This chapter analyses the relationship between motivation to learn and the use of learning strategies. It also explores a number of concepts that are key to further understanding the interplay between the use of learning strategies and students' attitudes towards learning and self-beliefs. These include students’ growth mindsets, social and emotional skills such as persistence and co-operation, and teacher inputs to cognitive activation and creative problem-solving.
PISA 2022 Results (Volume V)
Learning Strategies and Attitudes for Life
PISA
Abstract
For Australia*, Canada*, Denmark*, Hong Kong (China)*, Ireland*, Jamaica*, Latvia*, the Netherlands*, New Zealand*, Panama*, the United Kingdom* and the United States*, caution is advised when interpreting estimates because one or more PISA sampling standards were not met (see Reader’s Guide, Annexes A2 and A4).
Learning strategies, student motivation, and self-belief form a triangle of learning. Each part of this triangle contributes something unique to the learning process. Working together, they can help students learn better and for life.
While learning strategies, and control and self-monitoring strategies are what learners use to understand, learn, and retain information, motivation is the drive that compels students to learn in the first place. Motivation determines the amount of effort a student will invest in their learning. A supportive environment that fosters student motivation can lead to higher levels of engagement and enthusiasm for learning (Deci, 1985[1]).
Self-belief is a student’s confidence in their ability to succeed in learning tasks. One example is the belief that abilities can be developed through dedication and hard work, empowering students to embrace challenges and see failure as an opportunity for growth rather than an insurmountable obstacle. This positive self-belief is crucial for resilience. Students with strong self-beliefs are more likely to use effective learning strategies and remain motivated even when facing setbacks (Dweck, Walton and Cohen, 2014[2]).
In close connection with motivations and self-beliefs, metacognitive learning strategies; that is, learning strategies that entail awareness, understanding and control of learning processes, are key in fostering independent and active learning (Schneider and Artelt, 2010[3]). In the critical-thinking and perspective-taking sphere, these strategies involve reflective thinking exercises and creative problem-solving tasks. These are often exercised through cognitive activation and promote the deeper learning processes necessary for self-directed lifelong learning. When students are motivated and have strong self-belief, they are more likely to adopt challenging, creative and effective learning strategies. This chapter looks closely at this triangular relationship between learning strategies, motivation, and self-belief (c.f. Tables V.1.2 and V.1.3 in Chapter 1).
Analyses of the learning triangle of strategies, student motivation, and self-belief show that intrinsic motivations such as enjoying learning new things in school consistently predict the uptake of learning strategies though they are not always the strongest factor. In specific cases, enjoying challenging schoolwork shows the strongest relationship with asking questions when not understanding the material in some countries, including Estonia, Latvia*, Poland, Türkiye and the United Kingdom*. Still, the challenge remains: only half of students on average in OECD countries reported enjoying learning new things at school and less than half reported that they like challenging schoolwork.
Growth mindsets are strongly linked to positive learning strategies, attitudes, and outcomes as well. However, even when they have a growth mindset, many students still hold on to negative mathematics-learning stereotypes. Slightly over half of students with a general growth mindset reported a fixed mindset in mathematics. Argentina, Georgia, Peru, Singapore, and the United Arab Emirates show the smallest share of students with a contradictory combination of a general growth mindset and fixed mathematical mindset.
Low performers may need extra support connecting what they learn with what they had learned previously as they seldom use this learning strategy even when prompted by teachers.
Boys and girls may perceive and engage with learning strategies differently, highlighting the importance of tailored approaches to effectively reach all students.
Co-operation is the social and emotional skill most strongly related to critical-thinking attitudes, such as considering multiple perspectives before forming an opinion. This relationship is particularly strong in top-performing systems like Hong Kong (China)*, Korea, Singapore and Chinese Taipei. This suggests a strong cultural and educational emphasis on co-operative learning and considering multiple perspectives.
Students with higher levels of persistence, regardless of their socio-economic profile or mathematics achievement, are more adept at using a variety of learning strategies. Persistent students are more likely to be meticulous about their schoolwork, and they are also more proactive. These relationships are strong in several countries and economies, including Australia* for proactivity and Bulgaria and Hong Kong (China)* for meticulousness.
Students’ adoption of learning strategies is intricately linked to their motivations. In self-determination theory (Deci, 1985[1]), research suggests that the way motivations influence specific outcomes can vary according to the type of motivation (Taylor et al., 2014[4]). Some are intrinsic while others are extrinsic and more instrumental1. Intrinsic motivations generally have the strongest relationship to student outputs.
To get a measure of students’ intrinsic motivations, PISA analysed how much students enjoy learning new things in school and embrace challenging schoolwork. To measure their instrumental motivations, PISA looked at how much students want to do well in school and believe that school teaches things that can be useful in a job. These four motivations have a positive influence on students’ uptake of strategies for sustained lifelong learning.
Likelihood of reporting learning strategies when intrinsically or instrumentally motivated, after accounting for students' and schools' socio-economic profile; OECD average
Notes: All odds ratio coefficients are statistically significant (see Annex A3).
The socio-economic profile is measured by the PISA index of economic, social and cultural status (ESCS).
Source: OECD, PISA 2022 Database, Tables V.B1.3.51-V.B1.3.55.
See Table V.3.1 for StatLink at the end of this chapter.
Intrinsic motivations are a consistent predictor of learning strategies uptake but not always the strongest
To measure students’ use of learning strategies, PISA focused on their responses about five of them (see Chapter 1, Table V.1.2). Indicative of control and self-monitoring strategies are students’ propensity to try to not make mistakes in their work, double-check homework, and ask questions when they do not understand something that is being taught. Critical-thinking strategies are captured by students’ ability to view issues from different angles and belief that there is more than one correct position in a disagreement.
Students who reported having intrinsic motivations are more likely to employ control and self-monitoring strategies as well as critical-thinking (perspective-taking) strategies, demonstrating a robust association between them (Figure V.3.1).
Of the four learning motivations analysed in Figure V.3.1, enjoying learning new things in school has, on average, the strongest relationship with the strategy of checking work for mistakes, especially homework. This intrinsic motivation shows some of the strongest average relationships with three of the five learning strategies whereas an instrumental motivation like thinking that school teaches things useful for a job shows some of the weakest (Figure V.3.1).
In terms of countries and economies, these relationships are largely positive, particularly for intrinsic motivations such as enjoying learning new things in school as well as the more instrumental wanting to do well in mathematics class – the latter strongly related to the study behaviour of asking questions when one does not understand something (Figures V.3.1b-V.3.1g [available online]). Interestingly, liking schoolwork that is challenging shows the strongest relationship with asking questions when not understanding the material in some OECD countries: Estonia, Latvia*, Poland, Türkiye and the United Kingdom* (Figure V.3.1d [available online]). It shows the strongest relationship to carefully checking homework before handing it in the United Kingdom* and seeing things from different angles in Ireland* and Mexico (Figure V.3.1e [available online]). Yet, the relationship between the four student motivations and the critical-thinking indicator of embracing different perspectives in disagreements differs greatly from country to country. And, interestingly, the relationship between instrumental motivations and this complex type of critical thinking (perspective-taking) is often stronger than for the intrinsic motivations considered in these analyses (Figure V.3.1f [available online]).
Further analyses show similar relationships between the four motivations and learning strategies that make up students’ proactive mathematics study behaviours. These particular learning strategies include connecting new and prior knowledge, actively participating in group discussions, and doing mathematics assignments right away. Yet, the main driver for proactivity is wanting to do well in mathematics class even though liking schoolwork that is challenging is a stronger driver in two OECD countries, Mexico and the Slovak Republic (Table V.B1.3.50). Overall, these findings support the hypothesis that positive attitudes towards learning encourage students to employ effective learning strategies. They also show the value of fostering student interest in learning. Interestingly, the attitude of thinking there is more than one correct position in a disagreement shows the weakest relationship to students’ motivation to learn, though it is still positive on average (see Box V.3.1).
One way to improve students’ sustainable learning strategies is to work on how to best motivate them. PISA analyses show that in most of the cases analysed here there is a weaker, on average, relationship between motivation and critical thinking or perspective-taking learning strategies (Figure V.3.1).
However, the association of critical thinking or perspective-taking with more robust motivations can buttress the relationship, as measured by its indirect effect on student performance. The PISA index of curiosity encompasses different types of intrinsic motivations, including, for example, students' enjoyment of learning new things in school, asking questions, and developing hypotheses and checking them based on what they observe1.
Across OECD countries, about 32% of the performance difference between students who try to consider everybody's perspective before taking a position and those who do not can be understood as the indirect effect of their differences in intrinsic motivations measured by the index of curiosity (Table V.B1.3.6). Between students who reported they can view almost all things from different angles and those who cannot, the share of the performance difference indirectly resulting from intrinsic motivations can be as high as 40% on average. However, as mentioned earlier, the relationship between motivation and critical thinking or perspective-taking is the weakest between students who think there can be more than one correct position in a disagreement and those who do not. Only about 6% of the performance difference between these two groups of students can be interpreted as the indirect result of differences in intrinsic motivations as measured in the index of curiosity (Table V.B1.3.6)2.
These findings show the complexity of the relationships between student motivation, engagement with learning strategies, and academic outcomes. They also suggest that, just like learning strategies, motivations do not act alone. Students probably have different incentives for engaging in their own learning. But boosting motivations can encourage students to use learning strategies in school and later on in life.
1. The PISA index of curiosity is based on students’ ratings of their agreement with statements about a range of behaviours, including “I like to know how things work”, “I like to ask questions”, “I love learning NEW things in school” and “I like to develop hypotheses and check them based on what I observe”. Each of the items included four response options (“strongly disagree”, “disagree”, “agree”, or “strongly agree”).
2. The indirect effects described here are based on the coefficients resulting from two linear regressions: (1) the total effect of the critical-thinking strategy, which represents the change in score points in mathematics performance associated with agreeing/strongly agreeing (or disagreeing/strongly disagreeing) with the corresponding perspective-taking statement, controlling for students' socio-economic profile (measured by the PISA index of economic, social and cultural status [ESCS]), and (2) the effect of the critical-thinking strategy, controlling for the indirect effect of the index of curiosity. These coefficients are reported in the Table V.B1.3.6.
Boosting students' motivation to learn is key to lifelong learning
Not only do motivations have a positive link with students using learning strategies in most countries and economies but PISA data also show a positive relationship between these diverse types of motivation and mathematics performance. This indicates the broad influence of motivation on learning outcomes (Tables V.B1.3.5, V.B1.3.10, V.B1.3.15).
PISA 2022 data show that only half of students in OECD countries reported enjoying learning new things at school and 47% reported enjoying challenging schoolwork. While about the same percentage of skilled performers reported being intrinsically motivated, less than half of low performers said they were. There are, however, important differences depending on countries/economies; for example, at least 85% of students in Guatemala, Peru and Viet Nam reported enjoying learning new things in school. In these same countries, over 85% of low performers are also intrinsically motivated. Conversely, in countries like Czechia and Poland, around a third of students, or less, reported this motivation, with both skilled and low performers among the least intrinsically motivated (Tables V.B1.3.4 and V.B1.3.18).
Percentage of students who agree or strongly agree that they love new things in school
Countries and economies are ranked in ascending order of the percentage of all students.
Source: OECD, PISA 2022 Database, Table V.B1.3.4.
See Table V.3.1 for StatLink at the end of this chapter.
Instrumental motivations are more prevalent, with a substantial majority of students (89%, on average across OECD countries) expressing a strong desire to do well in mathematics class. Additionally, 67% of students agreed or strongly agreed that school has taught them things useful for working. Only in Germany did less than half of students report this instrumental motivation. Both skilled and low performers are, generally, instrumentally motivated but less than half of skilled performers are in Germany and Poland, and less than 50% of low performers in Germany (Figures V.3.2b and V.3.2c [available online], Tables V.B1.3.9 and V.B1.3.14).
While wanting to do well in mathematics class clearly motivates students across countries and economies, PISA data suggest that education systems might pay more attention to all four motivations for lifelong learning, whether intrinsic or instrumental. Of the four, intrinsic motivations should be a priority for schools. They have a strong relationship with proactive learning behaviours and sustained learning strategies, especially for low performers.
The third side of the learning triangle is self-belief, an important part of which is the conviction that abilities can be developed through dedication and effort. The concept of a growth mindset is the belief that abilities and intelligence can be developed over time. This contrasts with a fixed mindset or the belief that intelligence and abilities are static or fixed traits (Dweck, 2006[5]). Schools that foster a growth mindset can enhance student learning (Yeager and Walton, 2011[6]).
On average, across OECD countries, 58% of students reported having a growth mindset though this varies significantly by country/economy. For instance, over 70% of students in Austria, Estonia, Germany, Ireland*, Japan and Sweden reported a growth mindset compared to only a third or fewer in Albania and Kosovo (Table V.B1.3.39). Gender differences are non-significant in almost half of countries/economies and when they are, they are not more than 10 percentage points, with boys slightly more often reporting a growth mindset (Table V.B1.3.40).
In mathematics, however, only 35% of students reported a growth mindset.2 In countries like Georgia, New Zealand*, Peru, Singapore, and Sweden, at least half of their students reported a mathematics growth mindset while in Czechia, Japan, Poland and Slovenia, fewer than 20% did (Table V.B1.3.43). Unlike a general growth mindset, gender differences in mathematics growth mindset are more pronounced and significant across most countries and economies, with boys being more likely to report it by an average of 7 percentage points. This gap can be as sizeable as over 15 percentage points in countries/economies like Jordan and the Palestinian Authority (Table V.B1.3.42).
Math-learning stereotypes are obstinate even among students with a growth mindset
The discrepancy between general and mathematics-specific growth mindsets is notable. Slightly over half of students with a general growth mindset reported a fixed mindset in mathematics (55%, on average across OECD countries), with consistent gaps across low and skilled performers. Among top performers, the gap is slightly smaller but remains substantial at 48% (Figure V.3.3, and Table V.B1.3.44). Overall, the smallest gaps are in Argentina, Georgia, Peru, Singapore, and the United Arab Emirates.
Percentage of students with general growth mindset who reported agreeing/strongly agreeing (fixed mindset) or disagreeing/strongly disagreeing (growth mindset) with the statement "Some people are just not good at mathematics, no matter how hard they study"; OECD average
Note: Only countries and economies with available data are shown.
Countries and economies are ranked in ascending order of the percentage of students with a mathematics growth mindset.
Source: OECD, PISA 2022 Database, Table V.B1.3.44. See Table V.3.1 for StatLink at the end of this chapter.
This discrepancy is particularly important because it suggests that many students view math ability as innate, reinforcing fixed mindsets and stereotypes, including damaging math-gender stereotypes (Correll, 2004[7]; Cvencek, Kapur and Meltzoff, 2015[8]; Cvencek et al., 2017[9]). Students with fixed mindsets about school or about themselves as learners are more likely to withdraw from essential learning behaviours and give up easily when encountering setbacks. They are also more likely to attribute failures to what they perceive as aspects beyond their control (Dweck, Walton and Cohen, 2014[2]).
Growth mindsets show a strong relationship with learning strategies, attitudes and outcomes
Why is this relevant? The self-belief concept of growth mindset explains some of the reasons and motivations behind students engaging with specific learning strategies and using their energy and resources to meet their learning goals. This is central to lifelong learning and to this report.
For example, students who reported asking questions when unsure of material are, on average and across OECD countries, more likely to report a growth mindset in mathematics (Figure V.3.3b [available online]). The relationship is particularly strong in Korea and Chinese Taipei. While causality cannot be attributed to these analyses, the relationship suggests that creating spaces where students feel confident enough to ask questions encourages students’ conviction that they can master something even if it is difficult. Research suggests that students with a growth mindset are more willing to put in an effort even when they encounter challenges or fail (Dweck and Yeager, 2019[10]).
Findings in this section suggest that some education systems may be more attuned to growth mindset than others. However, low performers face the challenge of not only struggling to ask questions but also being at risk of not developing positive mindsets. If a student believes (or has been told) they are not good at mathematics, regardless of how hard they try, they are less likely to ask questions when in doubt. In the same vein, growth mindset relates positively to relevant critical-thinking behaviours such as considering there can be multiple valid perspectives in disagreements. This relationship is particularly strong in some OECD countries like Colombia, Mexico and New Zealand* (Table V.B1.3.47).
In close relation to this, intrinsic motivations such as enjoying challenging schoolwork and liking learning new things are also significantly related to growth mindset. These relationships are strong across most countries and economies, emphasising that students embracing the belief they can enhance their intelligence, skills and knowledge are often those that enjoy learning as well. Interestingly, students in Australia* and Denmark* are about twice as likely to report these two intrinsic motivations when they have a mathematics growth mindset (Table V.B1.3.47).
Research suggests that students with a growth mindset are more likely to persevere with their schoolwork, leading to better academic behaviours and improved performance, including in mathematics (Claro, Paunesku and Dweck, 2016[11]; Farrington et al., 2012[12]). PISA 2022 data support these claims as growth mindset in mathematics is strongly associated with higher perseverance, greater confidence (self-efficacy) in mathematics, and proactive study behaviour in mathematics. These relationships are robust across countries/economies, although they are influenced by mathematics performance in many countries/economies. The case of Colombia is particularly interesting as the relationship between all these aspects becomes non-significant when accounting for performance in mathematics. This suggests that success in mathematics for Colombian students is a crucial factor in sustaining their growth mindset and related behaviours (Table V.B1.3.46). As with a general growth mindset, a growth mindset in mathematics has a strong, positive relationship with learning outputs like performance in mathematics (Tables V.B1.3.45 and I.B1.2.17 [from Volume I, PISA 2022 Results]).
These results suggest that while the prevalence of a growth mindset varies across countries and economies, its positive relationship with learning attitudes and outcomes is consistent. Intervention research shows that academic mindsets are malleable and can be intentionally shaped through contextual and instructional variables (Yeager and Walton, 2011[6]). Developing positive mindsets in schools can support the development of students’ positive attitudes towards learning. It can encourage them to use effective learning strategies, enhance their motivation, and through this, foster lifelong learning. Building growth mindsets in different areas, particularly in mathematics, and tailoring teaching strategies to diverse learner needs can help all students achieve their full potential. Opportunities for students to develop growth mindsets have been incorporated into national plans. For example, the Youth Sector Development Plan (2021-2023) in Estonia helps create environments and opportunities for each student to cultivate attitudes and motivations through growth mindset activities (see Box V.3.2).
Percentage of students who disagree/strongly disagree (growth mindset) with the statement "Some people are just not good at mathematics, no matter how hard they study"
Note: Only countries and economies with available data are shown.
Countries and economies are ranked in ascending order of the percentage of all students.
Source: OECD, PISA 2022 Database, Table V.B1.3.43.
See Table V.3.1 for StatLink at the end of this chapter.
Estonia’s Youth Sector Development Plan for 2021-2035 outlines strategies such as instilling entrepreneurship, and skills and competencies to support the growth and development of young people who are key to Estonia’s lifelong learning tradition and policy. An integrated youth policy has been implemented since 2006. It requires all ministries to consider the principles of this youth policy in formulating measures and making decisions that impact young people.
The plan highlights that it is necessary for youth to build self-confidence and self-reliance as these qualities enable individuals to experience and deal with mistakes, and succeed and learn from the outcomes of their decisions. It emphasises encouraging young people to pursue their talents and interests, and providing opportunities for youth development.
Activities are held in youth centres and participation in these activities is voluntary for young people. The centres provide young people with growth-oriented and meaningful activities that focus on one’s development rather than outcome. In 2024, there were 288 youth centres, with most in rural areas. Youth initiatives that allow young people to develop and execute their ideas, safely experiment, make mistakes and learn from one’s experience are also supported. Implementing one’s own ideas allows individuals to acquire and value new skills and experiences, and develop a proactive frame of mind. Youth initiatives are supported locally through project calls and internationally through activities such as the Erasmus+ programme.
Cognitive activation encompasses instructional activities that often require student engagement in the evaluation, integration, and application of knowledge in problem-solving contexts, typically linked with (but not exclusive to) sharing and explaining their thoughts, concepts and solutions to given problems or tasks (Lipowsky et al., 2009[14]). These strategies are essential for fostering higher-order thinking skills such as critical analysis, problem-solving, and decision making.
Despite the established benefits of these practices, as highlighted in previous OECD studies (Echazarra et al., 2016[15]; Le Donné, Fraser and Bousquet, 2016[16]), student reports in PISA 2022 suggest they are not widespread on average: more “traditional” strategies like memorisation and perseverance are the most prevalent (52% of students reported memorising and persevering very frequently, on average across OECD countries) (Table V.B1.3.20).
Less than half of students frequently engage in self-reflective practices such as explaining how to solve a mathematics problem and explaining the reasoning involved in solving it, on average across OECD countries. Interestingly, students who face difficulties in the classroom perceive these strategies differently than more skilled students. On average, about 40% of low performers reported that their teachers use cognitive activation practices that require them to think about how problems are solved and their reasoning. Conversely, over half of skilled performers reported that their teachers do the same (Table V.B1.3.23). These results highlight important aspects of classroom teaching and learning. Low-performing students reporting less exposure to cognitive activation suggests that some systems adapt teaching practices for different performance levels. In a similar vein, low and skilled performers may be segregated in some systems and the exposure to these practices may, indeed, be different. This could also indicate, however, that low-performing students are less likely to recognise cognitive activation components in teaching even when they are as exposed to them as their skilled peers. Interestingly, students in Peru reported this self-reflective practice the most (60%), with very similar shares of low and skilled performers (59% and 63%, respectively) (Figure V.3.5b [available online] and Table V.B1.3.23).
Mean score in mathematics
Notes: Score-point difference between students with more cognitive activation in mathematics and those with less that are statistically significant are shown in a darker tone (Annex A3). Students who reported less (more) frequent cognitive activation in mathematics are those in the bottom (top) quarter of the index of cognitive activation in mathematics in their own country/economy.
Countries and economies are ranked in ascending order of the difference in score between students with more frequent cognitive activation in mathematics compared to those with less.
Source: OECD, PISA 2022 Database, Table V.B1.3.31. See Table V.3.1 for StatLink at the end of this chapter.
Explicitly connecting new learning to existing knowledge may require reinforcement, especially for low performers
Some examples of cognitive activation practices that are relevant for self-directed learning are teachers frequently asking students to think about how new and old mathematics topics are related (31%, on average across OECD countries). Another is teachers frequently asking students to think about how to solve mathematics in different ways than demonstrated in class (37%) (Table V.B1.3.20). What is interesting about frequently asking students to think about how new and old mathematics topics are related is that roughly the same percentage of both low and skilled performers, on average across OECD countries, reported that their teachers do this: slightly more than 30%. This is particularly important as few low performers said they proactively do this, suggesting that low performers may struggle to internalise this strategy (see Chapter 2). Finally, on average, slightly above 36% of both skilled and low-performing students reported their teachers frequently ask them to think about how to solve mathematics problems in different ways than demonstrated in class (Tables V.B1.3.27 and V.B1.3.29). Peru, again, stands out as a country where students not only reported frequent teacher prompting but by similar proportions of low and skilled performers, suggesting these practices are more homogeneously integrated and implemented than in other education systems.
These findings have potential implications for sustained learning. Figure V.3.5 shows how students in most countries and economies who reported that their teachers frequently use cognitive activation practices3 outperformed those who reported that their teachers use it less frequently (by 21 score points on average, across OECD countries).
Students with a strong grounding in cognitive activation are better prepared to keep learning past their school years
As with proactive study behaviours, a way to understand how cognitive activation relates to lifelong learning is to observe the types of tasks students are able to handle at each end of the cognitive activation index. About half of countries on the right panel of the figure show differences of at least one proficiency level between students who reported more and less exposure to cognitive activation practices. For instance, in the United Arab Emirates, students reporting the most frequent exposure to cognitive activation practices from their teachers could typically handle Level 2 tasks, which is considered the baseline for mathematics proficiency. Students reporting the least exposure often scored below this level. At the opposite end, in Peru, both groups scored below Level 2: the difference remains significant although the gap between the two ends appears small (Figure V.3.5).
These analyses suggest that the relationship between cognitive activation and academic proficiency is positive and statistically significant on average across OECD countries and among most countries and economies for all students regardless of their proficiency level (Table V.B1.3.30).
Students who reported more exposure to cognitive activation practices may be better prepared for sustained learning as they have a double benefit: an increase in their capacity to use metacognitive strategies (e.g. to do better planning, monitoring, and evaluating of one's own understanding as well as to transfer practices to enhance learning effectiveness) and, simply, better mathematics skills.
Skilled achievers may make better use of cognitive activation practices, but they can be beneficial for all students if adapted to their needs. Exposure to cognitive activation practices can enable students to be active agents in their own learning. This creates the foundation for methodical and transferable reasoning, a hallmark of sustained lifelong learning.
PISA data on gender differences in the use of specific learning strategies reveal interesting findings. Boys often reported more exposure to cognitive activation practices than girls (Table V.B1.3.21). This suggests that boys and girls may perceive learning strategies differently.
Gender differences can also be seen in how girls and boys reported strategies for sustained learning analysed in Chapter 2. Girls consistently exhibit higher control and self-monitoring strategies, particularly in checking for mistakes and reviewing homework before submission. Among skilled performers, girls outstrip boys by 8 percentage points in checking for mistakes and 14 percentage points in checking homework, on average across OECD countries. Among low performers, these differences are 7 and 10 percentage points, respectively (Table V.B1.3.48).
However, there is no significant gender difference on the matter of students asking questions when they do not understand the mathematics being taught in most countries and economies. Among skilled performers, the gender gap is not significant in most countries and economies either. For low performers, the gap is slightly significant in favour of girls in 19 out of 22 countries (from 4 to 12 percentage points) (Table V.B1.3.48).
In terms of critical thinking (perspective-taking), girls generally reported stronger abilities in assimilating multiple viewpoints before taking a position. Among skilled performers, girls outstripped boys by 8 percentage points in terms of considering everyone's perspective and 5 percentage points in being able to see things from different angles, on average across OECD countries. For low performers, these gaps increase to 11 and 9 percentage points, respectively. Additionally, girls were more likely to disagree with the notion that there is only one correct position in a disagreement, with gaps favouring girls by an average of 14 percentage points among skilled performers and 7 percentage points among low performers (Table V.B1.3.49).
Overall, these findings emphasise the need for tailored educational strategies that address the specific strengths and weaknesses of both genders, fostering an equitable learning environment that supports the development of strategies for sustained learning for all students (OECD, 2015[17]).
Creative school and class environment
Imagination and creativity significantly shape students' educational experiences and future career trajectories (Gotlieb et al., 2019[18]). A creative person generates novel ideas and formulates original solutions, and the process of implementing and refining these ideas in learning is dynamic (Beghetto and Schuh, 2020[19]). The focus should not merely be imparting knowledge but cultivating students’ ability to think innovatively.
The enduring link between creativity and problem-solving has been a subject of scholarly interest for many decades (Weisberg, 2006[20]). While a detailed discussion of creativity is presented in a separate volume (OECD, 2024[21]), the focus here is on creativity's role in enhancing students’ preparedness for lifelong learning, especially in problem‑solving. On average, across OECD countries, over 60% of students reported that teachers give them enough time to come up with creative solutions on assignments; activities students do in class help them think about new ways to solve problems; and that mathematics assignments require students to come up with different solutions for a problem (Table V.B1.3.32). When looking at responses to the latter two questions, which focus explicitly on finding new ways to solve problems, skilled and low performers reported over 60% on average (Tables V.B1.3.35 and V.B1.3.37). This suggests a broad emphasis on creative problem-solving overall.
Notably, PISA 2022 data show that students who reported more creative problem-solving activities do not always show positive relationships with learning outcomes like mathematics performance. In a number of countries/economies, the relationship is non-significant or even, negative (Table V.B1.3.38).
These findings suggest that different educational systems have different standards and practices in creative problem-solving activities. In some educational systems, they might be heavily integrated into the curriculum and teaching methods; in others, it may be less emphasised or implemented in a more fragmented way (Wyse and Ferrari, 2014[22]). Educational policies also support creative environments to very different extents. Further PISA analyses are needed to better understand how creative environments positively influence other learning outcomes, such as performance in mathematics. (c.f. Volume 3, PISA 2022 Results).
As shown in previous PISA reports (OECD, 2023[23]), social and emotional skills (SES) such as persistence, curiosity, co-operation, stress resistance and emotional control play a central role in shaping students' learning processes. PISA 2022 results confirm existing research showing that SES not only contribute to academic performance but support the development of lifelong learning habits by fostering resilience and adaptability (Poulou, 2007[24]) (Durlak et al., 2011[25]).
PISA 2022 data highlight the relationship between SES and learning strategies for sustained lifelong learning. Key findings show that persistence is the strongest driver among the SES analysed in this report. Students with higher levels of persistence are more adept at using a variety of learning strategies, regardless of their socio-economic profile or mathematics performance. For example, with a one-unit increase in the persistence index, students are twice as likely to carefully check their homework before handing it in and almost as likely to be meticulous with their schoolwork. This relationship is particularly strong in Bulgaria and Hong Kong (China)*. Persistent students are also more proactive, particularly in engaging with new material by relating it to previous lessons, especially so in Australia*, where persistent students are almost twice as likely to engage in such practices. This proactive approach is a hallmark of effective and sustained learning (Table V.B1.3.56).
Curiosity and co-operation also play important roles. Curious and co-operative students show a high propensity for thoroughness in their learning across different countries/economies. These students, along with those who manage their emotions well, are more likely to proactively engage with new material, relate it to prior knowledge and thereby deepen their understanding (Table V.B1.3.60).
Likelihood of reporting using learning strategies for each the following social and emotional skills, after accounting for students' and schools' socio-economic profile, and students' performance in mathematics; OECD average
Notes: All odds ratio coefficients are statistically significant (see Annex A3).
The socio-economic profile is measured by the PISA index of economic, social and cultural status (ESCS).
Source: OECD, PISA 2022 Database, Tables V.B1.3.56-V.B1.3.60. See Table V.3.1 for StatLink at the end of this chapter.
Critical thinking is another area where SES are crucial. Co-operative students, across the countries and economies surveyed, are the most likely to consider multiple perspectives before forming their own opinions. Interestingly, this relationship is particularly strong in high-performing systems such as Hong Kong (China)*, Korea, Singapore and Chinese Taipei, suggesting a strong cultural and educational emphasis on co-operative learning and considering multiple perspectives. This approach to education may help students to develop a more nuanced and comprehensive understanding of complex issues. Curious and persistent students also tend to embrace this integrative approach, highlighting the interplay between these skills and critical thinking (Table V.B1.3.57).
Conversely, while students with higher stress resistance are, on average across OECD countries, less likely to check their homework carefully, the relationship is not significant in many countries/economies. This interesting finding suggests that stress-resilient students rely more on their innate abilities and confidence in their understanding of the material, reducing the perceived need for meticulous checking of homework. In contrast, students with lower stress resistance may be more anxious about their performance and check their homework more carefully. In addition, in about half of the countries/economies surveyed, stress resistance is not related to proactive learning behaviour or to the ability to consider multiple perspectives (Table V.B1.3.59).
Finally, emotional control, while relating positively to meticulousness and perspective-taking, on average across OECD countries, shows a non-significant relationship in several countries/economies and even a negative relationship in some cases. Interestingly, emotional control is positively related to the belief that there can be more than one correct position in a disagreement, on average and across countries and economies. While the relationship is likely to be non-linear, the question remains whether maintaining emotional control might allow individuals to be more flexible and open to conflicting perspectives (Table V.B1.3.58).
As shown throughout this report, SES are highly relevant to students’ autonomous learning and confidence in their learning. Persistence, in particular, shows interesting relationships with almost all sustained learning behaviours. Yet, as the OECD’s Survey on Social and Emotional skills has shown, there can be important differences in SES across gender, age and socioeconomic groups (OECD, 2024[26]). Understanding the nuanced relationship between these skills and students' approaches to learning is essential for developing targeted education policies that can close learning gaps. As such, analysis of the PISA 2022 data on the relationship between SES and learning strategies provides valuable insights into how these skills can be nurtured to support all students in reaching their full potential.
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← 1. Intrinsic motivation refers to doing an activity for its inherent satisfaction or enjoyment, rather than for some identifiable outcome. Extrinsic or instrumental motivation, on the other hand, involves doing a task to obtain an external reward or even to avoid punishment. This type of motivation is driven by external factors such as grades, money, opportunities or recognition.
← 2. PISA 2022 asked students whether they agreed (“strongly disagree”, “disagree”, “agree”, or “strongly agree”) with the following statement: “Your intelligence is something about you that you can’t change very much”. Disagreeing with the statement is considered a precursor of a growth mindset as it is more likely that someone who thinks intelligence can change will challenge him/herself to improve it. To measure a growth mindset towards mathematics specifically, PISA 2022 asked students whether they agreed with the statement “Some people are just not good at mathematics, no matter how hard they study”. As with the first statement, disagreeing with the statement is considered a precursor of a growth mindset in mathematics. However, analyses based on this second question should be interpreted with caution. The fact that the question is not centred on the respondent but asks their judgement about 'some people' changes the interpretation of a growth mindset to some extent. It is possible that some students may experience difficulties with mathematics regardless of their study practices (for example, students with certain types of learning needs or challenges). In such cases, the question and statement could be interpreted as true and still not be inconsistent with a growth mindset. Yet, the object of analysis in this chapter is the preconceived notion that some students may have about learning mathematics in general and their belief that it is possible to be better at mathematics by studying hard.
← 3. The relationship is based on the index of cognitive activation in mathematics to foster reasoning. Countries and economies with the highest index are those in which more students reported that teachers frequently ask them to think about how new and old mathematics topics are related; to engage in self-reflective practices explaining how a mathematics problem was solved and their reasoning; and to think on how to solve a mathematics problem in different ways, among other activities.