Tuesday, April 30, 2013
Absent Peers in Elementary Years: The Negative Classroom Effects of Unexcused Absences on Standardized Testing Outcomes
Background/Context: This article addresses the classroom contextual effects of absences on student achievement. Previous research on peer effects has predominantly focused on peer socioeconomic status or classroom academic ability and its effects on classmates. However, the field has been limited by not discerning the individual-level academic effects of being in classrooms with absent peers.
Population/Participants/Subjects: The data set is longitudinal and comprises entire populations of five elementary school cohorts within the School District of Philadelphia, for a total of 33,420 student observations. Individual student records were linked to teacher and classroom data and to census block neighborhood information.
Research Design: To examine the educational effects of absent peers, this study employed an empirical specification of the education production function. The dependent variables were Stanford Achievement Test Ninth Edition (SAT9) reading and math scores.
Findings: Models differentiated between unexcused and total absence measures and indicated that the peer effect of absences was driven by negative effects associated with classroom rates of unexcused absences rather with rates of total absences. These findings were obtained after controlling for student, neighborhood, teacher, and classroom characteristics.
Conclusions/Recommendations: Not only are absences detrimental to the absentee, but they also have a pervasive effect on the achievement of other students in the classroom.
Since the dissemination of the Coleman Report (Coleman et al., 1966), economists, sociologists, education researchers, and policy makers have been assessing the relationship between classroom peer effects and educational outcomes. The basic premise is that stronger peers can produce better academic outcomes for their classmates. In the analyses of classroom composition, the research has focused predominantly on peer effects relating to socioeconomic status (SES) (Caldas & Bankson, 1997; Link & Mulligan, 1991; Willms, 1986) and classroom academic ability (Henderson, Mieszkowski, & Sauvageau, 1978, Summers & Wolfe, 1977; Zimmer & Toma, 2000). Nonetheless, even conditional on these characteristics, there remain other channels through which students can affect other students.
One uncharted line of research on the educational effects of peers is the relationship between classroom absences and student-level performance. The importance of this peer effect arises because research has thus far shown that being absent from school is detrimental to learning and academic achievement, and an increase in absences will exacerbate educational and sociological risk factors in concurrent and future years (Dryfoos, 1990; Finn, 1993; Lehr, Hansen, Sinclair, & Christenson, 2003; Stouthamer-Loeber & Loeber, 1988). As for individual test performance, absent students receive fewer hours of instruction and consequently are likely to perform more poorly on exams (Chen & Stevenson, 1995; Connell, Spencer, & Aber, 1994; Finn, 1993). In addition, when present in the classroom, highly absent students may feel a greater sense of alienation from their classmates, teachers, and schools and may thus disrupt classroom instruction through their negative interactions and social disengagement (Ekstrom, Goertz, Pollack, & Rock, 1986; Finn, 1989; Johnson, 2005; Newmann, 1981).
Hence, the peer effect of individual student absences can arise from both academic and behavioral sources. Academically, if absent students receive fewer hours of instruction and their in-school learning time decreases, then on their return, they often require remedial instruction (Monk & Ibrahim, 1984). If teachers respond to educational needs of absent students by allocating regular class time, then nonabsent students may be adversely affected because classroom instruction is slowed. Increasingly large numbers of absences in the classroom would suggest larger portions of instruction dedicated to remediation, thereby further slowing educational advancement for other students in the room. Similarly, if absences generate negative behavioral outcomes, such as school disengagement or alienation, and if these behaviors in turn produce further problems in school (Finn, 1989), then absent students can generate noninstructional (i.e., behavioral) disruptions on return to the classroom (Reid, 1983), which can also slow the learning process for nonabsent peers. That is, teachers must devote their instructional resources elsewhere rather than to teaching.
Lazear (2001) theorized about this phenomenon by proposing that education in the classroom can be classified as a public good, in which congestion effects exist on the teacher’s instructional time. As such, negative effects on learning are generated when one student’s actions impede the learning of other classmates. According to this notion, an absent student who disrupts regular instruction on return to school utilizes teaching time in ways that nonabsent students may not find useful. In essence, absent students produce both an individual effect by decreasing their own learning from having missed school, and a peer effect by slowing instruction and reducing the educational outcomes for others in the class.
Given the individual and classroom risk factors associated with being absent, this article empirically considers the classroom peer effects of students with unexcused absences. Although some studies have evaluated the relationship between student-level absences on individual-level achievement, and others have assessed school-level effects of absences on educational outcomes, the literature has been limited on discerning the effects of classroom-level absences on student-level achievement. That is, the extant body of research has not fully considered the classroom effect of absent peers on student-level test performance.
This study contributes to the literature on attendance by evaluating the classroom contextual effects of absences on individual student achievement. Because this study has been afforded multilevel data of elementary school students in the School District of Philadelphia from 1995 to 2001, it is possible to link students to classrooms, teachers, and schools, as well as other covariates, such as demographic information and neighborhoods. Therefore, having comprehensive multilevel and longitudinal data of elementary school students in a large urban district allows for the designation of student absences, identification of classroom peers, and subsequent construction of individual and classroom peer metrics of absences for every student’s schooling experience.
Furthermore, the field has predominantly focused on measures of total absences. However, absences can be defined in two ways—excused and unexcused. As such, students may be exposed to peers with high levels of excused absences, though absences by these students may not signal academic, family, or social disengagement or other problems. On the other hand, a classroom may contain students with high levels of unexcused absences, which may arise from delinquency or school disengagement and not for the same reasons as excused absences (Hess, Lynon, Corsino, & Wells, 1989; Rumberger, 1995).
The difficulty in relying on the current empirical literature is that most studies have not differentiated between unexcused absences and total absences. As a consequence, the findings from these studies may potentially contain confounding issues resulting from not parsing out the effects of absence behavior deemed unexcused (by the teacher and school) from other factors of absences (i.e., a general metric of absences does not differentiate between a high-performing student with the flu, and a student with behavior or disengagement issues). To avoid these problems, this article draws distinctions between total absences and unexcused absences in constructing measures of student- and classroom-level covariates as a way to discern individual and peer effects of missing school in general from those resulting from unexcused absence behavior.
Finally, the research on absences has predominantly focused on the educational outcomes of high school students. The effects of absences on elementary school performance are lacking in the research on attendance, and empirically, studying peer effects of absent students in elementary schools allows for two advantages. The first is that unlike high school students in large urban school districts like Philadelphia, elementary school students are generally contained within the same classroom throughout the school day and academic year. As a result, studying elementary classrooms allows for a more clear-cut identification of peers with whom other students interact. This effect is too confounded in empirical studies on high school students, who move classrooms throughout the school day with the start of each new period. Thus, because classroom peers potentially alternate five to six times per day, the peer effects for high school students (and some middle school students) are difficult to identify and are potentially diluted. There is a second advantage that is particularly germane to this sample: By identifying significant factors in the schooling experiences of urban elementary youth, it is possible to develop policy and support interventions for at-risk students early in school, before chronically absent students enter into secondary education, where their risk of dropout or postgraduation misbehaviors becomes exacerbated (Alexander, Entwisle, & Horsey, 1997; Barrington & Hendricks, 1989; Lehr et al., 2003).
EMPIRICAL LITERATURE ON ABSENCES
Given that the purpose of this study is to evaluate the relationship between absent peers and academic attainment, the relevant literature focuses empirically on the relationship between absences as a predictor and educational performance as an outcome. In early research, Summers and Wolfe (1977) implemented a student-level economic model of achievement to derive a relationship between unexcused absences and sixth-grade standardized test performance in the School District of Philadelphia during the 1970–1971 school year. Their cross-sectional results suggested a negative effect of unexcused absences on student achievement, which was heightened for low-SES students. However, their work did not evaluate the classroom peer effects of students with unexcused absences on individual test performance.
Among other hypotheses in their assessment of student absences, Monk and Ibrahim (1984) examined the peer effects of highly absent students. In particular, the authors evaluated the relationship between absences and achievement by utilizing a data set of 227 ninth graders in one middle school in upstate New York. The results suggested negative individual- and classroom-level effects on standardized ninth-grade test performance resulting from an increase in absences both for students and their peers. Although Monk and Ibrahim relied on a small sample of a single grade in one school within a homogenous school district, this early study laid the foundation for further empirical research in two capacities. First, in evaluating achievement, the authors did not distinguish between effects of total absences and unexcused absences. Therefore, additional research could parse out the effects of unexcused absences from overall absences of classroom peers on student testing performance. Second, rather than assessing the effects of absences on multiple grades, their analysis only relied on ninth-grade students. Thus, there is a need to evaluate the effects of absences at other school levels, such as early elementary years.
Several longitudinal studies have examined how attendance patterns in early years of schooling can predict future dropout rates (Alexander et al., 1997; Barrington & Hendricks, 1989; Hess et al., 1989). Rumberger (1995) identified student- and institution-level factors that significantly relate to dropout in middle school. The results suggested that the classification of students as having moderate or high absence patterns significantly predicted the probability of dropout. Odds ratios, which can be used as measures of effect sizes when both independent and dependent variables are binary, suggested odds of 2.03 (p < .01) for dropout related to moderate absenteeism and odds of 5.10 (p < .01) for students with high rates of absenteeism.
Other empirical studies have used metrics of current attendance or absences to evaluate contemporaneous educational outcomes. Neild and Balfanz (2006) utilized a cross-section of students in the 1999–2000 academic year and employed logistic regressions to predict the risk factors of nonpromotion from 9th to 10th grade. Among other results, they reported that for each additional percentage point increase in eighth-grade attendance, the odds of repeating ninth grade decreased by 5%. The odds ratio for this result was reported as .96 (p < .001). Although that paper focused on high school achievement, the work nonetheless provided insight into how student-level attendance and absence information is directly related to student-level performance.
Balfanz and Byrnes (2006) evaluated comprehensive school reform models aimed at closing the math achievement gap in urban middle schools. Among the span of covariates predicting math improvement was attendance, with results indicating a 20% difference in the probability of higher math performance for students with 60% attendance rates versus those who attended every day. Like Neild and Balfanz (2006), attendance was measured for each student, though no distinction was made between total absences and unexcused absences, nor was there an evaluation of classroom peer effects.
Other studies have evaluated the school-level contextual effects of elementary school attendance on standardized test performance, thereby providing initial insight into educational effects of absent peers. Assessing Louisiana public elementary schools, Caldas (1993) studied the effects of school attendance rates, among other covariates, on a composite index of test scores. The results indicted that a one standard deviation increase in average daily school attendance was associated with a .10 (p < .001) standard deviation increase in student-level test performance. This indicated that from within the context of the school environment, average daily student attendance was a positive and significant factor in predicting same-year academic performance for inner-city students. Similarly, Roby (2004) concluded that, based on the analysis of educational outcomes in Ohio, there were statistically significant correlation coefficients (specifically, Pearson’s r) between measures of school-level attendance and student achievement in fourth, sixth, ninth, and twelfth grades. Specifically, the correlation coefficients were .57, .54, .78, and .55 for each grade, respectively. These two studies have employed measures of attendance at the aggregated school level rather than for individual students or classrooms. Doing so has facilitated the opportunity for further in-depth student- and classroom-level analyses into the peer effects of the attendance–achievement relationship.
Within the framework of this body of empirical literature—in examining how missing or attending school can impact a range of academic outcomes—this study investigates individual- and peer-level effects of absences on annual student standardized testing performance, holding constant other predictors of academic achievement. To truly capture this relationship requires the use of empirical methods based on a large-scale individual-level data set in which students, teachers, and classrooms can be identified and in which absence measures can be parsed out for each student and peer group.
The complete research study, click here.
Decisions about whether to contract out support services or keep them in-house are influenced by many factors
In some cases, districts find that they can reduce expenses, especially in salary and benefits, or secure specialized services that would be hard to provide in-house, by seeking bids and selecting private companies to do the work.
In other circumstances, districts may find that outside businesses' costs are too high, and that their ability to provide the exact services needed are lacking, so they choose to have the work done by the people already on the payroll.
At the same time, many districts are among the largest employers in their communities, and few school officials are eager to lay off workers they know, even in the name of reducing costs.Districts' decisions about whether to contract out services or keep them in-house are influenced by myriad and often competing factors. School leaders want to cut expenses, while protecting money going to classroom instruction, and the pressure to trim cost was particularly strong during the Great Recession, from which states and districts only recently have begun to emerge.
"Every district wants to be a good employer and make sure that their employees are treated well," said James M. Hohman, the assistant director of fiscal policy for the Mackinac Center for Public Policy, a Midland, Mich., think tank that advocates free-market policies. The center sees contracting out for services, when that work can be performed effectively, as an "established way" for districts to save money, he said.
But unions representing support-service workers view many efforts to privatize services with skepticism.
"Privatization moves quality control away from the parents of the children these services are intended to support," said Ruby J. Newbold, an American Federation of Teachers vice president, in a statement toEducation Week, when asked about districts' decisions to contract out services. She is also the president of the Detroit Association of Educational Office Employees.
Estimates of cost savings through privatization are often exaggerated, Ms. Newbold argued. "Today's privatization bargain," she said, "quickly becomes tomorrow's increasingly costly contract that features less control and oversight."
National data on districts' contracting out for support services are limited, and the information that does exist offers a mixed picture.
A survey of state education departments, conducted in 2007 by the Mackinac Center, found that 13 percent of public school districts taking part in the federal National School Lunch Program contract meal services out to private companies, though the portion of systems doing so in each state varies enormously.
About 10 percent of districts said they outsourced custodial or maintenance services during the 2011-12 school year, according to a survey by the American Association of School Administrators, based in Alexandria, Va. The association also found that a greater number of districts, about 20 percent, said they were considering taking that step in 2012-13.
In Michigan, 61 percent of the state's 549 school districts reported they had privatized one or more support services, a number that has increased steadily from 31 percent a decade earlier, according to a Mackinac Center report released this year. The increases in contracting out were pushed along by changes in state policy from the 1990s to today that have made it easier for districts to privatize certain services, Mr. Hohman said.
Those policies included a 2011 law signed by Gov. Rick Snyder, a Republican, that offered districts financial incentives to obtain competitive bids on noninstructional services.
Even so, the decision to privatize services can be an agonizing one, as was the case in the Lake Orion Community School District, a 7,600-student system north of Detroit, where the school board voted last year to contract its custodial services out to a private company.
Felicia Hicks, a field staff representative for Council 25, the Michigan affiliate of the American Federation of State, County, and Municipal Employees, which represented the district custodial workers, argued that the district's estimates of savings from privatization were overstated, because a contractor could not match the breadth of services provided by the public employees at a lower cost. The decision was not based on realistic "dollar for dollar" and "work for work" comparisons, she argued. "It was a totally misguided decision," she said.The district has seen its tax base shrink by roughly one-third over the past six years or so, with job losses in the auto industry and other businesses, and it has been forced to cut spending, said John Fitzgerald, the system's assistant superintendent for business and finance.
About 50 custodial workers — many of whom handled multiple duties as "jacks of all trades" — lost their jobs, though they were invited to reapply with the private company, said Mr. Fitzgerald.
"It was probably the most dramatic decision the board had made in decades," Mr. Fitzgerald said of going with a private contract. "It was an extremely stressful time. ... These are all people we see every day. These are people the board members are seeing at the grocery store, at the movie theater."
Coverage of entrepreneurship and innovation in education and school design is supported in part by a grant from Carnegie Corporation of New York.
Monday, April 29, 2013
Sunday, April 28, 2013
Data and thoughts on public and private school funding in the U.S.
In my previous post I chastised state officials for their blatant mischaracterization of metrics to be employed in teacher evaluation. This raised (in twitter conversation) the issue of the frequent misrepresentation of findings from the Gates Foundation Measures of Effective Teaching Project (or MET). Policymakers frequently invoke the Gates MET findings as providing broad based support for however they might choose to use, whatever measures they might choose to use (such as growth percentiles).
Here is one example in a recent article from NJ Spotlight (John Mooney) regarding proposed teacher evaluation regulations in New Jersey:
New academic paper: One of the most outspoken critics has been Bruce Baker, a professor and researcher at Rutgers’ Graduate School of Education. He and two other researchers recently published a paper questioning the practice, titled “The Legal Consequences of Mandating High Stakes Decisions Based on Low Quality Information: Teacher Evaluation in the Race-to-the-Top Era.” It outlines the teacher evaluation systems being adopted nationwide and questions the use of SGP, specifically, saying the percentile measures is not designed to gauge teacher effectiveness and “thus have no place” in determining especially a teacher’s job fate.The state’s response: The Christie administration cites its own research to back up its plans, the most favored being the recent Measures of Effective Teaching (MET) project funded by the Gates Foundation, which tracked 3,000 teachers over three years and found that student achievement measures in general are a critical component in determining a teacher’s effectiveness.
I asked colleague Morgan Polikoff of the University of Southern California for his comments. Note that Morgan and I aren’t entirely on the same page on the usefulness of even the best possible versions of teacher effect (on test score gain) measures… but we’re not that far apart either. It’s my impression that Morgan believes that better estimated measures can be more valuable – more valuable than I perhaps think they can be in policy decision making. My perspective is presented here (and Morgan is free to provide his). My skepticism in part arises from my perception that there is neither interest among or incentive for state policymakers to actually develop better measures (as evidenced in my previous post). And that I’m not sure some of the major issues can ever be resolved.
That aside, here are Morgan Polikoff’s comments regarding misrepresentation of the Gates MET findings – in particular, as applied to states adopting student growth percentile measures:
As a member of the Measures of Effective Teaching (MET) project research team, I was asked by Bruce to pen a response to the state’s use of MET to support its choice of student growth percentiles (SGPs) for teacher evaluations. Speaking on my behalf only (and not on behalf of the larger research team), I can say that the MET project says nothing at all about the use of SGPs. The growth measures used in the MET project were, in fact, based on value-added models (VAMs) (http://www.metproject.org/downloads/MET_Gathering_Feedback_Research_Paper.pdf). The MET project’s VAMs, unlike student growth percentiles, included an extensive list of student covariates, such as demographics, free/reduced-price lunch, English language learner, and special education status.Extrapolating from these results and inferring that the same applies to SGPs is not an appropriate use of the available evidence. The MET results cannot speak to the differences between SGP and VAM measures, but there is both conceptual and empirical evidence that VAM measures that control for student background characteristics are more conceptually and empirically appropriate (link to your paper and to Cory Koedel’s AEFP paper). For instance, SGP models are likely to result in teachers teaching the most disadvantaged students being rated the poorest (cite Cory’s paper). This may result in all kinds of negative unintended consequences, such as teachers avoiding teaching these kinds of students.In short, state policymakers should consider all of the available evidence on SGPs vs. VAMs, and they should not rely on MET to make arguments about measures that were not studied in that work.Morgan
Baker, B.D., Oluwole, J., Green, P.C. III (2013) The legal consequences of mandating high stakes decisions based on low quality information: Teacher evaluation in the race-to-the-top era. Education Policy Analysis Archives, 21(5). This article is part of EPAA/AAPE’s Special Issue On Value-Added: What America’s Policymakers Need to Know and Understand, Guest Edited by Dr. Audrey Amrein-Beardsley and Assistant Editors Dr. Clarin Collins, Dr. Sarah Polasky, and Ed Sloat. Retrieved [date], fromhttp://epaa.asu.edu/ojs/article/view/1298
Ehlert, M., Koedel, C., Parsons, E., & Podgursky, M. (2012). Selecting Growth Measures for School and Teacher Evaluations. http://ideas.repec.org/p/umc/wpaper/1210.html
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