# Interleaved versus blocked practice in skill acquisition

## Introduction to the Paradigm of Desirable Difficulties

The architecture of human learning and memory is fundamentally counterintuitive. For decades, instructional design across global educational systems has been dominated by the assumption that the most effective way to acquire a new skill or conceptual framework is through massed, focused repetition. This approach, widely known as blocked practice, dictates that a learner must practice a single procedure repeatedly until mastery is achieved before moving on to the next topic [cite: 1, 2, 3]. Blocked practice forms the structural backbone of modern educational curricula, training programs, and textbooks, operating under the logical but empirically flawed premise that isolated focus reduces confusion and accelerates learning [cite: 2, 3, 4]. However, foundational research in cognitive psychology, spearheaded by scholars such as Robert Bjork and Doug Rohrer, has systematically dismantled this assumption over the past several decades [cite: 1, 2, 3]. They introduced the foundational concept of "desirable difficulties," proposing that introducing specific, calibrated cognitive challenges during the encoding and practice phases of learning can significantly enhance long-term memory retention and the transfer of skills to novel, unpredictable situations [cite: 2, 3].

At the absolute core of this theoretical framework is the science of interleaving. Interleaved practice refers to a highly structured schedule of learning that mixes different, but related, kinds of problems or materials within a single study session, serving as a direct contrast to blocking them by topic [cite: 3, 4, 5]. To illustrate, rather than completing twenty mathematics problems that all require the application of the Pythagorean theorem followed by twenty problems requiring the quadratic formula (a blocked sequence: AAABBB), an interleaved sequence forces the learner to alternate continuously between the two (an interleaved sequence: ABABAB or ABCABC) [cite: 2, 6]. By actively preventing the learner from settling into a mindless, robotic rhythm of applying a single strategy, interleaving demands continuous cognitive engagement, evaluation, and strategy selection [cite: 2, 3, 4].

Recent advancements in cognitive science, particularly a surge of rigorous meta-analyses and large-scale classroom trials published between 2023 and 2026, have provided deeply nuanced insights into the efficacy, neurological mechanisms, and critical boundary conditions of the interleaving effect. While interleaved practice has been proven to double test scores in specific domains such as mathematics and visual categorization, its application is not a universally beneficial panacea [cite: 2, 3]. The efficacy of this pedagogical strategy is heavily mediated by the learner's baseline expertise, the intrinsic cognitive load of the learning material, and the developmental stage of the human brain [cite: 6, 7, 8]. Furthermore, expanding this research beyond traditional Western, Educated, Industrialized, Rich, and Democratic (WEIRD) populations has revealed vital contextual, infrastructural, and socio-economic variables that influence exactly how interleaved practice operates in diverse global settings [cite: 9, 10]. This report provides an exhaustive, expert-level analysis of the science of interleaving. It meticulously differentiates the practice from deleterious habits like multitasking, explores its neurocognitive foundations through the lens of recent fMRI evidence, and establishes precise, evidence-based guidelines for its implementation across varied domains and demographics.

## Conceptual Distinctions: Interleaving Versus Multitasking

A critical vulnerability in the widespread adoption and public understanding of interleaved practice is the frequent, erroneous conflation of interleaving with multitasking. Because both concepts inherently involve engaging with multiple subjects or tasks within a given timeframe, lay educators and learners often incorrectly assume that the proven benefits of interleaving justify rapid context-switching across completely unrelated domains. Cognitive science, however, draws a sharp, uncompromising distinction between the two phenomena based on cognitive load, attention distribution, and neurological architecture.

The cognitive architecture of multitasking is characterized by an attempt to perform two or more complex, unrelated tasks simultaneously, or engaging in rapid, unguided context-switching between them [cite: 11, 12]. The human brain lacks the true parallel processing capacity required to attend to multiple cognitively demanding tasks at once; instead, what is colloquially termed multitasking is actually rapid sequential task-switching [cite: 11, 13, 14]. This rapid switching incurs severe cognitive penalties known in the literature as "switch costs" [cite: 11, 15]. In the mid-1990s, foundational research by Robert Rogers and Stephen Monsell established that when an individual shifts attention from one task to a disparate task, the prefrontal cortex must undergo a massive reconfiguration process to abandon the operational rules of the first task and load the entirely new rule set of the second [cite: 11, 14]. This shift leaves behind an "attention residue," wherein fragments of the previous task's cognitive framework continue to occupy working memory, causing interference and drastically degrading performance on the current task [cite: 14, 16]. Extensive research, including heavily cited studies from Stanford University, indicates that heavy multitaskers perform demonstrably worse at filtering out irrelevant information and managing working memory compared to those who focus on a single task [cite: 14]. For the modern knowledge worker, who tends to interleave unguided tasks every two to ten minutes, this unstructured, random assortment of disconnected activities (e.g., attempting to study physics while writing an email and checking a mobile device) overwhelms executive function, impairs cognitive control abilities, and leads to productivity losses approaching 40% [cite: 11, 14, 15, 17, 18].



In stark contrast to multitasking, interleaving is a highly structured, deliberate, and sequential pedagogical strategy. It operates on the principle of discretionary task interleaving, where the learner works on only one task at a time, but the sequence of the practice tasks is algorithmically designed to force continuous retrieval and strategy selection [cite: 4, 18, 19]. The primary and most vital differentiator between the two is the concept of relatedness and discriminative contrast. Interleaving is effective precisely when the materials being mixed share underlying characteristics that make them easily confusable to the learner [cite: 3, 15, 17]. For instance, interleaving the physical practice of forehands, backhands, and volleys in tennis forces the motor system to rapidly adjust, recognize the incoming stimulus, and select the correct kinematic response [cite: 17]. Similarly, interleaving the study of mutually exclusive mathematical concepts forces the brain to thoroughly analyze the problem's deep structure before deploying a solution [cite: 2, 20]. Mixing completely unrelated tasks—such as cooking and solving calculus problems—does not constitute effective interleaved practice because there are no shared features to contrast, rendering the exercise nothing more than an induction of switch costs [cite: 17]. Multitasking is characterized by divided attention across disparate goals, whereas interleaving is characterized by undivided attention applied to a sequentially shifting, but conceptually cohesive, set of related problems [cite: 17, 19, 21].

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## The Illusion of Competence: Subjective Versus Objective Performance Gaps

One of the most profound barriers to the widespread institutional adoption of interleaved practice is the massive metacognitive disconnect it creates within the learner. This deeply entrenched psychological phenomenon, heavily documented by researchers like Robert Bjork and Nate Kornell, is known as the "illusion of competence" or the "metacognitive illusion" [cite: 2, 3]. 

The trap of blocked practice lies in the artificial fluency it generates. During a blocked practice session, a student encounters a long series of identical problem types. By the time they reach the third or fourth problem in the sequence, the specific strategy required to solve it is already highly activated and actively loaded into working memory [cite: 2, 4, 17]. The learner no longer has to evaluate the problem to determine *which* strategy to use; they only have to execute the mechanical procedure [cite: 4, 17]. This circumvention of the decision-making process creates a high level of immediate performance and a powerful, yet entirely false, sense of fluency [cite: 2, 3]. The student feels they are mastering the material quickly because their immediate error rate is exceptionally low. However, this fluency is highly deceptive. Because the solution strategy is temporarily held in short-term memory, the brain is not doing the neurocognitively demanding work of retrieving the information from long-term memory, nor is it learning how to identify the specific environmental or textual conditions under which that specific strategy applies [cite: 1, 2, 17]. Consequently, when the final test occurs days or weeks later, and the problems are inevitably presented out of order, the learner experiences catastrophic forgetting because the structural cues that were artificially present during blocked practice have been removed [cite: 1, 3].

Interleaved practice completely subverts this dynamic, introducing what Soderstrom and Bjork (2015) termed the critical distinction between "learning and performance" [cite: 1, 3]. Because each consecutive problem in an interleaved assignment requires a different strategy, the learner cannot rely on the rote repetition of the previous step [cite: 4, 17]. They must first analyze the problem, discriminate it from other confusable problem types, and actively retrieve the correct solution strategy from long-term memory [cite: 4]. This process is immensely cognitively taxing, resulting in significantly slower acquisition speeds and higher error rates during the practice phase itself [cite: 1, 20]. Subjectively, learners report feeling frustrated, confused, and utterly convinced that they are failing to learn [cite: 3]. 

This metacognitive illusion was beautifully demonstrated in a 2008 study by Kornell and Bjork at UCLA, where participants were asked to learn the painting styles of twelve obscure artists [cite: 3]. Half of the artists were studied in a blocked format (all paintings by one artist shown sequentially), and half were interleaved. On a subsequent transfer test featuring novel paintings by the same artists, interleaved study produced roughly 65% accuracy, dwarfing the 50% accuracy of blocked study [cite: 3]. Yet, when participants were surveyed regarding which method they believed was more effective, a staggering 78% confidently selected blocked practice, maintaining this belief even after being shown their own superior test scores from the interleaved condition [cite: 3]. The feeling of fluency during blocked practice was so psychologically overwhelming that it completely overrode direct empirical evidence of failure [cite: 3].



The objective performance gap between the two methods reverses dramatically over time, a phenomenon observed relentlessly in longitudinal trials. In a major 2020 pre-registered, randomized controlled trial conducted by Rohrer across 54 seventh-grade mathematics classes involving 787 students, the results were definitive. Students utilizing blocked practice saw their performance crash from high accuracy during the practice sessions to an abysmal 37% on tests delayed by one month [cite: 3]. Conversely, students utilizing interleaved practice scored 61% on the identical delayed transfer tests, yielding an enormous effect size of Cohen’s $d = 0.83$ [cite: 3].

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 The desirable difficulty of interleaving essentially immunizes the learner against forgetting because it mandates that the brain continuously practice the diagnostic phase of problem-solving alongside the execution phase [cite: 2, 4].

## Expanding Cognitive Mechanisms: From Behavioral Models to fMRI Evidence

To comprehend why interleaving produces such exceptionally robust long-term retention despite causing substantial short-term friction, it is necessary to examine the underlying cognitive theories and their corresponding neurobiological mechanisms. Recent advances in functional magnetic resonance imaging (fMRI) and advanced computational neural modeling have crystallized several competing, yet ultimately complementary, theories into a cohesive neurocognitive framework.

### The Discriminative-Contrast Hypothesis
Historically, the dominant cognitive explanation for the interleaving effect has been the discriminative-contrast hypothesis. When learning concepts or categories that are highly similar, they compete for the same representational space within the brain [cite: 6, 22]. If a learner studies all paintings by Monet and then subsequently studies all paintings by Manet (a blocked sequence), the shared features—such as impressionist brushstrokes and similar color palettes—blend together into an indistinct mental model [cite: 3, 22, 23]. However, if a Monet is immediately followed by a Manet, the brain's pattern-recognition systems are abruptly forced to notice the subtle discrepancies and boundary conditions that separate the two categories [cite: 3, 22, 23]. Interleaving directs attention explicitly to the distinguishing features, enabling the brain to build much more precise, differentiated, and highly stable cognitive schemas [cite: 20, 22]. This explains why interleaving is particularly potent when within-category similarity is low and between-category similarity is high [cite: 22, 23, 24].

### Forgetting-and-Reconstruction (Study-Phase Retrieval)
A secondary behavioral mechanism is the study-phase retrieval hypothesis, often referred to as forgetting-and-reconstruction, which intimately connects interleaving to the well-documented spacing effect. When disparate tasks are interleaved, the practice of any single specific skill is inherently distributed across time [cite: 2, 23, 25]. While the learner is executing task B and task C, the neural activation responsible for task A begins to decay. When the learner must eventually return to task A, they have partially forgotten the procedural steps. The brain must exert significant metabolic and cognitive effort to reconstruct the memory trace from long-term storage and reload the strategy into working memory [cite: 1, 25]. This cyclical process of forgetting and effortful reconstruction strengthens the synaptic connections exponentially, making subsequent retrieval much faster, highly reliable, and resistant to decay [cite: 22]. Researchers note that this depletion of working memory resources, followed by a recovery period, mirrors the physiological process of muscular hypertrophy [cite: 6, 25].

### Recent Neuroscientific and fMRI Evidence (2024–2026)
Recent neuroscientific investigations have moved aggressively beyond theoretical behavioral models to directly map the interleaving effect within the physical brain. These studies have unearthed paradigm-shifting data regarding how human brains encode and consolidate information.

A pivotal study utilizing resting-state fMRI demonstrated that interleaved practice initiates profound and enduring changes in memory consolidation [cite: 3]. Researchers measured brain activity in the hours immediately following a training session. They discovered that interleaved practice led to significantly greater functional connectivity within the fronto-parietal networks during periods of rest and sleep compared to blocked practice [cite: 3]. Furthermore, using advanced psychophysiological interaction analysis, they observed sustained functional connectivity between the dorsolateral prefrontal cortex (DLPFC)—the critical hub of executive control, attention regulation, and strategy selection—and the premotor areas for up to 72 hours post-practice [cite: 3]. This explicitly suggests that interleaving permanently binds the executive decision-making process ("which strategy do I need to use?") to the execution process ("how do I perform it?"). Blocked practice completely failed to produce this sustained neural coupling [cite: 3].

Adding deeper nuance to these connectivity findings, a 2025 study from the Technical University of Munich (TUM) and the Friedrich-Alexander-University (FAU) challenged long-standing, foundational assumptions about fMRI Blood-Oxygen-Level-Dependent (BOLD) signals during intense learning tasks [cite: 26, 27]. Researchers Samira Epp and Valentin Riedl found that in up to 40% of cases, an increased fMRI signal was actually associated with *reduced* neural activity [cite: 26]. They discovered that brain regions facing exceedingly high cognitive demand—such as the default mode network attempting to resolve the interference generated by interleaved problem solving—often boost their efficiency by extracting exponentially more oxygen from existing blood supply rather than requiring increased overall blood flow [cite: 26, 27]. This discordant voxel behavior indicates that the intense cognitive effort induced by interleaving fundamentally alters the brain's oxygen metabolism and extraction efficiency at a cellular level, permanently upgrading the neural network's processing capacity rather than just temporarily lighting up a specific region [cite: 26].

Furthermore, computational modeling and human trials conducted by Menghi et al. in 2025 explored exactly how the brain represents interleaved tasks computationally. They hypothesized that interleaving facilitates the formation of representations that directly integrate related experiences into "shared subspaces" within the neural architecture [cite: 28, 29, 30]. However, this research revealed a fascinating paradox: while interleaving builds flexible, highly generalized knowledge, mixing tasks with structures that are *too* similar can occasionally cause severe interference during the immediate learning phase due to overlapping neural representations [cite: 28, 30]. The brain's attempt to build a unified model requires intense computational effort to segregate task-relevant contingencies, which explains the high metabolic cost and subjective frustration associated with interleaving [cite: 29, 30].

## Implementation Framework: Direct Comparison of Methodologies

Translating the complex cognitive science of interleaving into actionable instructional design requires a clear, uncompromising understanding of the trade-offs between blocked and interleaved practice. As established by the expertise reversal effect, neither approach is universally superior in all contexts; they must be deployed strategically based on the learner's specific phase of skill acquisition.

### Table 1: Direct Comparison of Blocked vs. Interleaved Practice

| Dimension | Blocked Practice (AAABBB) | Interleaved Practice (ABCABC) |
| :--- | :--- | :--- |
| **Primary Cognitive Focus** | Execution of a procedure; isolated skill acquisition [cite: 2, 3, 17]. | Discrimination, strategy selection, and boundary identification [cite: 2, 6, 20]. |
| **Acquisition Speed** | Fast. Learners quickly execute tasks with low error rates during the study phase [cite: 1, 3]. | Slow. Frequent switching induces errors, forces reconstruction, and increases cognitive effort [cite: 1, 3, 20]. |
| **Subjective Learner Experience** | High fluency, feels easy, reliably leads to overconfidence (the Illusion of Competence) [cite: 3]. | Difficult, highly frustrating, leads to underestimation of actual learning [cite: 3]. |
| **Long-Term Retention & Transfer** | Poor. Catastrophic forgetting frequently occurs once contextual cues are removed [cite: 1, 3]. | Excellent. Promotes robust generalization and delayed transfer to novel, unpredicted problems [cite: 2, 3, 20]. |
| **Optimal Target Audience** | Absolute novices requiring basic schema formation; tasks with massive intrinsic cognitive load [cite: 31, 32, 33]. | Intermediate to advanced learners; experts requiring schema refinement and stress-testing [cite: 31, 33, 34]. |
| **Neurological Signature** | Localized processing; transient, short-term activation patterns [cite: 3]. | Sustained fronto-parietal connectivity; deeper oxygen extraction efficiency; systemic metabolic changes [cite: 3, 26]. |

## Meta-Analytic Evidence and Domain-Specific Efficacy

The theoretical advantages of interleaving have been heavily stress-tested in the empirical literature over the last five years. The most authoritative meta-analysis to date, originally conducted by Brunmair and Richter in 2019 and continuously validated and expanded upon by subsequent researchers through 2026, synthesized 238 effect sizes from over 158 independent samples encompassing diverse demographics [cite: 3, 23, 24]. The analysis revealed a robust, moderate overall advantage for interleaving over blocking across all metrics (Hedges’ $g = 0.42$) [cite: 3, 24]. 

However, analyzing aggregate data obscures the vast, scientifically significant differences in efficacy across specific learning domains. Interleaving is not a universal panacea; its effectiveness is strictly dictated by the intrinsic nature of the material being learned.

### Table 2: Summary of Interleaving Effectiveness Across Distinct Domains

| Domain / Task Type | Effect Size (Hedges' $g$ / Cohen's $d$) | Description of Efficacy & Domain Characteristics |
| :--- | :--- | :--- |
| **Visual Categorization** | Large ($g = 0.67$) | Highest efficacy. Highly effective for tasks requiring discrimination between easily confusable visual stimuli (e.g., identifying painting styles, classifying geological rock formations, medical ECG diagnosis) [cite: 3, 20, 24, 35]. |
| **Motor Skills** | Medium to Large ($SMD = 0.54$ - $1.28$) | High contextual interference significantly benefits motor skill retention and delayed transfer in structured settings. Notably, the effect is exceptionally large in older adults ($SMD = 1.28$) compared to younger cohorts [cite: 3, 8, 36]. |
| **Mathematics & Physics** | Moderate to Large ($g = 0.34$, up to $d = 1.88$ in field trials) | Robust long-term benefits for complex problem-solving. Forces learners to identify the deep structure of a problem rather than relying on surface cues. Highly effective in authentic, longitudinal classroom settings [cite: 2, 3, 24, 37]. |
| **Language Acquisition** | Ambiguous to Null | Highly mixed results. Interleaving verb conjugations in a single session yields no benefit over blocking. Distributed interleaving across weeks shows retention benefits, but initial blocking is mandatory to build base vocabulary [cite: 3, 38, 39]. |
| **Expository Text / Words** | Negative ($g = -0.39$) | Interleaving fails completely when learning isolated facts or word lists where discrimination between categories is not required. Blocked practice or spaced repetition is vastly superior for rote memorization [cite: 3, 23, 24]. |

### Deep Dive into Domain Variances
**Visual Categorization and Medical Diagnostics:** The largest effect sizes in the literature are consistently found in visual category induction [cite: 3, 24]. In medical education, randomized trials demonstrated that interleaving the interpretation of electrocardiograms (ECGs) vastly outperformed traditional blocked practice [cite: 3]. Because a physician operating in an emergency room does not encounter patients sorted sequentially by disease type, the cognitive ability to rapidly discriminate between similar-looking cardiac anomalies is absolutely critical. Interleaving forces the visual cortex to permanently calibrate to subtle diagnostic boundaries [cite: 3].

**Mathematics and Physics:** In mathematics, the interleaving effect translates exceptionally well from highly controlled laboratory settings to chaotic, real-world classrooms. A massive longitudinal study analyzing the PIPES educational system ran from 2019 to 2025, tracking 730 high school mathematics students and 480 physics students [cite: 37]. Over the 32-week study cycle, students practicing interleaved mathematics achieved an astonishing average final exam score of 82%, compared to a national average of 33% (yielding an extraordinary effect size of $d = 1.88$) [cite: 37]. Similarly, physics students scored 85% compared to a national average of 52% ($d = 1.14$) [cite: 37]. Interleaving prevents the "plug-and-chug" mentality by forcing the student to diagnose the underlying mathematical parameter before blindly executing a formula [cite: 2, 4].

**Motor Skills and the Contextual Interference Debate:** In the vast motor learning literature, the interleaving effect is historically referred to as "Contextual Interference" (CI), a concept dating back to Battig's seminal work in 1966 [cite: 8]. Historically, high CI (random or interleaved practice) was believed to be universally beneficial for all physical skills. However, a highly controversial 2023 meta-analysis by Ammar et al. aggressively challenged this consensus, suggesting the CI effect in applied sports settings was a "myth" due to statistically non-significant effect sizes [cite: 36, 40, 41]. This publication sparked intense academic debate, leading to subsequent, highly rigorous meta-analyses by Czyz et al. in 2024 [cite: 8, 41]. Czyz and colleagues clarified that while random practice in highly chaotic, unstructured applied field settings may have its effects diluted, structured laboratory and controlled sports settings consistently show a robust medium effect ($SMD = 0.54$) [cite: 3, 8]. Astonishingly, they discovered that older adults benefit massively from interleaved motor practice ($SMD = 1.28$), theorizing that the intense cognitive effort required by interleaving effectively compensates for age-related declines in baseline implicit learning mechanisms [cite: 3, 8, 36].

**Language Acquisition and Word Lists:** Conversely, interleaving fails spectacularly when applied to isolated vocabulary lists or expository texts, frequently yielding a negative effect size ($g = -0.39$), indicating that blocked practice is vastly superior [cite: 3, 23, 24]. When items do not share structural similarities that cause cognitive confusion (for example, learning the vocabulary word for "apple" versus the word for "truck"), interleaving merely acts as an unnecessary, taxing distraction [cite: 3, 24]. In the realm of grammatical syntax, a 2025 study examining L2 learners found that interleaving Spanish and French verb conjugations only proved effective when spaced over multiple weeks; within a single session, it provided no benefit over blocking, suggesting that a foundational, blocked schema must be built before interleaving can be successfully introduced [cite: 3, 39].

## Deepening Limitations: Cognitive Load Thresholds and the Expertise Reversal Effect

If interleaving is a highly potent pedagogical tool, it is also a highly volatile one. It is not an instructional switch that can be blindly activated across all curricula. Its efficacy is strictly constrained by the hard limits of human cognitive architecture, specifically regarding cognitive load, the learner's existing baseline expertise, and developmental neurobiology.

### Intrinsic Cognitive Load Thresholds
Cognitive Load Theory, heavily developed by John Sweller, posits that human working memory has a strictly limited capacity for processing new information simultaneously [cite: 6, 25, 42]. The intrinsic cognitive load of any given task is determined by its "element interactivity"—the total number of interacting elements that must be held in working memory to comprehend the concept [cite: 6, 43]. 

Because interleaving requires the learner to continuously hold multiple rules in working memory to compare and contrast them, it inherently and significantly increases the intrinsic cognitive load of the learning task [cite: 6, 44]. For tasks of low to moderate complexity, this artificial increase acts as a desirable difficulty, promoting deeper encoding. However, if the underlying learning material is already highly complex, interleaving can easily push the working memory demand far past its biological threshold, resulting in catastrophic cognitive overload [cite: 7]. When massive overload occurs, the desirable difficulty immediately transforms into an undesirable barrier, and learning collapses. A highly relevant 2026 classroom study involving 376 upper secondary students demonstrated this perfectly. When students were tasked with learning notoriously difficult physics concepts (the motion of charged particles in electric and magnetic fields), interleaved practice independently led to *worse* long-term outcomes than blocked practice [cite: 7]. The material was simply too abstract. However, when students were paired together to collaborate, the cognitive load was distributed between the two brains, and the interleaved-collaborative condition suddenly produced the highest overall test scores [cite: 7]. This conclusively proves that interleaving requires available, unburdened cognitive bandwidth to function properly.

### The Expertise Reversal Effect
A direct, cascading consequence of working memory limitations is the Expertise Reversal Effect, a well-documented phenomenon where instructional strategies that are highly effective for novices become ineffective, highly inefficient, or even actively detrimental for experts [cite: 31, 32, 34, 45].

Novices completely lack established cognitive schemas in long-term memory. When they are introduced to a new, complex topic, they require highly guided, blocked practice to isolate variables and prevent cognitive overload [cite: 31, 32, 33]. If a novice is forced to interleave before they have a basic, fundamental grasp of the individual components, they will fail to recognize the underlying structures and become quickly overwhelmed and frustrated [cite: 31, 32, 33]. In a 2025 experiment, university students provided with pre-training (a glossary and concept maps) before engaging in complex problem-solving exhibited significantly lower intrinsic cognitive load, allowing them to benefit from advanced strategies [cite: 33].

Conversely, experts possess highly organized, automated schemas. They do not need to process individual elements; they process large, interconnected chunks of information instantaneously [cite: 32, 34]. If an expert is forced to undergo blocked practice or highly guided, repetitive instruction, processing the redundant, simplistic information actually induces an extraneous cognitive load that actively distracts them and degrades performance [cite: 32, 34, 45]. Therefore, optimal instructional design mandates an adaptive fading approach: beginners must start with blocked practice to build foundational knowledge, and as expertise increases, the sequence must aggressively transition to interleaved practice to challenge the expert to discriminate between highly nuanced, edge-case scenarios [cite: 31, 32, 34, 45].

### Developmental Factors and Learner Age
The cognitive control required to manage the interference generated by interleaved tasks relies heavily on the prefrontal cortex, which matures very slowly throughout childhood and adolescence [cite: 3, 14]. While some recent evidence suggests that children as young as 9 can benefit from interleaved visual categorization (e.g., learning natural rock categories), the magnitude of the interleaving effect is generally much smaller than in adults [cite: 3, 22, 35]. In self-paced study environments, where learners regulate their own time, young children often struggle to regulate interleaved practice effectively due to lower baseline executive function [cite: 3, 35]. In contrast, adults with higher fluid intelligence extract significantly greater benefits from interleaving, as they possess the immense cognitive resources necessary to resolve the continuous interference generated by mixing tasks [cite: 3].

## Cross-Cultural Robustness: Evidence from Non-WEIRD Contexts

A pervasive and long-standing limitation in cognitive psychology is the disproportionate reliance on WEIRD populations—Western, Educated, Industrialized, Rich, and Democratic societies. To firmly establish interleaving as a fundamental principle of human cognitive architecture rather than a culturally conditioned artifact of Western schooling, it is absolutely imperative to examine experimental data from the Global South, including Africa, Latin America, and South Asia.

Recent large-scale, international randomized evaluations have finally begun to fill this empirical void, yielding results that confirm the fundamental cognitive mechanisms but highlight critical, localized implementation challenges that must be addressed.

### Insights from Africa and South Asia
A landmark 2023 cluster-randomized evaluation, supported by J-PAL, was conducted across 62 classrooms in Nigeria. This massive study tested the impact of a full-year interleaved mathematics program on students living in urban informal settlements [cite: 10, 46]. The findings were highly complex and revealing. On tests of short-term retention, interleaved practice increased test scores by a statistically significant 0.29 standard deviations, completely aligning with the findings from smaller-scale laboratory studies in rich Western countries [cite: 10, 46]. This robust finding strongly confirms that the baseline cognitive mechanism of interleaving operates universally across human populations.

However, the Nigerian study found absolutely no evidence that interleaving improved average performance on a *cumulative* assessment measuring retention over the entire 141-day academic year [cite: 10]. Furthermore, there were troubling indications that the interleaving intervention may have actually had negative impacts on students situated at the very top of the performance distribution [cite: 10]. This suggests that in severely resource-constrained environments, where baseline literacy and numeracy may vary wildly within a single classroom, deploying a rigid, automated interleaving schedule might inadvertently trigger severe cognitive overload without the necessary, highly trained teacher scaffolding required to guide students through the confusion [cite: 10, 46]. 

### Evidence from Latin America
In Latin America, significant systemic educational challenges exist regarding high dropout rates and massive disparities in learning quality, severely impacting socially vulnerable youth [cite: 47, 48]. Following the PISA 2022 report, which highlighted a significant decline in learning levels across Latin America and the Caribbean, researchers have focused on implementing evidence-based strategies [cite: 48]. Cluster-randomized trials examining early literacy interventions across four Latin American countries have demonstrated the absolute necessity of capturing robust baseline data to detect meaningful variance when implementing complex cognitive strategies like interleaving [cite: 9]. 

Broad assessments of learning strategies in Peru and Indonesia indicate that while metacognitive strategies (such as interleaving and elaboration) are theoretically highly beneficial, they are vastly underutilized in the Global South compared to highly inefficient, rote memorization techniques [cite: 48]. A primary structural barrier to advancing interleaving research in these regions is the severe lack of culturally adapted assessment tools [cite: 49]. Evaluation frameworks developed in Western contexts often fail to accurately capture nuanced cognitive developments due to deep linguistic and contextual variations [cite: 49]. Therefore, while the cognitive benefits of interleaving are demonstrably robust internationally, realizing these benefits at a national scale in the Global South requires coupling the cognitive science with multi-sectoral partnerships, massive teacher capacity building, and highly context-sensitive measurement frameworks [cite: 46, 49, 50].

## Conclusion

The science of interleaved practice represents one of the most robust, thoroughly validated, and deeply counterintuitive findings in modern cognitive psychology. By deliberately substituting the superficial, deceptive fluency of blocked repetition with the desirable difficulty of discriminative contrast, interleaving forces the human brain to actively retrieve information, resolve interference, and build highly flexible, enduring neural schemas. Recent meta-analyses confirm its profound, transformative impact across mathematics, visual categorization, and motor skill domains, while cutting-edge fMRI data illuminates the deep metabolic and connective alterations it permanently induces within the prefrontal cortex. However, interleaving is strictly bounded by the biological limits of human cognitive load. To leverage its full potential, instructional design must deeply acknowledge the expertise reversal effect—sequencing learning to guide novices through initial, necessary blocked acquisition before aggressively introducing interleaved complexities to build true mastery. As empirical evidence successfully expands into non-WEIRD populations, it is definitively clear that while the underlying neurological mechanisms of interleaving are a universal human trait, its successful educational implementation requires incredibly careful calibration to cultural context, cognitive capacity, and systemic instructional support.

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6. [mdpi.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFlF9RzmEUizyPXhfcGcdSs7M0niJTMFh5KKUA9c9dUJ_FDNuxcK3fbuy_v9ZCpKLkZ7a3-xNY3K7lQAmrmqyshrFJBsKYALqJ0t1fk19aoR1fyVaIjVkhNlGh5p4PUGw==)
7. [theeconomyofmeaning.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHVx1Ua9vY8sO_ef2_gYaPXooOCY1xw8mxxahoKgQ8S8Cg5SPwlNgHf8nDTbg6eKTH-PAxzugXEZr0BJv0kwxXVa7JR6y4VFRJxgdM7bZSoiTHZmXayxx8kF9JvljLy2qD6TYQiT9TFMED1oP8e3y-nhEoJfXoqyq_jfbWHudRN70aoDAMq9WoKu6Ljm7KKkUoaahA_Z16jwjKfM1LdPtg=)
8. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEuamNKKZd0_rGqpcyhQFnnHTX6p2Sgch6zMdGKnkmB3QJhiYIWX7fPpg6ql68pgn2GUP_dCcQi7RUP_0G3DT72Qf-rWaKlu6gWkyITnPmBeotCZE5aYHWPN3x7mY9OVEQj7ZTPdVmZiA==)
9. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGpDU0EBPb3sztFSj_UXvypa0z_keW3zfEOAHESasA3rpteZKdocdqrvsG9f0HV4UMWXDRmVKex0VuYWrF07AF6_Wi3Iz1NGHRIoVKtZTh6cxl7TZjZ-aAwG7cRIanyPA==)
10. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHJjjy0-kJuTQ8MaZ596ZmNrprClrZTCbX8SoiWthBekmLeB5CcKwwANG7Oxv8RaCVbsHndG3bjFLqSpO29V84VGFkri64utJLfqBizzgryfV3pf61P3AoSerSXIgHNvfDoEfRbfjRTgt9XLejAHbVzuN4fcyjZPcI8go1jY3f-Erg7aps8XUWOHw-cxMntgW0MH3z6-wyZNFGG1sqWifk=)
11. [apa.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEwUhCEGLrG9AVU25qRs6EtAiIpv_DxaZKmuO8-wxWiVnNVGBT6_iJVVMvo14fq1RQNcN6BIaL0sHoihGV5qzsbFzR6jMMEziJepBk0psd_3IbkzzWi5ecSgT_khxhYESgmoIHSbDw=)
12. [emerald.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFZyUkpFBfGgYxbvYMCAmFUDXH_sB1ph4QZJ_G6YDVzvwDJk2a7C79W_3HUrMp6UopLcxcZ8sXDYxiN4krrpNNhFD8s2c6bo4PAw09py9YKnEunt94cdJGMsPcQo1WY6HEWQUNvO10YQBX2S3lO1hF-P7irorF1mjCZu5uiC1QTa9NDZRX2G2MMcvvMNN9BwhwYvA==)
13. [youtube.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG82ViAXR2ODxJuJ7HRn1t-cNZhW2ELyP2TAIU9SAd8aZwmAqlyLUZUIX_mmfKtLVcKq9ZXC7ih-sKdYys1ZCvT4CAEVNyv9AYP6F3l7O3qSvR0YSjPKSwRLX0cR9GZzf90)
14. [mindspacex.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGlPfghMtAxUtLz6vtZBFUmgIib6d5eCdC6DWPySH8vAwuMdy5ivNDzn65l3Jrdwx3_-y7QCK08sR2CcyFLj4jnm1ryE3Bv6_BVDgEu_8AEwv-wcQwvEbhVAzGVlkSLQySR04vBSRzhA6Vn50DzMF3UJUf7cG0UrWDtlKnCRGB5KNtRKxdcZXVQFrLRx2eU387tqOtQcZ3cPNJ8retSYA==)
15. [richardson.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGzdjvdpYUApDsNWkck8i3Ix1VkHhjf2fq4yxHCOUIglLazLoNwUdsN5HQe3VR4jTkvs80l_85dUcNmjCmU_xbetYoufTd00sDeyOMVtz5RQGTsvSov2KqQTWww-Knj5qR4WHAJmDCo8-gyEmSH2GonDa70tR7dyCwM9JM=)
16. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQExEp-WjcGJDByAn3VA1o-nAaRoL_B1fzj84xRvLfvkzEo2asIhrk0DVcgJRyorLnxwua7OHwCef6PijejMkobKVYCCapep0ZHDokZBsWT-SkjTLLtIgqD63y4zpv5XBh5NQGTpjT1q)
17. [nesslabs.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHT207mRvdAbhaX0SkxvIFSg9pw55Vbyg1VE3oSgl8f3r48gak_KqCv9SHxzUNwv5QboIUygbI3BQLTZi8lPLmGK3Ee2AXx6-xtC4sDZ1vfcHXWgf3lx2A=)
18. [semanticscholar.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFUl5GGIYhizbUi4bQzSP_ni1Gw2Ndcpd9cNI4qngyQkPOOd0TSeycKzVMfJkkznvcUgL6ebF3UmBkE2lWidHBanhEifuFryWNESh3qe9pBbmAgcVM9Y0yq2F5nqxBhcsFFOJ-piC_ZKdWTZoDnD8nELS7V-R8DO8Nsdsau-AMae1fV-GA=)
19. [21kschool.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFH9Xfh-wyysuah7BgsznGMwarSCyKBQPd0QIxTW4gaoqmViAMXT-i-cksRQQ-RP_i306M8Hcr_JRL8FDrfVIc1j5vWAN-SmVGhf08pldVthzFIVTqVNr2tmFu2A3MG1xFWXBg9NOSlFTr6WEoQyRzJAxU=)
20. [structural-learning.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFkflXxoUUg8BpFhOrjLjonqdZwWWU2QHumyQ_W5zpZLHrgcNFNaBAboNM133OmDeORL8nPqgD2es7AftgbWSJ0UuWpS0hJvFPwvw95bhjISZ7oQrqNKf78QA4gWMedvAvdSO-TkdZMeKa8hgrTKmWnbYCH0GwnI6lqgl8E)
21. [frontiersin.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG7X1hl3ka2OhYqRUh-7yBkJzPFH7kwSX0mdVVENbMJ0CiGLDYVOPY44s0TFy2nBGqVZBG2AHlLhCvTSjw0giAMjFaCsOSD2zfC38oR-cp7PmkKryPSI10XWue5jAhXrZVpHJO-w0CEQZHchgk4uSXyVpy9DrjvKpTyVtQ1-b8DxRVzSoqtxVqkX7jtqlYm)
22. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF-WLsRJ8rsxRi--lvsZh4lAeF0SQdHRWK8m1W9SX_cxEJ36A8fjNQZP2Qt79k0IL5EQuqFG219xtL3byEpJN20wYo5ywPPUOGTaxYOj4s8CRWszYMENZ8Ci4VZDBru0Kuj9Xrh9sb3UQ==)
23. [uni-wuerzburg.de](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHEex1_4nyE_3FxA-2-MseHCaSg_LMw6Cyx9rS3Xf7yjf48p01TDq9MKYL98qi3LLO-KreEgnua4i9LNeQsCFiiI9ANrcHs2sqieJM7vnZznVUNRSlok3z5MZMI4YZhj4Ti9tdzEmt93RY6aeV2YUk-0M2CMIiUo1aiE_qaltts6oQMEoxzzaDfITlqg-tiy-xmpKZFN2SDmQgyTNd94OsV8heoQQMky_AolrASpfkLZExOTH20VFfTgVLgoEwJodKa)
24. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHisCky42OuOOs_vchUAcZ6gcO8LlQckRDkqStbaMs4bdLrlv4iG05CqTgm86ZUXFEpSCzOa3YFoJhtVotiMcJEavtRtINcJD6jlqOjwFLy-WUClhmKcQ-jWKqxu9eKJw==)
25. [innerdrive.co.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGHhwiJ5wYRJDIPFCCwGLJ3Iy1eWB8aUoVWvb9knlCgcxuK5MwLnXAVyJuTziaaoo_4RcPRKvfLDCCV_plmqMZ4NMDX3tIaH0Yl51TPEoNgrTNeD0s5cRliLUXZDdo3R8lwUH95CAO7-PamJfvBDGjuyXbUJ1dk-uKWl0Bw)
26. [neurosciencenews.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHAWTWWqPcTrxL6Jw-QeG87jBuG6-M8gyRyfa04DQlEHwvzUpakaFk343Joc1Xid-E4y5o36QTlZ1qBBxJJAjRwuL_aNy3Sn_C3EK-JnLcR6I5VRiVl91L5cYGzDFi82oGB8xWIGZJvvjXn4jV5Nw==)
27. [realclearscience.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHWgARVCuYLlbhsMeVanXB2v3S5nfPZB_Advmy8wFoh0zWtk7R3hnbNM2EEGIXerr1GE-j05GXAaHYa0kiU2DghTWsVHcm9meIvFhIVNmnxKWpSeHaBKQ0LRSVNmGBzEp2yEK-HOU7l3PevasMGO6yOTPA3voDnR5r2HNmVg0b8FzPXnD1FqIEZYzG07JyYBzrhULqX-XujWtVR2ZU=)
28. [biorxiv.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHQa3QD3_slLeeElNMZN88Mtovyiw64zRHYtknACwkPhM9pLv9IeC-hKHW7uRXzJhPfqku2jO1HcTiv4JtV77kjoGzRKE_oHy4bd09cNtVN05ElbQeyjHTvBlftXDrOYvQUk_48Z4k27fHk2m-e4Dm8vmOqn8MRPV7q3A==)
29. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHf00i15H7ixmLC_DEIcVCk1OdvpnEXcrrbggQfWjbMC_988QGkuht24jY5W7CSL1jrSg0_56Z5-RFP5tab-Zw_eoPpW7uarLV-VJqldH8Hlsey_yVqcF-y-WI6vdLkSCcThFV8IEa5z56CzU_hymaT6m3F5vfEf-SdHj4qp2hXpr6HtIdGKumis7tyy7ItWnAF8b6Nt_xHPjivB5IIbdbFh1LbmnPelId-_LUhHxuyxM4LduHY7Q7n7VPqQqn2rw==)
30. [biorxiv.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF4GZUt9TYd84s8DikZE2fMGFl4iL0QX8X2plxGtR4yyUFszTNV1MLdcEHGvM87613MNoPapUpjJZcpzHQoUBGIU8w4ktyCsYL_icWXYT_qNpcGweh9lCz5NgMGPI6yh4v3EczGROxNu_Uq01QpDICofuaZ1ToVGgM6DP4=)
31. [wikipedia.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEy6fAZ9S-JYQljAUI1tkYMcf8wdhyrVwZGf0P-Zp1FCpZs0Rn8tGgYqyjBuQSEKWxwPtviKXQYaRNDyZ549RQmzgYdxwV0oOd_B7FmngGx1_8j3jMMHfhS6O9zF2cVaFjad0HZkclv5ZGqD_c5)
32. [theelearningcoach.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEyTZaIWZx9YsNMNv76f9JZGBaHx3EWJvAbTtqyFbjwuc1oLv62EiWXW7jetI6A2X5NXw_q0BUC9-q-qO-FLhH8LZKqrFQD_rdRP-0Dtqo8TjKm7dNSnOgxo6nywM24o6l6iW1lsWOVoOrQqbMgsvPD1l_J1FkGv_mSYrAalA1QQJyQR9I=)
33. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFl3F1AT2ROmabFkPjvLZx2S_l4JcA8xujmfpJu_Qs0svJwQSyzigjNHdcnNfKzBohC6yt1sqIRAVBayz8dS0Fsb6fV-N2Z5WrVrFLxuTQ9BIThsPN0yTv9uMbW0DdjAwuHyZtXFnaRjIK__hzp75Onk2V0LqegR-bY5Y5fqcvp8Vbvy9ePvjzuhZbSfRSfvIEN52GDv87xiw9U48AmPCLR0bEZMdq8r9GQ2mdl0152LHLer_lgNgx3nM0gUQTyeRSAOMv8oaxX)
34. [mrbartonmaths.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHj7ydCzQ7DoNh8nGcqIiGg6SUGAm8c1ORRjuZZEv9kFeTUXEb3Bz3_96uQ9wKkrql0S-V06YlNhvhHB71yb0dGq4OJCQOB6JByYT3kHroXP5rP2308yLUSlxdOMkdY_R684fvpK1tCIONaoJYkq0EESQurB1twgmQyisSTOe2PSOwDebLDjhBL38BtmIovgg_0StChzG_T9IZm2YuAuLNDwyoRRBMTNuRr)
35. [mdpi.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGjrHUjZIb5r8_5Hfgtws61GkYgXQvL6MXR8MtY4BRuAUtUcUeVmvwDttM1BM_WLPbFoqFVpmAJDPnVBL4mjTufipPOXmWw_Gsg12GLxlF4Qn5jd5b7UYpZEi_cV2g=)
36. [frontiersin.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG-edbvonvMOO5oNgIRjZvtTM0fX0WOfjH21qcC5Vhxi_68ZmdzBcMJpxyaQ-9Kjy15sy5Mbgw9_hHgVGUhgT_q-IajpLWvN5H6CXyYGfhjAXZiLDdDLtQRH2wbn2AyU6wOlE1Ub8xtVljZfLNh-jvvEi_IA-cJgzUVKojf_msb_KFnHi1M0XBIuYhBx3b4)
37. [mdpi.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHjxvwMjADA287VZh58l2Pch9mJDFp4vyXxD7q8w509F7vPdW8eoaGiKRD83c5wuUH0ZCWFZlNnq0C2Xd0wYsUFECd4Eozz7kGaJ7oDbk9kzRLSfZ3xEL6lbtQmwgE=)
38. [cambridge.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFb8WMyIUpIPSZ6z4aC_x5jk8eegkuu6ZKZE4FqEaN_BcOOhA00fhyxTlH-kvg3d4SH3q2giaWn4aBNQSOuzBqKwz85Z1yNsPT8iwHcQmwOXveOYKqLfyifr1xGNCXL6xb3x7HSN1V7cEw5AL0RdXjFgfV5Xq0b9mMerFHrmzTdgF_9gQXvvBo6cYM-QHBh8dScMOhYL2Z42So7OhyhQyB1rkwuhghx-JmGQD4FwlKtLZYVIxrG94GBZ8mS6H0Zj2irR9sP4qlYwl3HtfBh0jPf6smx2gUTYaw16cGreL7cBna0wd19XMMImUGtjo_CnQYfohTP7l10gYBUp6rDuaEZUf4=)
39. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFeEJKZFk4uCTULA2ICIrZfsJT-5ps4ZtBCaeFyWqdvBxUWFFDyX48-YV9WzShysiGDUjukqr9Ol9mFItWks6MYCB0WDtpiXqxFiyFGHmHSiswG2W2LHS7hCN1FpMqUlu_z647xzsR1HA==)
40. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEqLDKJQ0u15DOilFZKGowKCTDvSD4u0S4Ul5YFAhWwiuFX5jzus7vT_tlRoAbmiI8Hby8V1YdAQS149zau6UsisLRRoqa4BfEPo9h8Uw45xqEab727NzgP7GwDV5t5o0U7d6wAsCCZhENyALnOPmXUcC20zE2KgTyAuiAJ7yfMLg6oU29swfr31LHgIrHc7sljYdznaEMFFIEveq9BqYBTIiULPP824MBsj6cf6UB6tWIbNKQC279uu-t_t8zmIeWOrD2VOWtt80tnrG-E2VNpkRjDKUvQcg==)
41. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEfytzeHWSs6WfviGd5_ueocv7pWJJE01s79kGUPpKB5vhFjMknyYOjJZHNC79BUPeIUvoedtQlNW9EAQJM_QPZLkzSnbjmcMVh4S3u08Eyc8JS2XS2HBRamr9kWPuEYcEEP1DfSpv5vc9FerSvR_SrU9ixEMK2l8wLT6w8lJRs7zg59oCnOfuVX9qpVoa6PwmCUSpbqEqR7O1-zEBcJpq7Luu42MGQPQ==)
42. [mdpi-res.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEwf3otsUr7Sexzl02moF4tl7s-LxqjWRHalHSRP1mJRkQDZc-Zn2Qdy40lB_Ct3bE2_6XpxM9neAqjLe7uYR4D8SH9V-5RONJNa6K3EGFM101TvNjTYCgeFEBYDw2MzVZ-u9x0MINVKDOZyU3u7FxGEET7t_zQvfqtG_-ZPvliNTm1OGOHFw==)
43. [whiterose.ac.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFrscd8QMXBQs3U87cyY9su6AXSjyQPXKDipENwygZ2Rmaj_a4f9I7bDfAJVkT8c0gcMJUQB0lrQ2SccXgFsXLrEbrjl9pEC10oP4BdRT0Xla6MewWi6e4HEj6Y63bF-4vNFtlAwyi39X0abPil7EmFKk_XfsjXkqIHBsomZRXd8YJLDJagx8uFM4MFCkNmccGF)
44. [birmingham.ac.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEH96vhVhtiE0zPo7KS_2TdciSmuy3SNvRzOOOpkIWX93x8lwIIPYO1uz9mUOwHqI_93BQzrx7v8UrEWxEHCXoMnW-6YW-xM1dABPPPqnsAT6eRfTVhzI3Gv_UcgmE6YXKjhzlml63wGjH8hDanxn1ETvLN5AdXRk_A1EezGQKXAiHsC5MbQc9G_9Tc-moHpNVgje7XZKKhNtx1NmJZaqCIQV_k-lH84fFUIA==)
45. [learning-theories.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFk2oX5uCh33bB5ybJAFGxDYymHE--GGHrEm2MMTATqdjodDQzfdNxeAUUsHkaEQvIP05bj04hUaSNFKaRmomSFgen0oRV4526ajcIZyj-kFH97lBypclbCf-mM43bGUXX-SNv37_OqpWRHHjwqwkci6iFtG_Z9s5oHWwZZnSiLIkzOTlfoMFQM7RUoiWR8)
46. [fcdo.gov.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG0zKFBie_TBX5aQTntnm30snY1dHd6le82y28NIRJbNLVVTZ2NnB_ajeB1t-wKpbRSYsxgr5Y_Ist0Rx-rny2rBKODGtNkAg5jUWFmrEdeTI73p3Iw4muqbDiCwABo9AJllkYeLSOjmVeJ)
47. [iadb.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHX8cfZaRDCqvqhNi0Xs2hsCmWFnP5mB0nIc3XX267KMKYi3C6Ql_UtmwFbBAY8o_x9PNThYD986wbYPZPlth8pBPlGJBHMw8x1EojFNRRYqnHq9uzjG6_wEsJHKd3psvl7gENeq8FAJGBbSDJ6u0UvHDl8ACeIx0yv_icf1Xyh8yhiVaZpBx0=)
48. [revistainvecom.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFooQqC4eT6GhIDJrcMRNYY3wi0Xs87k_VGJe1Xjr6tseAazxbXyF9GlpOHMfi9hMOrPEBDup6vvtag9XgmgUmeTK7qkpiRXAme0m99ipupC0EoDROuHOQy7QVEuHhYxrfyA69YkZxq0-LCSR47X7Q-tlaRHJGPGatgRYZ_YSYIi5ikq6myBw==)
49. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGUH7Vcqdu3mR3Wa0g5DJe0FEbmKL2IBsAzcWZ5t88QFykVNtZDdJybVTw0Z-iCuWdbx5q7V7-OaClT3Q-5OmzCE2WmjIRx8d0ldzNvvKckroGdOTesCf0ig_1DEQroGSfHYBcnGbaXBg==)
50. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGMpSMEwFich_WqvryvgQWKRXL-Z7AfBH_VfQM1RxLhgTH5P8-0wN5pkMz1zzn5M7GHfHB72sou702VaezAmbYuGmWdTf2-dnxl-P-40PYnr7v4Pp4z_mADPZv6v-VHFw==)