The question the team posed is deceptively simple: when people teach, are they reasoning about another mind, or merely executing a routine? Psychologists have long regarded teaching as a foundational social behavior, one that underpins education, culture and the transmission of knowledge across generations. But the cognitive machinery behind it has remained opaque, because teaching can be accomplished in two very different ways. It can be performed optimally, through mentally effortful reasoning that treats the learner as a mind to be modeled. Or it can be performed frugally, through heuristics that demand little thought and no mentalizing at all. Debates about when humans deploy expensive planning rather than inexpensive habits usually unfold over nonsocial tasks: choosing between rewards, navigating mazes, pressing keys. Teaching offers an unusually clean test case, because the two routes leave measurably different fingerprints in the examples a teacher selects. The researchers set out to establish which route people naturally take, whether they abandon a failing strategy when circumstances change, and what it takes to make them switch.

Experiment 1, with 100 participants, delivered the study’s first surprise: teaching strategies are not a matter of degree but of kind. Participants took the role of teachers, selecting examples to convey a concept to a learner whose knowledge they could not directly observe. The researchers then fitted a family of computational models to each individual’s choices, asking which algorithm best reproduced the observed behavior. For some participants, the best-fitting account was an optimal Bayesian pedagogy model, in which the teacher explicitly reasons about the state of the learner’s knowledge before choosing what to show. For others, the best-fitting account was a set of simple heuristics that require no mentalizing whatsoever — rules of thumb that select plausible-looking examples without ever computing what the learner believes. Crucially, both groups faced the same task, the same instructions and the same information. The difference lay not in what they knew or how well they taught, but in how their minds chose to spend their cognitive budget. Teaching, it turns out, has personality.

To appreciate why that split matters, it helps to unpack what Bayesian pedagogy demands. In this framework, teaching is a recursive act of mutual inference. The teacher maintains an internal model of the learner’s current beliefs — a probability distribution over the rules the learner considers plausible — and then runs a counterfactual simulation for every candidate example: if I show this, and the learner understands that I am deliberately trying to teach, how likely are they to update their beliefs toward the correct rule? The optimal teacher selects the example with the highest expected payoff, the greatest probability of steering the learner’s inference toward the truth. This is heavy cognitive lifting. It requires holding a representation of another person’s mental state in working memory, predicting how that state will change with each new piece of evidence. Cognitive scientists call reasoning about other minds mentalizing, and it ranks among the most demanding computations the social brain performs. The Bayesian teacher is the cognitive equivalent of a chess player who calculates several moves deep while simultaneously modeling the opponent’s style.

The heuristics, by contrast, are mentally frugal. A heuristic-driven teacher might simply pick examples that are themselves excellent specimens of the concept, on the intuitive logic that good examples make good teaching, without checking whether those examples tell this particular learner anything new. Another might repeat instances that worked earlier, or choose items resembling previously successful ones, letting past performance rather than the learner’s current understanding drive the next choice. Such rules can perform respectably in many situations, which is why they persist. But they are fundamentally blind: they never represent the learner’s knowledge, so they cannot detect that the learner has already grasped a point, nor can they recognize a misconception the teacher is unwittingly reinforcing. It is the difference between a physician who orders tests based on a patient’s specific symptoms and one who orders the same standard battery for every patient who walks through the door. The first is expensive but tailored; the second is cheap but indifferent to the very person it serves.

Then came the study’s sharpest test. In a preregistered Experiment 2 with 253 participants, the researchers altered the teaching environment so that the heuristic no longer worked — conditions in which blindly applying the shortcut would steer the learner astray. If people were flexible strategists who adjusted their cognitive spending to circumstances, they should have abandoned the failing heuristic and switched to mentalizing. They did not. Participants persisted in using the now-ineffective shortcut, a statistically robust effect (P < 0.001; rank-biserial correlation r = 0.287, 95% confidence interval 0.149 to 0.419). The rank-biserial statistic, an effect-size measure for two-group comparisons, points to a small-to-medium but highly reliable tendency. In plain terms, even when the cheap strategy stopped paying off, people kept deploying it, apparently because it remained the path of least resistance. The result echoes a familiar theme from research on habits: behaviors that economize on effort become sticky, and a track record of past success is enough to keep a strategy alive long after its expiration date.

The third experiment, preregistered and by far the largest, with 759 participants, showed that this stickiness can be broken — not by urging people to try harder, but by scaffolding the expensive step itself. Participants received an auxiliary task that supported their inference about what the learner knew, effectively lowering the cognitive cost of mentalizing. With that inference partially externalized, the tendency to persist with heuristics was pre-empted: participants shifted toward reasoning about the learner’s knowledge when choosing their teaching examples (P < 0.001; partial ηp² = 0.107, 95% confidence interval 0.068 to 0.148, a medium-sized effect in this design). The barrier to thoughtful teaching was not a lack of ability but a question of cost. When the price of representing the learner’s mind dropped, people paid it, and their teaching changed accordingly. Mentalizing, the study suggests, is not a fixed capacity that some possess and others lack; it is a resource that people purchase when its price falls or its expected payoff rises.

Taken together, the three experiments reveal what the authors describe as “sophisticated arbitration between planning and heuristics during teaching.” The mind appears to run something like a cost–benefit calculation over its own cognitive effort: mentalizing buys accuracy in transmitting knowledge, but it is expensive, so the cognitive system rations it. Heuristics are the economy class of teaching — cramped, limited, but affordable. Individual differences in Experiment 1 show that people price the trade-off differently, with some defaulting to first class and others to economy. Experiment 2 shows that once a cheap strategy is running, it resists shutdown even in the face of clear evidence of failure. Experiment 3 shows that the pricing is not fixed but responsive to context: change the cost structure, and the strategy follows. The findings extend dual-process accounts of cognition — the interplay of fast, automatic and slow, deliberate thinking — into the social domain, where the slow, deliberate option is specifically the construction of a model of another mind.

The implications radiate well beyond the laboratory. In education, a teacher relying on heuristics may deliver polished, reasonable-looking lessons while never noticing that a student’s misconception is quietly being reinforced. This research suggests that tools which surface a learner’s actual state of knowledge — diagnostic feedback, formative assessment, structured insight into what students do and do not understand — could shift even shortcut-prone teachers toward genuinely adaptive instruction. In human–AI interaction, the same asymmetry grows by the year: people now teach machines constantly, from recommendation algorithms to household robots to large language models, and whether they do so with or without mentalizing may determine how quickly and how well those systems learn from the examples people supply. For theories of bounded rationality, the work adds a social dimension to a long-standing principle: intelligence is not about always thinking harder, but about deploying hard thinking precisely where it changes outcomes.

The authors frame their contribution as demonstrating just such arbitration and elucidating “the more general mechanisms involved in adapting mental effort during social interactions” — a framing that positions teaching not as a special talent reserved for gifted educators but as a window onto how any mind manages its cognitive budget in the presence of another person. The natural next questions follow directly from the design. When in development do individuals settle into their pricing schemes for mental effort, and how durable are those schemes across the lifespan? Does the same arbitration govern other social behaviors — cooperation, conversation, deception — where modeling another mind is likewise optional but consequential? And can such scaffolding be scaled from a laboratory task to classrooms, workplaces and the algorithms humans increasingly find themselves teaching? What is already clear is that the gulf between a heuristic teacher and a mentalizing teacher is not a gulf of talent. It is a gulf of effort — and effort, this research shows, can be moved.

The fundamental premise of highlighting is straightforward: it encourages readers to identify and emphasize key information as they engage with a text. The simple act of marking critical phrases or sentences can transform a passive reading experience into an interactive one, fostering better retention and understanding of the material. However, the ways in which students utilize highlighting can vary significantly, not only from individual to individual but also across different educational systems and cultures.

The research presents compelling evidence suggesting that the effectiveness of highlighting strategies may differ vastly between countries, thereby contributing to measurable gaps in reading achievement on international assessments. By analyzing data accumulated from various educational contexts, Anghel and von Davier establish a connection between highlighting practices and reading comprehension levels, inviting educators and policymakers to reconsider how they approach literacy instruction on a global scale.

This study scrutinizes various factors influencing the use of highlighting, including teaching methodologies, curriculum designs, and the availability of resources. Those elements play critical roles in shaping how students approach reading tasks and, subsequently, their performance in standardized assessments of reading proficiency. For instance, in educational environments where explicit instruction on effective highlighting techniques is prevalent, students tend to perform better on reading comprehension tests compared to those in systems where such guidance is lacking.

Moreover, this research prompts educators to reflect on their own pedagogical practices. Highlighting, while simple, is not necessarily intuitive. Many students may not instinctively know which parts of a text to emphasize, resulting in ineffective highlighting that does little to aid comprehension. As such, targeted instruction—teaching students not only what to highlight but also how to analyze texts critically—could bridge gaps in reading achievement.

One significant outcome of the study reveals that students who employ highlighting effectively tend to display higher levels of engagement with the material. This engagement is particularly vital in an educational landscape increasingly influenced by technology and digital content, where distractions abound. The ability to sift through information and concentrate on salient details is an invaluable skill that transcends academic settings, preparing students to navigate the complexities of modern informational ecosystems.

Additionally, the study explores the cultural dimensions of highlighting practices. Certain educational cultures may prioritize rote memorization or standardized test performance over comprehension strategies, potentially stunting the development of critical thinking and analytical skills. Nations that emphasize a more holistic approach to education may find that fostering effective highlighting techniques contributes not only to improved reading scores but also to the development of well-rounded thinkers and problem solvers.

The implications of these findings are profound, extending beyond theoretical discussions into practical applications. For policymakers aiming to enhance reading achievement and educational equity, integrating effective highlighting instruction into literacy curricula could be a game-changer. Such enhancements could lead to a more significant focus on metacognitive strategies that empower students to take control of their learning, illustrating that mastery of reading is not merely about decoding words but also about understanding and interacting with content.

In a world where educational achievement is increasingly assessed through international benchmarks, understanding the subtleties of reading strategies like highlighting is crucial. The disparities highlighted by Anghel and von Davier’s research serve as a clarion call for educators and administrators alike to prioritize effective reading strategies in curricula. By doing so, we may not only enhance standardized test scores but also equip future generations with the skills necessary for lifelong learning.

As educators face the challenge of adapting instructional methods to the needs of diverse learners, this research acts as a guiding light. Emphasizing comprehension strategies rooted in cognitive psychology, like highlighting, encourages an approach to literacy that values individual differences and promotes broader understanding. This could lead to internationally comparable reading achievements that reflect genuine comprehension rather than mere memorization of facts.

The analysis also raises vital questions about the resources and training available to educators. Teacher preparation programs must evolve to include training on strategies like highlighting that support critical thinking and literacy skills. Investing in professional development that emphasizes innovative instructional practices can yield long-term benefits not only for academic performance but also for the overall efficacy of the educational system.

In conclusion, Anghel and von Davier’s research offers an essential perspective on an often-overlooked aspect of reading achievement. By shining a light on the highlighting divide, they underscore the vital connection between comprehension strategies and academic success. As we navigate the complexities of educating a diverse student population, it is imperative that we embrace evidence-based teaching practices that promote meaningful engagement and lasting understanding.

As the conversation around educational equity and literacy continues to evolve, it will be exciting to see how such research translates into tangible changes within classrooms around the globe. The quest for improved reading proficiency is not merely an academic exercise; it is fundamental to fostering informed, engaged citizens who can contribute thoughtfully to society at large.

By addressing the underlying factors contributing to disparities in educational outcomes, we have a unique opportunity to create more equitable learning environments that empower students to thrive irrespective of their cultural or geographic contexts.

Subject of Research: The relationship between highlighting strategies and international gaps in reading achievement.

Article Title: The highlighting divide: does highlighting strategy help explain international gaps in reading achievement?

Article References:
Anghel, E., von Davier, M. The highlighting divide: does highlighting strategy help explain international gaps in reading achievement?.
Large-scale Assess Educ 13, 6 (2025). https://doi.org/10.1186/s40536-025-00241-2

Image Credits: AI Generated

DOI: https://doi.org/10.1186/s40536-025-00241-2

Keywords: reading comprehension, highlighting strategies, educational equity, literacy instruction, international assessments.

Word problems can often be daunting for students, as they require the translation of textual information into mathematical expressions and operations. This transformative cognitive process involves various skills, including comprehension, logical reasoning, and mathematical application. Through the meta-analysis conducted by Peng and colleagues, the researchers sought to assess different strategies employed in tackling these problems, evaluating their effectiveness in various educational settings and contexts.

Peng and their team meticulously analyzed existing research to create a comprehensive picture of how different strategies perform in educational contexts. The study brought to light the various standalone strategies—such as visualization, story mapping, and the staging of questions—as well as hybrid strategies that combine two or more approaches. The significance of hybrid strategies was particularly emphasized, as they offer a multifaceted approach to problem-solving that can cater to diverse learning styles.

One of the key findings of the meta-analysis was the effectiveness of strategy combinations over isolated methods. When students engaged in using both visual representations and structured problem-solving methodologies, their success rate in correctly solving word problems increased significantly. This revelation resonates deeply with educators who have long advocated for differentiated instruction tailored to diverse learner needs. It further reinforces the notion that flexible thinking in mathematics can enhance student engagement and comprehension.

For educators and school administrators alike, the data derived from this study provides invaluable insights into instructional design. Understanding which strategies can be combined effectively to improve student outcomes allows for a more strategic approach to curriculum development. By integrating successful word-problem strategies into everyday lesson plans, educators can create an environment where students not only learn mathematics but also develop resilience and adaptability in their problem-solving approaches.

Furthermore, the review revealed the necessity for professional development and training among teachers on these identified strategies. Educators must be equipped with the knowledge and skills needed to implement these strategies effectively in classrooms. Continuous professional development ensures that teachers are not only aware of the latest educational research but are also adept at applying these strategies in practice, making them champions of effective teaching methodologies.

Another noteworthy point highlighted in the study was the role of assessment. Traditional assessments often focus solely on final answers, which misses the opportunity to evaluate students’ reasoning processes and strategy application. By developing assessment tools that emphasize strategy use, educators can gain better insight into students’ understanding and reasoning, informing future instruction and intervention strategies.

The findings also raise questions about the applicability of these strategies across various age groups and educational backgrounds. As the research continues to unfold, it will be essential to conduct further studies that investigate these strategies’ effectiveness across diverse populations, including students with learning disabilities and those for whom English is a second language. Understanding how these factors influence strategy effectiveness will be crucial for developing inclusive educational practices.

Moreover, Peng et al.’s comprehensive analysis has the potential to spark further research into other areas of mathematics education, beyond word problems. The integration of technology in problem-solving strategies is one such area ripe for exploration. As digital tools increasingly become part of the educational landscape, investigating how they can enhance traditional strategies or contribute to new hybrid methods could yield significant benefits for contemporary classrooms.

The implications of this research extend beyond the classroom. Enhanced problem-solving abilities have far-reaching effects on students’ overall academic success and can lead to increased self-confidence and a positive attitude toward mathematics. Buildings of knowledge constructed through effective problem-solving strategies serve as a foundation for future learning, reinforcing the importance of early engagement in mathematical practices.

Through this systematic review and network meta-analysis, Peng and their team are not merely contributing to academic discourse; they are challenging educators to rethink their approach to teaching mathematics, urging them to consider the unique needs of their students and to explore the intricate relationships between various problem-solving strategies. This work adds a valuable layer to our understanding of pedagogical effectiveness in mathematics education, positioning it as a critical area for ongoing inquiry and innovation.

In summary, the exploration of word-problem strategies and their combinations provides a robust framework that underscores the importance of strategic and flexible problem-solving approaches in mathematics education. As we continue to unravel the complexities of effective teaching strategies, the findings from Peng et al. offer a beacon of hope for both students and educators striving for excellence in learning outcomes.

Subject of Research: Effectiveness of Word-Problem Strategies and Strategy Combinations in Mathematics Education

Article Title: Exploring the Effectiveness of Word-Problem Strategy and Strategy Combinations: A Systematic Review and Network Meta-Analysis

Article References:

Peng, P., Liu, Y., Li, S. et al. Exploring the Effectiveness of Word-Problem Strategy and Strategy Combinations: A Systematic Review and Network Meta-Analysis.
Educ Psychol Rev 37, 81 (2025). https://doi.org/10.1007/s10648-025-10057-9

Image Credits: AI Generated

DOI: 10.1007/s10648-025-10057-9

Keywords: Word Problems, Problem Solving Strategies, Strategy Combinations, Mathematics Education, Systematic Review, Network Meta-Analysis