ERIC Identifier: ED339092
Publication Date: 1991-00-00
Author: Gaustad, Joan
Source: ERIC Clearinghouse on
Educational Management Eugene OR.
Identifying Potential Dropouts. ERIC Digest.
The percentage of Americans completing high school has increased steadily
over the past fifty years. Not only have dropout rates been falling, but many
dropouts return to high school or obtain an equivalency certificate within a few
years after dropping out. According to U.S. Census Bureau figures, in 1940 less
than 40 percent of all persons aged 25 to 29 had completed high school; by 1980,
over 85 percent had done so (Finn 1987). Frase (1989) notes that there was an
increase in the annual dropout rate between 1968 and 1978, but the rate has been
declining since then.
Nonetheless, concern about the dropout issue has increased among educators,
policymakers, and the public. Dropout rates remain disturbingly high in certain
areas, particularly major cities, and among certain populations, such as
Hispanics. Moreover, as changes in the nation's economy eliminate jobs for
unskilled workers, dropouts will increasingly suffer in the job market.
Recent legislation to raise high school graduation requirements has provoked
concern that students unable to meet these requirements will drop out, says
Rumberger (1987). State and federal efforts to evaluate and improve school
performance have stimulated attempts to more accurately measure dropout rates,
to identify potential dropouts, and to develop programs to help them.
WHICH STUDENTS ARE MOST AT RISK?
Most studies agree that
the main factors associated with dropping out include students' socioeconomic
status, location, school behavior, and academic achievement.
"Dropout rates are higher for students coming from low socioeconomic
backgrounds, from single-parent families, and from non-English language family
backgrounds," stated Frase in the first annual report by the National Center for
Education Statistics. This nationwide study also found higher dropout rates for
students living in cities than in suburbs or rural areas, and in the South and
West rather than in the Northeast. Students who marry or have children, or who
have had problems with the law or school authorities, are also at greater risk.
Academic factors are clearly related to dropping out. Students who received
poor grades, who had repeated a grade, who were overage for their class, and who
had poor attendance for reasons other than illness were more likely to drop out.
"A powerful predictor...was the attendance record during the first four months
of tenth grade," Frase reported.
Barrington and Hendricks (1989) found that dropouts in a Wisconsin community
showed clear indications of academic problems by the third grade. Their
achievement test scores were significantly lower than those of their classmates
and also below their ability as measured by intelligence tests; teacher comments
alone identified potential dropouts with 63 percent accuracy. Poor attendance,
failing grades, and low overall GPA marked these students' high school careers.
Unfortunately, uncontrolled variables complicate the process of accurately
identifying dropouts, as we shall see below.
HOW ARE DROPOUTS DEFINED AND CALCULATED?
among states, districts, and even among schools within the same district. In
addition, the criteria used to define dropout are sometimes questionable,
resulting in statistics that don't accurately reflect the problem.
For example, some institutions count as dropouts students who transfer to
other schools, are hospitalized, take longer than four years to graduate, or are
admitted early to college. "One district treated a student who had died as a
dropout," note Barber and McClellan (1987). Some don't count students who leave
to get married, who attend for four full years, or who exceed the compulsory
attendance age but haven't fulfilled graduation requirements.
LeCompte and Goebel (1987) describe how recordkeeping problems can contribute
to inaccurate totals. In one pilot study, 25 percent of a group of "dropouts"
turned out to have transferred; the transfer requests in their folders just
hadn't been entered into the computer. And if "acts of dropping out" are
measured, a student who drops in and out repeatedly will be counted more than
once. On the other hand, if students who have dropped out remain on the rolls,
the error benefits schools whose funding depends on enrollment--a situation that
doesn't encourage vigorous attempts at accuracy.
When the count is made also affects the totals. If dropouts are recorded only
during the academic year, students who don't return after the summer--which may
constitute one-third of all dropouts--are overlooked. And collecting statistics
only from grades 9 through 12 misses kids who dropped out earlier (LeCompte and
WHY IS PREDICTING DROPOUTS DIFFICULT?
Although a number of
factors are correlated with dropping out, this does not mean that these factors "cause" individuals to drop out (Finn). In addition, the interaction of
multiple, complex variables makes it hard to determine which ones are
For example, overall dropout rates are higher for African-Americans than for
whites, but race turns out not to be the crucial factor. When social background
is factored in, reports Frase, "dropout rates for blacks are not higher, and in
some cases may be lower, than those for whites."
On the other hand, Fernandez and Shu (1988) found that Hispanic students in a
national sample dropped out at significantly higher rates than other students,
even when factors such as family income, academic achievement, and parents'
educational level were considered.
Different risk factors are important in different communities. Even within
the same school, students drop out for different reasons. Finally, most dropouts
are simply unexplained. The majority of students with any particular risk factor
do not drop out, and the majority of dropouts are not in the at-risk groups.
For example, as Frase reports, "Of the dropouts from the 1980 sophomore
class: 66 percent were white, 86 percent had an English language home
background, 68 percent came from two-parent families, 42 percent had neither
children nor spouses, and 71 percent had never repeated a grade."
HOW USEFUL ARE CURRENT MODELS FOR PREDICTING DROPOUTS?
margin for error in current prediction models clearly limits their value. For
example, in 1987 the Texas legislature required school districts to identify
students who were at risk of dropping out. Four criteria were mandated: being
overage for grade, being two or more years below grade level in mathematics or
reading skills, failing two or more courses during a semester, or failing any
section of the state minimum skills tests.
Evaluators at the Houston Independent School District found these criteria
had serious limitations (Bowman and others 1991). To begin with, 40.6 percent of
the district's secondary school students fell into at least one of the at-risk
categories, over 50 percent on some campuses, too large a target for meaningful
In terms of predictive accuracy, only 13.9 percent of Houston's at-risk
students actually dropped out, and almost half the dropouts were not predicted.
A study of nine other Texas districts found even lower accuracy: 61.7 percent of
dropouts were not predicted (Parsons, Saye, and McNamara 1990).
Bowman and his colleagues found that using combinations of the four criteria
increased accuracy to 32.3 percent at best--an improvement, but still
WHAT CAN BE DONE TO IMPROVE PREDICTION?
Before we can
predict who will drop out, we must know who is dropping out. Experts agree that
educators and policymakers must set a standard definition of dropping out before
accurate, comparable data can be collected. LeCompte and Goebel say only a
federal mandate can ensure uniformity in definitions as well as in basic
reporting procedures among states and districts.
To date, most studies have covered only the high school years; more data are
needed on younger dropouts. The National Education Longitudinal Study of 1988,
which follows a representative nationwide sample of eighth-graders, will
ultimately provide more data than its predecessor, High School and Beyond, which
began with tenth-graders (Frase). Several researchers urge that statistics be
collected starting with elementary school. It is hoped such studies will
identify characteristics that permit earlier intervention.
More accurate recordkeeping is essential. Barber and McClellan believe the
necessary technology and personnel are already available. However, LeCompte and
Goebel express concern about the ability of smaller and poorer districts to
finance up-to-date, computerized recordkeeping systems.
A systematic means of tracking transfers would be desirable. LeCompte and
Goebel suggest a nationwide system modeled after the Migrant Student Record
Transfer system but acknowledge the cost may be prohibitive. As a low-tech
alternative, they suggest districts be required to request transcripts for all
transfer students and record requests in a uniform manner.
Research may eventually produce more accurate models for predicting dropouts.
In the meantime, although educators may want to pay special attention to
students with the risk factors mentioned above, they must not overlook the
majority of potential dropouts who are not obviously "at risk."
Barber, Larry W., and Mary C. McClellan. "Looking
at America's Dropouts: Who Are They?" PHI DELTA KAPPAN 69,4 (December 1987):
264-67. EJ 363 376.
Barrington, Byron L., and Bryan Hendricks. "Differentiating Characteristics
of High School Graduates, Dropouts, and Nongraduates." THE JOURNAL OF
EDUCATIONAL RESEARCH 82,6 (July/August 1989): 309-19. EJ 398 453.
Bowman, Clay, and others. "Making the Best of State-Mandated At-Risk
Criteria." Houston Independent School District Department of Research and
Evaluation. Paper presented at the Annual Meeting of the American Educational
Research Association, Chicago, Illinois, April, 1991.
Fernandez, Ricardo R., and Gangjian Shu. "School Dropouts: New Approaches to
an Enduring Problem." EDUCATION AND URBAN SOCIETY 20,4 (August 1988): 363-86. EJ
Finn, Chester E., Jr. "The High School Dropout Puzzle." THE PUBLIC INTEREST
87 (Spring 1987): 3-22. EJ 355 110.
Frase, Mary J. DROPOUT RATES IN THE UNITED STATES: 1988. Washington, DC:
National Center for Education Statistics, 1989. 114 pages. ED 313 947.
LeCompte, Margaret D., and Stephen D. Goebel. "Can Bad Data Produce Good
Program Planning? An Analysis of Record-Keeping on School Dropouts." EDUCATION
AND URBAN SOCIETY 19,3 (May 1987): 250-68. EJ 356 409.
Parsons, James L.; Elaine Saye; and James F. McNamara. "1988-89 Student
Dropout Research Project: An Aggregate Report of Nine Collaborative School
Districts." Texas A&M School/University Research Collaborative. Paper
presented at the Fourth Annual Collaborative Research Conference, January 12,
Rumberger, Russell W. "High School Dropouts: A Review of Issues and
Evidence." Review of EDUCATIONAL RESEARCH 57,2 (Summer 1987): 101-21. EJ 369