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.

At the heart of this investigation lies the concept of teacher agency, which refers to the capacity and autonomy of educators to make decisions regarding their teaching practices. In an educational environment increasingly influenced by digital technology, supporting teacher agency becomes essential. Ethical leadership plays a critical role in this context, guiding educators to navigate complexities and challenges associated with integrating technology into their pedagogical approaches. These leaders foster an environment of trust and collaboration, enabling teachers to exercise their professional judgment without fear of repercussions.

The study meticulously outlines the definition and dimensions of ethical leadership, emphasizing the importance of moral principles within educational leadership. Ethical leaders are characterized by their commitment to fairness, integrity, and accountability. They model behavior that encourages ethical conduct among their staff and promote a culture that prioritizes student welfare. The authors argue that this moral foundation is essential for creating an inclusive environment where all educators feel empowered to innovate and experiment with digital tools and resources.

Moreover, the analysis delves into the transformative potential of digital pedagogical innovation. As technology becomes an integral part of the learning experience, educators must adapt their methodologies to leverage these advancements effectively. The authors highlight instances where ethical leadership has successfully facilitated such adaptations, illustrating how leaders can inspire teachers to explore new pedagogical strategies that enhance student engagement and learning outcomes. The intersection of ethical leadership and digital innovation reveals a promising pathway for improving educational practices while fostering inclusivity.

In practical terms, the study emphasizes the necessity of professional development opportunities that align with teachers’ needs and aspirations. Ethical leaders are tasked with ensuring that their staff receives adequate training to become proficient in utilizing digital tools for instruction. By investing in professional growth, these leaders not only enhance the technical skills of their teachers but also reinforce a culture of inquiry and innovation. This continuous support is crucial for nurturing a workforce that is adaptable and ready to embrace the advancements in digital education.

The research also addresses the challenges that educators face as they seek to integrate technology into their pedagogical practices. Resistance to change, lack of resources, and inadequate training can hinder the effective implementation of digital innovations. However, by fostering a supportive and ethical leadership framework, institutions can cultivate resilience among teachers. Ethical leaders can mitigate these barriers by actively addressing concerns, providing necessary resources, and encouraging a collaborative approach towards overcoming obstacles. This proactive stance is vital for maintaining momentum in the pursuit of inclusive digital pedagogical practices.

In addition to practical implications, the study underscores the significance of inclusivity in educational contexts. As digital tools become prevalent, it is imperative that they are accessible to all students, regardless of their backgrounds or needs. Ethical leaders must advocate for equity in educational technology, pushing for resources that ensure every student has the opportunity to thrive in a digital learning environment. This commitment to inclusivity resonates with the broader ethical responsibilities of educators and leaders, highlighting the transformative potential of education as a vehicle for social change.

Throughout their analysis, the authors utilize qualitative research methods, including interviews and case studies, to gather insights from educational practitioners. This rich data informs their conclusions about the pivotal role of ethical leadership in fostering both teacher agency and digital pedagogical innovation. By grounding their findings in real-world experiences, Mphatsoane-Sesoane and Jita offer a compelling narrative that resonates with educators and policymakers alike, beckoning them to reconsider their approaches to leadership and innovation.

As the educational landscape continues to adapt to the demands of the digital age, the findings from this research hold valuable lessons for stakeholders at all levels. Ethical leadership serves as a cornerstone for building a resilient educational community, one where teachers feel empowered to explore innovative practices that enhance teaching and learning. The call to action is clear: leaders must embrace ethical principles in their leadership practices to cultivate an environment conducive to experimentation and growth.

In conclusion, the analysis of ethical leadership in the context of teacher agency and digital pedagogical innovation provides a fresh perspective on the complexities of modern education. By emphasizing the interconnections between leadership, teacher empowerment, and inclusivity, Mphatsoane-Sesoane and Jita contribute significantly to the ongoing discourse on educational reform. Their findings resonate with the urgent need for ethical stewardship in education, ensuring that innovation is pursued in ways that benefit all students and support teachers in their vital role as agents of change.

As educational institutions continue to navigate the challenges of diverse learning environments and technological advancements, the principles laid out in this research will undoubtedly serve as a guiding light. By prioritizing ethical leadership, educators can create transformative learning experiences that prepare students for success in an increasingly complex world.

The findings of this study pave the way for future research to explore the nuances of ethical leadership further, potentially uncovering additional strategies for fostering teacher agency and innovating inclusive digital pedagogical practices. As educators strive to meet the ever-evolving demands of their profession, the insights offered in this analysis will remain relevant, serving as a critical foundation for educational leaders committed to ethical practices and digital literacy.

Subject of Research: The role of ethical leadership in fostering teacher agency for inclusive digital pedagogical innovation

Article Title: Analysing the role of ethical leadership in fostering teacher agency for inclusive digital pedagogical innovation.

Article References:Mphatsoane-Sesoane, L., Jita, L.C. Analysing the role of ethical leadership in fostering teacher agency for inclusive digital pedagogical innovation.
Discov Educ 4, 493 (2025). https://doi.org/10.1007/s44217-025-00944-2

Image Credits: AI Generated

DOI: https://doi.org/10.1007/s44217-025-00944-2

Keywords: Ethical leadership, teacher agency, digital pedagogical innovation, inclusivity, education reform.