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Relative Age Effects

In: People

Submitted By nathanmenold
Words 3549
Pages 15
When Peers Are Not Equals:
The Relative Age Effect in the Classroom

Abstract Relative age effects are differentiated experiences amongst children in the earliest years of primary school resulting from both a single, yearly cut-off date and an escalation of curriculum replacing socialization with skill acquisition activities as early as kindergarten before maturity differences by age have evened out. Implementation of three cut-off dates per class and the creation of individual student developmental planning reduces the potentially long lasting effects associated with relative age differences. This study aims to determine the existence of, and potential long lasting effects associated with, relative age differences. A background on the evolving framework of early elementary curriculum to that of a factory model emphasizing the development of the whole over the individual is included to underscore the ripe conditions for relative age effects to manifest themselves. If nothing is done, relatively younger students will continue to score noticeably lower in reading, math, and science testing throughout elementary and middle school. Pre-university program participation in high school and college enrollment will remain lower, on average, among the relative youngest. Lastly, implications for educational policy, administrations, parents, and teachers are evaluated.

What if the date of someone’s birthday was a gift in it of itself? Suppose this gift was manifested in the form of an inherent advantage enjoyed by the recipient indefinitely. For a new student entering kindergarten in states such as Illinois, Iowa, or Wisconsin, this advantage is enjoyed by a child with a birthday falling on or shortly after September 1st. The United States, like almost all education systems around the world, incorporates a single cut-off date to determine kindergarten class eligibility. A child needs to be five years old by the end of August to qualify for kindergarten entry. I, for example, was one such lucky child with a birthday falling just nine days after the arbitrarily determined cut-off. So why did such a seemingly benign factor result in an advantage for me? Compared with the summer born five year olds in my class, I was as much as twenty percent older at the start of kindergarten. This gap translated into physical maturity and cognitive ability differences between the youngest and oldest students. Though I didn’t know it at the time, I was better positioned to attain academic success, because, again like most other countries, the United States educational model allowed for teachers to implement advanced ability grouping (most commonly seen in reading and math) as early as the kindergarten and first grade levels. I, too, was selected for advanced reading and math groups in kindergarten and first grade. Was I relatively smarter than others not selected for such advanced streams? Possibly. I was, in all probability, more physically mature. Without dispute, I was at least relatively older than many of the children not picked. On the heels of my early, often advanced development, I continued the academic momentum into high school. I tested relatively high on college entrance exams and had my pick of several esteemed four year universities. My brother, Jordan, experienced a far different academic progression model. Having never placed into an advanced ability group, he struggled with core concepts at a very early age, often falling behind the pack at the start of each grade. By the time Jordan reached high school, his position toward education soured, and, as a result, he didn’t even consider pursuing a four year college. Also opposite from me, he was a summer born child relatively younger than most his classmates. For so many children like Jordan, the reality of beginning his first years of school with one arm tied behind his back is symptomatic of a noticeable pattern too evident to deny. Early in primary school, teachers, when selecting and separating kindergarten and first grade students into advanced math and reading groups, are mistaking maturity with aptitude due to the relative age effect. The resulting differentiated experience, compounded with each subsequent grade level, is significant if early degrees of success (or lack there-of) in academic development and achievement persist beyond the point where maturity differences by age have evened out. The notion so much of a child’s future academic developmental path falls on the kindergarten experience calls for a closer look at evolving classroom dynamics and expectations. Two experts in the early-education practices and evaluation field analyzed the changing kindergarten curriculum, the role teachers and administration played on the changes, and, ultimately, the effect on the students. In their study “Escalating Academic Demand in Kindergarten: Counterproductive Policies” (1988) L. A. Shepard, Dean of Research & Evaluation at University of Colorado, and M. L. Smith, Professor of Education Policy and Measurement at Arizona State University, asserted though kindergarten is still formally positioned to acclimate children into the classroom environment by focusing on familiarizing the students with the construct of school (i.e. listening to teachers, sitting at a desk, participating in group interactions, etc.), over the last twenty years there has been a steady, incremental “escalation of curriculum” whereby teachers are incorporating “what were next-grade expectations” into the kindergarten and first grade course material. Driven by now-universal enrollment of children in kindergarten, pressures put on teachers by administration and, most often, middle and upper class parents pushing for educational plateaus in excess of year-end goals, young children are funneled into a “factory model” placing the needs of the whole over the individual more and more since the early 1970’s. Ultimately, teachers are increasingly judged and rewarded not by the success of the lowest performers, by their ability to produce students capable of scoring high in reading and math criteria (p. 1). So, are all children ready to achieve in advanced ability groupings in mathematics and or reading at the kindergarten and first grade level? Well, no. Intuitively, children cognitively develop at different rates. An age-based performance differential is anticipated at the outset of primary school given the impact of the maturity gap inherent with the range in ages amongst the oldest and youngest children within a class. This difference is important in the context of the before-mentioned state of kindergarten as now a rigorous curriculum of reading and mathematics exists. Affirming this imbalance, economists K. Bedard and E. Dhuey, in their study “The Persistence of Early Childhood Maturity” (2006), assert, “…relatively older students are better positioned to accumulate more skills in the early grades because their maturity advantage increases the likelihood that they are selected for more advanced curriculum groups or because they progress through a common curriculum at a faster rate” (p. 2). An in-depth analysis of the relative age effect enduring beyond childhood is then prudent.
If meaningful consideration of the relative age effect is to be warranted, the phenomenon, while inherently intuitive, will be both accepted by experts in the educational field and cited as a significant factor associated with differences in achievement. To that end, a considerable amount of research conducted in the United States and abroad at various points over the last three decades confirms the existence of performance differentials at the earliest stage of primary schooling between the youngest and oldest students in the same class as direct result of the relative age effect. Two universal elements virtually all educational systems around the world incorporate, Bedard and Dhuey assert, are the practice of sorting students into advanced ability groups within an individual class coupled with a class by class age range of at least a year by way of the enforcement of “a single annual cut-off date” (p. 4).
The gap in maturity ascribed to the age ranges in each class is absolutely critical to the initial development of five and six year olds, and the impact cannot be overstated. To further illustrate the effect, consider the scenario painted by K. Dougan, doctoral student in curriculum and instruction, and J. Pijanowski, professor of educational leadership, in their study “The Effects of Academic Redshirting and Relative Age on Student Achievement” (2011) published in the International Journal of Educational Leadership Preparation assert, “They [oldest children] are usually more emotionally mature then the younger children and have more behaviors conductive to school success such as being able to pay attention for longer periods of time, being able to sit still for longer periods of time and having better fine motor skills” (p. 5). This is where early age ability grouping exploits the age difference. In their findings on the correlation between relative age and ability group placement, Bedard and Dhuey assert kindergarten and first grade teachers are observing these differences in maturity and interpreting them as differences in ability when making placement decisions regarding advanced ability groups. Considering these differentiated learning experiences are taking place at such an early age due to the aforementioned escalation of curriculum, relative age differences play a significant role in skill accumulation. So why are teachers skewing the results of their observations? In their study “Are Summer-born Children Disadvantaged? The Birthdate Effect in Education” (1990) published in the Oxford Review of Education, J. Bell and S. Daniels contend teachers in primary school consider differences in age while evaluating the progress of students to the extent they (teachers) expect less of relatively younger students. This, the study asserts, is the manifestation of the “teacher expectancy effect” wherein students are more likely to excel if teachers expect them to do well, especially in the first years of primary school, where proportionally greater expectancy effects exist (p. 78). Just as the expectations of the teacher have bearing on student achievement, so too does the mindset of the child influence his or her own propensity to succeed. Why? Advanced ability groups often tackle more advanced material and move more quickly through a given curriculum. As such, placement in the top academic track can be self-reinforcing and psychologically advantageous. M. Gladwell, noted journalist and author, expands on this cause-and-effect in his book Outliers: The Story of Success (2008) where he asserts, “they [teachers] put the older kids in the advanced stream where they learn better skills; and the next year, because they are in the higher groups, they do even better…It [age advantage] locks children into patterns of achievement and underachievement, encouragement and discouragement, that stretch on and on for years” (p. 28, 29). While older students are relatively more likely to be motivated and achieve a higher standing in their class, often the youngest students like my brother, Jordan, experience the flipside. Dougan and Pijanowski contend relatively younger students develop a negative outlook, a lower self-esteem, and a lessened belief in their academic abilities. These psychological trends translate into impacts on test scores amongst students as they get older. Test results are directly impacted by lingering relative age effects into adolescence suggestive of a meaningful, long term impact. Specifically, when analyzing the results of different studies interested in age effects on standardized test scores, the youngest students, on average, score substantially lower than the oldest students in core subjects like math, science, and reading at all ages of childhood in adolescence. In a study conducted on the kindergarten class of 1998-1999, higher test scores in math and reading were relatively more likely among the oldest students. Likewise, the oldest students made the greatest strides throughout kindergarten in the same subjects. Further, by the end of fifth grade, the oldest students mean test scores in math and reading were significantly higher than their younger classmates (Dougan & Pijanowski, 2011). The conclusions found by Bedard and Dhuey are universal, because their source data originated from the TIMMS (Trends in International Mathematics and Science Study). Since testing is administered at the fourth and eighth grade levels in the United States and over thirty other countries, the pair was able to fully gauge relative age persistence across differing educational systems. “Overall,” Bedard and Dhuey conclude, “We find the youngest students score substantially lower than the oldest students at both the fourth and eighth grade levels” (Bedard & Dhuey, 2006, p. 3). If the effects persist through middle school, is there existence of the effects at even higher ages? Relative age effects indeed do persist into and beyond high school. Berdard and Dhuey, in order to confirm long lasting implications of relative age differences, looked to age based data associated with post high school education. Amongst British Columbia high schoolers, they found the younger students are almost ten percent less likely to participate in pre university programs. In the United States, the predominant pre-college program high schoolers have the opportunity to participate is the SAT and/or ACT. Similarly high schoolers were almost eight percent less likely to take the ACT or SAT (p. 4). Considering the propensity for those same students to harbor negative feelings toward academia and pessimistic views toward their own abilities, as shown earlier, this comes as little surprise. Perhaps more perplexing is the interpretation of the age differences by others weighing in. To be clear, noteworthy communities of early age educational development researchers flatly denying the existence of relative age differences among children in early adolescence do not exist. However, some research warranting discussion disputes the actual effect noticed in early primary school as well as the long term impact on a child’s academic development. In an analysis of the validity of relative age effects sponsored by the National Bureau of Economic Research titled “First in the Class? Age and the Education Production Function” E. Cascio and D.W. Schanzenbach dispute a lag in classroom performance attributed to differences in relative age. Instead, they claim any relative age differences present in a child’s first years are small and dissipate before skill acquisition and ability tracking are incorporated in primary school. This [lack of performance differential], as they claim, hinges on the assertion kindergarten still primarily functions to facilitate socialization of children into the classroom environment. Further, any noticeable differences seen are incorrectly labeled relative age differences and are, in fact, more correctly interpreted as absolute age effects. That is, the older the mean (average) age of a given classroom, the greater the overall performance of such a class, and vis-versa (2007). Yes, kindergarten, traditionally, was almost exclusively intended to familiarize children with the classroom setting up into the 1960’s. However, as was mentioned earlier, the steady escalation of curriculum transformed the kindergarten and first grade setting into a competitive, test result-oriented atmosphere characterized by skill acquisition activities. Interestingly, the claim labeling relative age effects as absolute age differences is both right and wrong. Yes, in an absolute sense, the older a child is, the greater the physical and cognitive abilities. The same is true for the classroom overall; the academic benchmarks achieved (as a class average) are greater if the average age of the entire class is higher versus the overall average age of every kindergarten out there. However, relative and absolute age effects are forces acting simultaneously whereby the relatively youngest students, while positively influenced by the interaction with older children, still underperform versus the oldest students. Finally, while Cascio and Schanzenbach dispel the premise relatively younger students at the beginning of primary school are disadvantaged, their report ultimately concedes the inability of their statistical model, “…to determine whether the age effects reflect differences in developmental trajectories” (p. 22). While their model wasn’t able to incorporate projected academic paths, the majority of the research conducted conclusively points to relative age differences impacting educational performance. How then, might we address the faults in the current education model in use today? Sometimes the easiest place to begin addressing any issue is to attack its most simple element. Simply put, we first need to acknowledge cut-off dates matter. But how can this arbitrarily selected sorting tool be both so clearly ill-conceived and yet so enduring through the years? Perhaps the motivating factor has less to do with the keys to success for the young student than we’d like to think. “We cling to the idea that success is a simple function of individual merit,” Gladwell states, “and that the world in which we all grow up and the rules we choose to write as a society don’t matter at all” (p. 33). Yet, everything covered in this research has shown the enforcement of a single cut-off date is a detriment to those children (summer-born) having a birthday immediately preceding the cut-off. Use of a single date was a natural start in the formative days of education to sort children into their different classes, however, due to the changing classroom dynamic as previously mentioned, it’s time for a progressive approach. If the current structure allows for relative age differences to be magnified and proliferated, then it is the school’s responsibility to mitigate those effects. The education administration, in looking for the most simple and effective method to curb relative age effects, would be wise to create a classroom setting where young students are competing with other children closely related by age. In a practical sense, elementary and middle schools would separate September through December born kids into their own class. Likewise, the children born between January and April would be assigned to a second class. Finally, a third class would consist of May through August born children so that, in effect, each class would foster the development of children with relatively equal maturity levels. According to Gladwell, such a reorganization, while more complex from an organizational perspective, would not automatically come with a more expensive price tag (2008). I urge federal and state governments to put the needs of the students first and implement this change. Besides, the rate of students repeating grades in the early years of elementary school would stand to drop under the three cut-off date proposal, thereby creating a cost benefit to schools. Schematic changes aside, school administrations need to evaluate the current learning approach in use. Differences in academic development associated with relative age differences demand we pay close attention to early school structures affecting skill accumulation. As such, I call for school administrators and teachers alike to create a culture at the school level where teachers share a commitment to adapting curriculum to the developmental levels of children on student by student basis. How much longer can we afford to sacrifice the needs of the individual in favor of the factory model approach forcing the hand of teachers to solely get the majority of children ready for the next grade? Stressing urgency, I would implore schools to emphasize individual (student) planning to address a wide range of developmental levels in a single classroom to close the gap between the youngest and oldest students. A mountain of data suggesting fundamental flaws in our education system demands our attention. While the United States is certainly not alone in the employment of both the single annual cut-off and factory model-type curriculum, I argue the need is great and the time is now to push for improvements to our education system other countries around the world can model. By switching to three cut-off dates for each class in elementary school and implementing individual student developmental planning the education system will, if not eliminate, greatly reduce the differentiated academic experiences associated with the relative age effect; differences which, if not suppressed at a young age where maturity variances by age have yet to even out, result in long lasting academic disadvantages well beyond adolescence. For those summer born men and women like my brother, Jordan, considering they are already out of school, the proposed changes will have no effect. However, the changes would affect his family. Jordan has two daughters. The oldest, Nora, was born August 18, 2011. Next year she will be eligible to enter kindergarten as one of the relatively youngest students in her class. Physically, she is amongst the smallest of the children in her preschool. Will Nora accumulate academic skills at a slower rate than her older classmates? Possibly, though there are many variables. For instance, the amount of time spent at home by her parents developing her cognitive skills through reading, counting, writing, etc. will have a sizeable impact as well. It is said children, like Nora, are our greatest asset. Parents, teachers, administrators, governments, and policies have an impact on the academic development of these children. The educational system should not be allowed to be the limiting factor.

Bedard, K., & Dhuey, E. (2006). The Persistence of Early Childhood Maturity: International Evidence of Long-Run Age Effects. The Quarterly Journal of Economics, 121(4), 1437-1472.
Bell, J., & Daniels, S. (1990). Are Summer‐born Children Disadvantaged? The Birthdate Effect in Education. Oxford Review of Education, 16(1), 67-80.
Cascio, E. (2007, December 1). First in the Class? Age and the Education Production Function. Retrieved October 4, 2015.
Dougan, K., & Pijanowski, J. (2011). The Effects of Academic Redshirting and Relative Age on Student Achievement. International Journal of Educational Leadership Preparation, 6(2).
Gladwell, M. (2008). Chapter 1 The Matthew Effect. In Outliers: The Story of Success (pp. 25-33). New York, New York: Little, Brown and Company.
Shepard, L., & Smith, M. (1988). Escalating Academic Demand in Kindergarten: Counterproductive Policies. The Elementary School Journal, 89(2), 134-134.

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...Family & Society Instructor: Kara O’Brien February 13, 2012 Non-Parental childcare is very important for many different reasons. It helps working parents attend to their child’s needs when they themselves can’t do so. Non-Parental childcare helps teach and mold children from an early age. It also helps children learn how to become self reliant earlier rather than latter on down the road. I went to a type of non-parental daycare facility it was fun and I was excited to go. I will talk about 3 different types of non-parental child care facilities which are childcare small childcare facility with 12 kids or less, childcare in a center with 30 or more kids, unrelated childcare in the kid’s home. I will then analyze the influences that non-parental childcare has on psychological, social and cognitive development on the children. There are many ways that parents provide for the care of their children during work-times. The setting for child care is a home or a center. The home may be the child’s own home, a relative’s (grandparent, aunt, etc.) home, or the home of an unrelated person. The individual caring for the child in the child’s own home may be the parent, a relative, or an unrelated person such as a babysitter. Home care can include the simultaneous care of many children from many families. Home care is sometimes referred to as family day care, even though the family may not be the child’s own family. I went to Head Start and I loved every minute of it......

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Coronary Diseases

...British Journal of Nutrition (2006), 96, Suppl. 2, S61–S67 q The Authors 2006 DOI: 10.1017/BJN20061865 Nuts and coronary heart disease: an epidemiological perspective ´ John H. Kelly Jr and Joan Sabate* Department of Nutrition, School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA The epidemiological evidence for the cardio-protective effect of nut consumption is presented and reviewed. Four large prospective epidemiological studies of primary prevention of coronary heart disease are reviewed and discussed (Adventist Health Study, Iowa Women’s Health Study, Nurses’ Health Study and the Physicians’ Health Study). Other studies of nuts and coronary heart disease risk are addressed. The combined evidence for a cardio-protective effect from nut consumption is summarized and presented graphically. The risk of coronary heart disease is 37 % lower for those consuming nuts more than four times per week compared to those who never or seldom consume nuts, with an average reduction of 8·3 % for each weekly serving of nuts. The evidence for a causal relationship between nut consumption and reduced risk of coronary heart disease is outlined using Hill’s criteria for causality and is found to support a causal cardio-protective relationship. Nuts: Cardiovascular: Coronary heart disease: Diabetes: Cohort studies: Causality: Hill’s criteria Nuts have constituted a part of mankind’s diet since pre-agricultural times (Eaton & Konner, 1985), providing a complex......

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Survival Notes

...Lecture 12: Introduction to Survival Analysis In many biomedical studies, the outcome variable is a survival time, or more generally a time to an event. We will describe some of the standard tools for analyzing survival data. Most studies of survival last a few years, and at completion many subjects may still be alive. For those individuals, the actual survival time is not known – all we know is how long they survived from their entry in the study. Similarly, certain individuals may drop out from the study or be lost to follow-up. Each of these cases is said to be censored, and the recorded time for such individuals is their time until the censoring event. Example: HPA staining for breast cancer survival We consider data from a retrospective study of 45 women who had surgery for breast cancer. Tumor cells, surgically removed from each woman, were classified according to the results of staining on a marker taken from the Roman snail, the Helix pomatia agglutinin (HPA). The marker binds to cancer cells associated with metastasis to nearby lymph nodes. Upon microscopic examination, the cancer cells stained with HPA are classified as positive, corresponding to a tumor with the potential for metastasis, or negative. It is of interest to determine the relationship of HPA staining and the survival of women with breast cancer. The survival times in months Ti and staining results (xi = 0 for negative and xi = 1 for positive) for the 45 women are presented in the following table. Also......

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Ceo Turnover in Large Russian Firms

...CEO Turnover in large Russian firms Introduction The main responsibility of Chief Executive Officer (CEO) is to form and implement strategic goals, policies and plans of the firms. The most studies show that Executive turnover has positive or negative impacts on firm performance. The decision of CEO’s change is an extremely important issue especially for the firms. There are two ways for a firm to change CEO. First one consists of the obligatory change of CEO depending on external influences due to worsening of firm’s performance. Second one (internal) consists of the resignation of CEO due to better career opportunities, this is a voluntary change, and board initiated turnover. Majority of the studies found in literature review show that CEO decisions and the change of CEO are influential factors on firm’s financial performance and vice versa. Studies such as Helmich (1974), Davidson et al. (1993) have approve that CEO turnover depends on firms' performance positively while Grusky (1964), Allen et al. (1979), Carroll (1984), Beatty and Zajac (1987), Haveman (1993) have argued that CEO change is effecting firms’ performance in a negative way. On the other hand, Boeker (1992) have argued that CEO turnover is not effective at all on firm’s performance. Other than these studies, Kesner and Sebora (1994) have used CEO turnover as a dependent variable. The results of their study showed that the higher turnover CEO results in lower firm performance.......

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