The study, published in the journal Large-scale Assessments in Education, drew on the German National Educational Panel Study, a long-running effort that follows children’s competence development across the life span. The researchers, led by Jana Welling of the Leibniz Institute for Educational Trajectories, analyzed reading and mathematics assessments administered in Grades 2 and 4, with 1,512 children participating in the second-grade assessments and 1,470 in the fourth-grade versions. Because the tests were administered on tablets or computers, every response came with a precise timestamp, allowing the team to reconstruct exactly how long each child spent on each item.

Rapid guessing matters because large-scale assessments are typically low-stakes: nothing happens to a child’s grades, placement, or future based on the outcome. Expectancy-value theory suggests that when a task carries no personal consequence, motivation to invest effort can collapse. The demands-capacity model adds a second dimension, proposing that effort depends on the match between what an item demands and the cognitive resources a test-taker is willing and able to deploy. When either willingness or capacity falls short, disengaged responding emerges—and in its most extreme form, responses arrive at implausibly high speed with accuracy near chance level.

Among adolescents and adults, this is no small problem. A 2022 meta-analysis found that roughly 7 percent of responses in low-stakes assessments are rapid guesses, and about 28 percent of examinees rapid-guess at least once. Worse, uncorrected proficiency estimates are biased downward by an average of 0.13 standard deviations. But children, the researchers reasoned, may be a different story. Young children tend to be overconfident in their abilities, which could boost their expectancy of success and keep them engaged. At the same time, their shorter attention spans could work in the opposite direction, making long tests feel more demanding and pushing them toward disengagement.

To detect rapid guessing, the team used response-time thresholds: any answer delivered faster than a cutoff was flagged as a guess and scored as missing. Because no single threshold method works for every test design, the researchers compared several approaches. For the reading tests and the fourth-grade mathematics test, they applied normative threshold methods, defining the cutoff as 10 or 20 percent of the average response time for each item. For the second-grade mathematics test—where items were read aloud via pre-recorded audio and children could not answer before the audio finished—they used visual inspection methods based on the shape of the response-time distribution and on how accuracy changes with speed. Thresholds were then validated by checking whether flagged responses showed chance-level accuracy and near-zero correlation with overall test scores.

The headline result: rapid guessing was scarce. In second-grade reading, 3.3 percent of responses were classified as rapid guesses; in second-grade mathematics, just 0.8 percent. By fourth grade, the rates fell even lower, to 0.5 percent in reading and 0.4 percent in mathematics. Contrary to the researchers’ hypothesis, disengagement did not increase between Grades 2 and 4—in the reading domain, it actually declined. The authors suggest that the fourth-grade reading test may simply have been too easy for most children, since easier items tend to elicit less rapid guessing, and that the real rise in disengagement documented in earlier studies typically emerges around puberty rather than in early elementary school.

Who rapid-guesses? Across all four assessments, only one characteristic reliably predicted the behavior: proficiency. Less proficient children were consistently more likely to fire off quick answers than their higher-performing peers, echoing patterns well established in older samples. A one-unit increase in estimated ability raised the probability of engaged responding by between 0.52 and 1.96 percentage points depending on the assessment. Notably, gender and parental socioeconomic status—both of which have been linked to test-taking effort in adolescent and adult studies—showed no significant effects. Descriptively, boys and children without a university-educated parent did guess somewhat more often, but these differences were too small and inconsistent to reach statistical significance, suggesting that the social gradients in test engagement familiar from older populations may simply not have taken hold yet in eight- and ten-year-olds.

The most consequential finding concerns what rapid guessing does to the numbers that policymakers actually use. The researchers compared estimates of ability differences between girls and boys, and between children of low and high parental socioeconomic status, computed once from the raw data and once from data in which rapid guesses had been scored as missing. The differences were essentially zero. Whether the team examined the modest gender gap in fourth-grade reading, the male advantage in mathematics, or the substantial socioeconomic gaps present in every domain, accounting for rapid guessing shifted the estimates by at most 0.01 standard deviations, well within the bootstrap confidence intervals. In other words, even the small amount of guessing observed did not distort subgroup comparisons in any meaningful way.

Why doesn’t a behavior that biases average scores elsewhere leave group comparisons untouched? The authors point to two mechanisms. First, when most test-takers are engaged, the handful of rapid guesses carries little statistical weight. Second, rapid guessing is strongly tied to low proficiency—and because less proficient respondents have a low probability of answering correctly even when trying, a random guess changes little. For a bias in group comparisons to emerge, the groups would need to differ substantially in their guessing rates, which appears to be rare in practice, particularly among children.

The study carries practical weight for the assessment community. It suggests that the alarming disengagement rates documented in adolescent samples cannot simply be projected downward onto younger children, and that large-scale assessments involving elementary schoolers may be more robust than critics fear. But the authors caution against complacency. Prevalence varied considerably between assessments even within the same children, pointing to the strong influence of test design, time limits, item presentation, and proctoring conditions—and a lack of rapid guessing does not guarantee full engagement, since children may express disengagement in other ways, such as omissions or slow, effortful guessing. The team also notes that no single threshold method fits every test, and that the rarity of the behavior itself makes its predictors statistically hard to pin down. Future work, they argue, should examine broader forms of disengagement, test model-based identification approaches in child samples, and experimentally vary assessment settings. For now, though, the message is clear: the youngest test-takers, by and large, are still trying.

Subject of Research: Rapid guessing behavior and test-taking engagement among elementary school children in large-scale educational assessments

Article Title: Prevalence, predictors, and consequences of rapid guessing among children in elementary school

Article References: Welling, J., Fischer, L., Thums, K., & Gnambs, T. (2026). Prevalence, predictors, and consequences of rapid guessing among children in elementary school. Large-scale Assessments in Education, 14(1), Article 51. https://doi.org/10.1186/s40536-026-00319-5

Image Credits: AI Generated

DOI: 10.1186/s40536-026-00319-5

Keywords: rapid guessing, test-taking engagement, elementary school, large-scale assessment, response times, psychometrics, educational measurement, reading assessment, mathematics assessment, socioeconomic status, test validity, National Educational Panel Study

The study, led by Umar Abubakar Hassan and colleagues including Adewale Luqman Oyeyemi, Kylie Wilson, Pamela Hodges Kulinna, and Allison Poulos, focused on 72 children aged 8 to 12 years in grades 3 through 6. These children attended fee-based after-school programs at 14 elementary schools in a public school district in Maricopa County, Arizona. The programs offered a mix of recreation, games, academic support, and arts and crafts, running roughly three hours each weekday from about 3:00 p.m. to 6:00 p.m. None of the programs was specifically designed to promote physical activity, which makes the activity findings all the more notable. To capture what children actually did throughout the day and night, each participant wore a wrist-mounted ActiGraph GT3X+ or GT9X Link accelerometer for ten consecutive days in October 2022, removing the device only for water-based activities.

The technical demands of measuring both movement and sleep in free-living children are considerable, and the researchers followed rigorous protocols to ensure their estimates were trustworthy. Accelerometers were initialized at 50 Hz and data were processed in 60-second epochs using ActiLife software. Periods of non-wear were identified using the Choi algorithm, which flags sustained inactivity of at least 90 consecutive minutes, allowing up to two minutes of sporadic counts. To qualify for analysis, children needed at least four valid days, three weekdays and one weekend day, with a minimum of 10 hours of wear time each day. Physical activity intensity was classified using cut points developed by Chandler and colleagues, which were specifically validated for wrist-worn accelerometers in children aged 8 to 12. Sleep scoring relied on the Sadeh algorithm, which classifies each minute as sleep or wake based on activity counts within an 11-minute moving window, with sleep onset and offset determined by visual inspection of activity graphs.

Out of 382 children invited to participate, 153 provided consent, and 72 met the stringent wear-time criteria for the final analysis. The results on the activity side were remarkable. Nearly all participants, 99 percent, met the daily guideline of at least 60 minutes of moderate-to-vigorous physical activity averaged across all days, including weekends, where 93 percent still met the target. Children accumulated an average of roughly two hours of moderate-to-vigorous activity per day, drawing on time before school, during physical education and recess, and after dismissal. During the after-school programs themselves, children attended for an average of 179 minutes and accrued about 35 minutes of moderate-to-vigorous activity. That figure represents more than half of the 60-minute daily requirement, confirming that these programs make a meaningful, quantifiable contribution to children’s movement even when they are not explicitly designed for exercise.

Perhaps the most surprising discovery came from an exploratory reanalysis. When the researchers recalculated daily activity after stripping out the 35 minutes accumulated during after-school programming, they found that 93 percent of children still met the 60-minute guideline. This suggests the children in this sample were highly active outside of structured programming as well, likely through active commuting, recess, physical education, and free play. The authors caution that this unusually active population may partly reflect the study’s baseline sample, which was drawn from a larger intervention trial, and the fact that the fee-based nature of the programs may have favored children from higher-income households with more resources for weekend activities and sports. Nevertheless, the finding underscores that after-school hours are a valuable lever for supporting daily activity, particularly on weekdays when children’s routines are most structured.

The sleep results told a very different story. On average, children slept just over seven hours per night, far below the 9-to-12-hour range recommended by the American Academy of Sleep Medicine and the National Sleep Foundation for children aged 6 to 12. Not one child met the sleep duration guideline on any day type, weekdays, weekends, or overall. The arithmetic behind this failure is revealing: children averaged only about 8 hours and 33 minutes of total time in bed, which is insufficient even before accounting for sleep latency and nighttime awakenings. In other words, the problem begins with bedtime itself. Children were simply not spending enough time in bed to achieve nine hours of sleep, a shortfall the authors attribute in part to factors such as evening screen time, inconsistent bedtime routines, homework, video games, and environmental disruptions like noise or bedroom sharing, which are more common in lower-income neighborhoods.

Sleep efficiency, defined as the percentage of time in bed actually spent asleep, painted a moderately better but still concerning picture. The National Sleep Foundation recommends that school-aged children achieve at least 85 percent sleep efficiency, yet only about 40 percent of participants reached that threshold across all days. The average sleep efficiency was 83 percent. Interestingly, girls showed higher physical activity levels, longer sleep duration, and better sleep efficiency than boys across all day types, a pattern that ran counter to the researchers’ initial hypotheses and to some prior literature. Fisher’s exact tests found no statistically significant differences in guideline adherence by age, gender, or school-level income, though the authors note that with 99 percent meeting the activity guideline and zero percent meeting the sleep duration guideline, there was little variability left to detect.

The study does have limitations that warrant careful interpretation. Wrist-worn accelerometers can overestimate moderate-to-vigorous activity in children because upper-limb movements inflate activity counts, while visual sleep scoring may underestimate true sleep duration by misclassifying quiet wakefulness, and the sleep data did not capture daytime naps. The strict wear-time criteria excluded roughly 40 percent of consenting participants, the sample size was modest, the observational analysis was nested within a larger intervention trial and was not powered for these specific outcomes, and the study did not account for clustering by school. School-level income, measured through Title I status, served only as a proxy for individual socioeconomic status. These constraints limit generalizability, but the authors argue the device-based measurement of both activity and sleep in this population represents a genuine strength and provides critical preliminary data for future research.

The broader implications of the findings extend well beyond Arizona. Chronic insufficient sleep in childhood is linked to disrupted attention and memory, emotional and behavioral difficulties, and elevated risks of obesity and other physical health problems, undermining academic success and well-being. Prior evidence consistently shows that meeting physical activity guidelines improves the odds of good sleep quality, and indeed, among the small number of children in this study who failed to meet the activity guideline on weekends, 80 percent had poor sleep quality. The authors suggest that after-school programs could evolve beyond their focus on physical activity to actively promote healthy sleep, for example by helping children finish homework earlier, reducing evening screen exposure, and encouraging consistent wind-down routines. They also call for research comparing sleep on days when children do and do not attend after-school programs. For now, the takeaway is clear: structured after-school hours are a proven engine for keeping children active, but ensuring children get enough sleep remains a challenge that families, schools, and communities must tackle together.

Subject of Research: Physical activity and sleep patterns among elementary school children attending after-school programs in Arizona

Article Title: Physical activity and sleep patterns in children attending after-school programs in Arizona: a cross-sectional study

Article References: Hassan, U. A., Oyeyemi, A. L., Wilson, K., Kulinna, P. H., & Poulos, A. (2026). Physical activity and sleep patterns in children attending after-school programs in Arizona: a cross-sectional study. Journal of Activity, Sedentary and Sleep Behaviors, 5(1), Article 7. https://doi.org/10.1186/s44167-025-00093-9

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00093-9

Keywords: physical activity, sleep, after-school programs, children, moderate-to-vigorous physical activity, sleep efficiency, accelerometers, MVPA guidelines, sleep duration, elementary school, child health, Arizona