique; what is challenging for one may not be for another. The larger and more diverse the classroom, the more challenging it becomes to understand individual needs and orchestrate how students are challenged. More diverse classrooms are likely to increase the complexity of differentiation, scaffolding, and monitoring to maintain appropriate cognitive challenges.

Teachers’ opportunities for planning, the flexibility of the curricula, and the availability of teaching resources can be helpful in being more responsive to specific class and student needs. This can be particularly useful in navigating the many tensions in balancing the cognitive load of learning: finding the right depth and breadth, ensuring relevance, and maintaining appropriateness. For instance, to foster meaningful contexts and real-world connections, teachers do not necessarily need to reinvent the wheel every single lesson; a trusted bank of educational resources can facilitate more meaningful context and real-world applications, and tools can help adapt a single concept into diverse formats (visual, textual, etc.).

A school-wide approach might be beneficial to introduce relatively new practices such as metacognition, helping students ‘think’ about their own learning. The school’s use of consistent language and approaches around metacognition can be significant; explaining and embedding strategies in a way that transcends individual classrooms to build a more holistic approach to metacognition across lessons may be powerful.

A school-wide approach might also be needed for practices such as first-hand experiences that diverge from the historically traditional classroom structure. If these experiences are to take on an interdisciplinary nature, they may require flexibility in the curriculum and opportunities for collaboration among colleagues. Many first-hand experiences also invite a reimagination of the learning spaces or even connections with other learning environments, such as local communities and wider digital networks. Moreover, student learning might be harder to monitor and more susceptible to distractions, and school-level behaviour policies and routines for learning may provide teachers with tools for managing more challenging classroom structures.

In navigating the challenge of enabling high-quality cognitive engagement in classrooms, school and system leaders may carefully consider some of the following questions:

• How can school leaders empower teachers with the necessary mindsets, skills, and resources to consistently challenge students at appropriate levels? What strategies for student groupings, in terms of both type, size and length, can be implemented to support differentiated instruction where appropriate?

• What is the school's identity within its local community, and how does it connect to the broader world? What structures and partnerships can the school leadership establish to ensure that local identity and diversity are meaningfully integrated across curricula in various subjects? How does this translate into the school’s physical space (e.g. displays, art)?

• How can school spaces become more versatile learning environments? More broadly, how can the allocation of school resources – time, staff and finances – facilitate quality first-hand experiences for all students, such as through field trips and laboratory experiences at appropriate moments in student learning?

• In what ways can a culture of professional collaboration among teachers, both within and outside the school, be cultivated to enhance access to high-quality learning resources and tools? How can this collaboration support teachers in adopting multiple approaches and representations in their teaching practices?

• How can schools be structured to provide dedicated time and space for both students and teachers to engage in metacognitive practices, such as reflective meetings, peer observations, and self-assessment sessions? How is this aligned to the school's overall commitment to continuous improvement and reflection?

[65] Ainsworth, S. (2014), “The Multiple Representation Principle in Multimedia Learning”, in The Cambridge Handbook of Multimedia Learning, Cambridge University Press, https://doi.org/10.1017/cbo9781139547369.024.

[82] Allen, K. and T. Hancock (2008), “Reading Comprehension Improvement with Individualized Cognitive Profiles and Metacognition”, Literacy Research and Instruction, Vol. 47/2, pp. 124-139, https://doi.org/10.1080/19388070801938320.

[81] Amal, M. and A. Mahmudi (2020), “Enhancing students’ self-efficacy through metacognitive strategies in learning mathematics”, Journal of Physics: Conference Series, Vol. 1613/1, p. 012061, https://doi.org/10.1088/1742-6596/1613/1/012061.

[41] Atwater, M. (ed.) (2020), Using project-based learning to leverage culturally relevant pedagogy for sensemaking of science in urban elementary classrooms, Springer.

[50] Baron, A. et al. (2017), “The Tools of the Mind curriculum for improving self‐regulation in early childhood: a sytematic review”, Campbell Systematic Reviews, Vol. 13/1, pp. 1-77, https://doi.org/10.4073/csr.2017.10.

[7] Baumert, J. et al. (2010), “Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress”, American Educational Research Journal, Vol. 47/1, pp. 133-180, https://doi.org/10.3102/0002831209345157.

[61] Baumert, J. et al. (2013), “Professional competence of teachers, cognitively activating instruction, and the development of students’ mathematical literacy (COACTIV): A research program”, in Cognitive Activation in the Mathematics Classroom and Professional Competence of Teachers, Springer US, Boston, MA, https://doi.org/10.1007/978-1-4614-5149-5_1.

[28] Beers, K. and B. Probst (2016), Reading nonfiction: Notice & note stance, signposts and strategies, Heinemann.

[27] Beers, K. and B. Probst (2012), Notice & note: Strategies for close reading, Heinemann.

[57] Belland, B. et al. (2017), “Synthesizing Results From Empirical Research on Computer-Based Scaffolding in STEM Education”, Review of Educational Research, Vol. 87/2, pp. 309-344, https://doi.org/10.3102/0034654316670999.

[32] Bennett, J. et al. (2023), A systematic review of approaches to primary science teaching, Education Endowment Foundation, https://educationendowmentfoundation.org.uk/education-evidence/guidance-reports/primary-science-ks1-ks2Co-fundedbyWellcome (accessed on 8 January 2025).

[1] Blumenfeld, P., T. Kempler and J. Krajcik (2005), “Motivation and Cognitive Engagement in Learning Environments”, in The Cambridge Handbook of the Learning Sciences, Cambridge University Press, https://doi.org/10.1017/cbo9780511816833.029.

[24] Braithwaite, D. and R. Goldstone (2015), “Effects of Variation and Prior Knowledge on Abstract Concept Learning”, Cognition and Instruction, Vol. 33/3, pp. 226-256, https://doi.org/10.1080/07370008.2015.1067215.

[19] Chi, M. and R. Wylie (2014), “The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes”, Educational Psychologist, Vol. 49/4, pp. 219-243, https://doi.org/10.1080/00461520.2014.965823.

[16] Coe, R. et al. (2020), Great Teaching Toolkit: Evidence Review.

[79] Colognesi, S. et al. (2020), “Teaching Writing--With or without Metacognition?: An Exploratory Study of 11-to 12-Year-Old Students Writing a Book Review”, International Electronic Journal of Elementary Education, Vol. 12/5, pp. 459-470.

[73] Credé, M. and L. Phillips (2011), “A meta-analytic review of the Motivated Strategies for Learning Questionnaire”, Learning and Individual Differences, Vol. 21/4, pp. 337-346, https://doi.org/10.1016/j.lindif.2011.03.002.

[4] Creemers, B. and L. Kyriakides (2013), Improving Quality in Education, Routledge, https://doi.org/10.4324/9780203817537.

[3] Creemers, B. and L. Kyriakides (2006), “Critical analysis of the current approaches to modelling educational effectiveness: The importance of establishing a dynamic model”, School Effectiveness and School Improvement, Vol. 17/3, pp. 347-366, https://doi.org/10.1080/09243450600697242.

[53] de Jong, T. et al. (2023), “Let’s talk evidence – The case for combining inquiry-based and direct instruction”, Educational Research Review, Vol. 39, p. 100536, https://doi.org/10.1016/j.edurev.2023.100536.

[43] Deci, E. and R. Ryan (2016), “Optimizing Students’ Motivation in the Era of Testing and Pressure: A Self-Determination Theory Perspective”, in Building Autonomous Learners, Springer Singapore, Singapore, https://doi.org/10.1007/978-981-287-630-0_2.

[5] Dunlosky, J. et al. (2013), “Improving Students’ Learning With Effective Learning Techniques”, Psychological Science in the Public Interest, Vol. 14/1, pp. 4-58, https://doi.org/10.1177/1529100612453266.

[72] Education Endowment Foundation (2021), Metacognition and self-regulation: Technical Appendix, https://educationendowmentfoundation.org.uk/education-evidence/teaching-learning-toolkit/metacognition-and-self-regulation/technical-appendix.

[11] Fauth, B. et al. (2019), “The effects of teacher competence on student outcomes in elementary science education: The mediating role of teaching quality”, Teaching and Teacher Education, Vol. 86, https://doi.org/10.1016/j.tate.2019.102882.

[13] Fauth, B. et al. (2014), “Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes”, Learning and Instruction, Vol. 29, pp. 1-9, https://doi.org/10.1016/j.learninstruc.2013.07.001.

[76] Fleur, D., B. Bredeweg and W. van den Bos (2021), Metacognition: ideas and insights from neuro- and educational sciences, Springer Nature, https://doi.org/10.1038/s41539-021-00089-5.

[12] Fredricks, J., P. Blumenfeld and A. Paris (2004), “School Engagement: Potential of the Concept, State of the Evidence”, Review of Educational Research, Vol. 74/1, pp. 59-109, https://doi.org/10.3102/00346543074001059.

[44] Fu, D., Y. Liu and D. Zhang (2023), “The relationship between teacher autonomy support and student mathematics achievement: a 3-year longitudinal study”, Educational Psychology, Vol. 43/2-3, pp. 187-206, https://doi.org/10.1080/01443410.2023.2190064.

[48] Furtak, E. et al. (2012), “Experimental and Quasi-Experimental Studies of Inquiry-Based Science Teaching”, Review of Educational Research, Vol. 82/3, pp. 300-329, https://doi.org/10.3102/0034654312457206.

[29] Grant, S., J. Lee and K. Swan (2017), Teaching social studies : a methods book for methods teachers, Information Age Publishing, Inc.

[21] Hamari, J. et al. (2016), “Challenging games help students learn: An empirical study on engagement, flow and immersion in game-based learning”, Computers in Human Behavior, Vol. 54, pp. 170-179, https://doi.org/10.1016/j.chb.2015.07.045.

[6] Hattie, J. (2012), Visible learning for teachers: Maximizing impact on learning., Routledge.

[22] Hsieh, Y., Y. Lin and H. Hou (2016), “Exploring the role of flow experience, learning performance and potential behavior clusters in elementary students’ game-based learning”, Interactive Learning Environments, Vol. 24/1, pp. 178-193, https://doi.org/10.1080/10494820.2013.834827.

[10] Keller, M., K. Neumann and H. Fischer (2017), “The impact of physics teachers’ pedagogical content knowledge and motivation on students’ achievement and interest”, Journal of Research in Science Teaching, Vol. 54/5, pp. 586-614, https://doi.org/10.1002/tea.21378.

[66] Kirschner, P. (2002), “Cognitive load theory: implications of cognitive load theory on the design of learning”, Learning and Instruction, Vol. 12/1, pp. 1-10, https://doi.org/10.1016/S0959-4752(01)00014-7.

[17] Klieme, E. (2006), Qualitätsdimension und Wirksamkeit von Mathematikunterricht: Theoretische Grundlagen und ausgewählte Ergebnisse des Projekts ’’Pythagoras’’, Waxmann.

[54] Kolb, D. (2014), Experiential Learning: Experience as the Source of Learning and Development, Pearson FT Press.

[36] Krajcik, J. et al. (2023), “Assessing the Effect of Project-Based Learning on Science Learning in Elementary Schools”, American Educational Research Journal, Vol. 60/1, pp. 70-102, https://doi.org/10.3102/00028312221129247.

[56] Lazonder, A. and R. Harmsen (2016), “Meta-Analysis of Inquiry-Based Learning”, Review of Educational Research, Vol. 86/3, pp. 681-718, https://doi.org/10.3102/0034654315627366.

[9] Li, H. et al. (2021), “Examining the relationships between cognitive activation, self‐efficacy, socioeconomic status, and achievement in mathematics: A multi‐level analysis”, British Journal of Educational Psychology, Vol. 91/1, pp. 101-126, https://doi.org/10.1111/bjep.12351.

[8] Lipowsky, F. et al. (2009), “Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean Theorem”, Learning and Instruction, pp. 527-537.

[68] Li, T. et al. (2024), “The relationships between elementary students’ knowledge‐in‐use performance and their science achievement”, Journal of Research in Science Teaching, Vol. 61/2, pp. 358-418, https://doi.org/10.1002/tea.21900.

[20] Ma, N. et al. (2023), “Promoting programming education of novice programmers in elementary schools: A contrasting cases approach for learning programming”, Education and Information Technologies, Vol. 28/7, pp. 9211-9234, https://doi.org/10.1007/s10639-022-11565-9.

[58] Mayer, R. (2002), “Multimedia learning”, https://doi.org/10.1016/S0079-7421(02)80005-6.

[31] Mayer, R. (1990), “Problem solving”, in Eysenck, M. (ed.), The Blackwell Dictionary of Cognitive Psychology, Basil Blackwell, Oxford.

[23] McNeill, K. et al. (2006), “Supporting Students’ Construction of Scientific Explanations by Fading Scaffolds in Instructional Materials”, Journal of the Learning Sciences, Vol. 15/2, pp. 153-191, https://doi.org/10.1207/s15327809jls1502_1.

[39] Menzies, V. et al. (2016), Project Based Learning Evaluation report and executive summary, Education Endowment Foundation, http://www.educationendowmentfoundation.org.uk (accessed on 8 January 2025).

[84] Michalsky, T., Z. Mevarech and L. Haibi (2009), “Elementary School Children Reading Scientific Texts: Effects of Metacognitive Instruction”, The Journal of Educational Research, Vol. 102/5, pp. 363-376, https://doi.org/10.3200/JOER.102.5.363-376.

[80] Ministry of Education, Nuray Tuncay Kara Science and Art Center (2021), “The effect of metacognition strategy teaching on biology education”, African Educational Research Journal, Vol. 9/4, pp. 870-876, https://doi.org/10.30918/aerj.94.21.139.

[25] Mishra, P. and M. Koehler (2006), “Technological pedagogical content knowledge: A framework for teacher knowledge”, Teachers College Record, pp. 1017-1054.

[30] Monte-Sano, C., S. De La Paz and M. Felton (2014), “Reading, Thinking, and Writing about History: Teaching Argument Writing to Diverse Learners in the Common Core Classroom, Grades 6-12”, Common Core State Standards in Literacy Series, p. 240.

[85] Muijs, D. and C. Bokhove (2020), Metacognition and Self-Regulation: Evidence Review, https://educationendowmentfoundation.org.uk/evidence-summaries/evidence-reviews/metacognition-and-self-regulation-review/ (accessed on 8 January 2025).

[75] Muncer, G. et al. (2021), “A Meta-Analysis Investigating the Association Between Metacognition and Math Performance in Adolescence”, Educational Psychology Review, Vol. 34/1, pp. 301-334, https://doi.org/10.1007/s10648-021-09620-x.

[35] National Research Council (2007), Taking science to school: Learning and teaching science in grades K-8, National Academies Press.

[18] Neumann, K., A. Kauertz and H. Fischer (2012), Quality of instruction in science education, Springer.

[33] Nunes, T. et al. (2017), Review of SES and Science Learning in Formal Educational Settings, Education Endowment Foundation, https://d2tic4wvo1iusb.cloudfront.net/production/documents/guidance/Review_of_SES_and_Science_Learning_in_Formal_Educational_Settings.pdf?v=1736485426 (accessed on 18 September 2023).

[26] Nunokawa, K. (2010), Proof, mathematical problem-solving, and explanation in mathematics teaching, Springer.

[46] OECD (2024), What Does Child Empowerment Mean Today?: Implications for Education and Well-being, Educational Research and Innovation, OECD Publishing, Paris, https://doi.org/10.1787/8f80ce38-en.

[74] Ohtani, K. and T. Hisasaka (2018), “Beyond intelligence: a meta-analytic review of the relationship among metacognition, intelligence, and academic performance”, Metacognition and Learning, Vol. 13/2, pp. 179-212, https://doi.org/10.1007/s11409-018-9183-8.

[69] P., B., A. Paiva and J.  Self (eds.) (1996), Co-ordinating multiple representations in computer based learning environments, Ediçoes Colibri.

[59] Paivio, A. (1990), Mental Representations: A Dual Coding Approach, Oxford University Press, Oxford.

[45] Parker, J. et al. (2021), “Perceived Teacher Autonomy Support and Self-Determination Skill Expression: Predictors of Student Engagement Among African American High School Students”, Journal of Black Psychology, Vol. 47/6, pp. 445-475, https://doi.org/10.1177/00957984211009190.

[15] Pekrun, R. and L. Linnenbrink-Garcia (2012), “Academic Emotions and Student Engagement”, in Handbook of Research on Student Engagement, Springer US, Boston, MA, https://doi.org/10.1007/978-1-4614-2018-7_12.

[2] Pellegrino,  . and M. Hilton (2012), Education for Life and Work, National Academies Press, Washington, D.C., https://doi.org/10.17226/13398.

[77] Perry, J., D. Lundie and G. Golder (2018), “Metacognition in schools: what does the literature suggest about the effectiveness of teaching metacognition in schools?”, Educational Review, Vol. 71/4, pp. 483-500, https://doi.org/10.1080/00131911.2018.1441127.

[83] Peters, E. and A. Kitsantas (2010), “Self‐regulation of student epistemic thinking in science: the role of metacognitive prompts”, Educational Psychology, Vol. 30/1, pp. 27-52, https://doi.org/10.1080/01443410903353294.

[34] Puttick, S. (2017), “Should we only teach about real people and real places?”, Geography, Vol. 102/1, pp. 26-32, https://doi.org/10.1080/00167487.2017.12094006.

[60] Rau, M., V. Aleven and N. Rummel (2015), “Successful learning with multiple graphical representations and self-explanation prompts”, Journal of Educational Psychology, Vol. 107/1, pp. 30-46, https://doi.org/10.1037/a0037211.

[71] Richter, J., K. Scheiter and A. Eitel (2016), Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis, Elsevier Ltd, https://doi.org/10.1016/j.edurev.2015.12.003.

[47] Rogers, C. and M. Thomas (2022), Educational Neuroscience, Routledge, London, https://doi.org/10.4324/9781003185642.

[40] Sánchez Tapia, I. (ed.) (2020), International Perspectives on the Contextualization of Science Education, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-27982-0.

[42] Sánchez Tapia, I., J. Krajcik and B. Reiser (2017), ““We do not know what is the real story anymore<i>”</i>: Curricular contextualization principles that support indigenous students in understanding natural selection”, Journal of Research in Science Teaching, Vol. 55/3, pp. 348-376, https://doi.org/10.1002/tea.21422.

[14] Schmidt, J., J. Rosenberg and P. Beymer (2018), “A person-in-context approach to student engagement in science: Examining learning activities and choice”, Journal of Research in Science Teaching, Vol. 55/1, pp. 19-43, https://doi.org/10.1002/tea.21409.

[37] Schneider, B. et al. (2022), “Improving Science Achievement—Is It Possible? Evaluating the Efficacy of a High School Chemistry and Physics Project-Based Learning Intervention”, Educational Researcher, Vol. 51/2, pp. 109-121, https://doi.org/10.3102/0013189X211067742.

[78] Schraw, G. (2001), “Promoting General Metacognitive Awareness”, in Neuropsychology and Cognition, Metacognition in Learning and Instruction, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-017-2243-8_1.

[64] Schwartz, D. and J. Bransford (1998), “A Time For Telling”, Cognition and Instruction, Vol. 16/4, pp. 475-5223, https://doi.org/10.1207/s1532690xci1604_4.

[67] Schwarz, C., C. Passmore and B. Reiser (2017), Helping students make sense of the world using next generation science and engineering practices, NSTA Press.

[52] Skene, K. et al. (2022), Can guidance during play enhance children’s learning and development in educational contexts? A systematic review and meta-analysis, John Wiley and Sons Inc, https://doi.org/10.1111/cdev.13730.

[62] Stradling, R. (2003), Multiperspectivity in history teaching: A guide for teachers, Council of Europe.

[38] Sweller, J. et al. (2023), “Response to De Jong et al.’s (2023) paper “Let’s talk evidence – The case for combining inquiry-based and direct instruction””, Educational Research Review, p. 100584, https://doi.org/10.1016/j.edurev.2023.100584.

[86] Symonds, J., J. Schreiber and B. Torsney (2021), “Silver linings and storm clouds: Divergent profiles of student momentary engagement emerge in response to the same task.”, Journal of Educational Psychology, Vol. 113/6, pp. 1192-1207, https://doi.org/10.1037/edu0000605.

[70] Van Meter, P. et al. (eds.) (2020), Handbook of Learning from Multiple Representations and Perspectives, Routledge, New York.

[63] Wansink, B. et al. (2018), “Where Does Teaching Multiperspectivity in History Education Begin and End? An Analysis of the Uses of Temporality”, Theory & Research in Social Education, Vol. 46/4, pp. 495-527, https://doi.org/10.1080/00933104.2018.1480439.

[51] Whitebread, D. et al. (2019), The SAGE Handbook of Developmental Psychology and Early Childhood Education, SAGE Publications Ltd, 1 Oliver’s Yard, 55 City Road London EC1Y 1SP , https://doi.org/10.4135/9781526470393.

[55] Willingham, D. (2009), Why don’t students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom, Jossey-Bass/Wiley.

[49] Zosh, J. et al. (2017), Learning through play : a review of the evidence, LEGO Foundation.