356 N.A. Alexander Economics of Education Review 19 2000 351–361
student population of the variables used in the analyses are presented in Table 3.
3. Findings
The data in Table 4 are the estimates derived for the models of generic measures of student performance as
outputs in the education production process. The general measures of achievement used are 4-year college attend-
ance, diploma type, and retention rates. Dummy vari- ables are used to capture the award of a variance in any
subject. Interaction variables were created between the student demographic variables and the receipt of a vari-
ance to explore if approved variances altered the associ- ation between the profile of schools and student out-
comes. Faculty, district size, school diversity and organization are also included as controls. Most of the
background variables have the expected associations with educational outcomes.
Even when non-policy variables e.g. historical trends, diversity of the student body, etc. are controlled for, the
association between the award of a subject variance and portion of graduates with Regents diplomas remains. The
data suggest receipt of a variance causes the portion of graduates receiving Regents diplomas to increase by
0.5. This represents a 1.87 increase over pass rates before this strategy was pursued. However, the results
also indicate that this curriculum policy is not as relevant for retention rates or the rates at which graduates sub-
sequently attend 4-year colleges.
The estimates imply that increased portions of black and Latino students are associated with lower portions
of Regents diplomas granted. Poverty considerations do not play a big role in any of the generic educational out-
comes. Moreover, there is no substantial difference in the link between school profile and educational achievement
before and after applying a variance. That is, curriculum standards policies do not seem to affect the relationship
between race, poverty, and student outcomes.
By contrast, subject variances matter for pass rates i.e. 65 in Regents Global Studies, Regents English,
and Regents Biology. Approved variances in those sub- jects resulted in an increase in the portion of students
passing; this increase was by 1.68, 1.88, and 3.96 for global studies, English, and biology, respectively. The
data in Table 5 are the estimates derived for subject- specific models of curriculum policy. Educational out-
puts are defined as the percentage of enrolled students passing the Regents in a particular field. The standards
are also categorized according to specific subjects, where biology variances are distinguished from English vari-
ances, math variances, and so on.
To facilitate presentation, Table 5 does not specify the class size nor the education and the experience of the
faculty for each Regents course. Instead, a generic for- mat is adopted for the table where the average size of
the Regents class culminating in the specified exam is represented by “Course class size”. Thus, when the
dependent variable is the percentage of average 9–12 grade enrollment passing biology, “Course class size” is
the average class size for Regents Biology. Similarly, the average size of the 10th grade class in a particular field
is represented by “Average subject size”. When the dependent variable is the percentage of average 9–12
grade enrollment passing biology, “Average subject size” is the average size of a 10th grade science class in the
district. The experience and education of the faculty teaching the Regents courses culminating in the specified
exams are represented by “Average experience of course teacher” and “Course faculty with masters”, respectively.
Thus, when the dependent variable is the percentage of average 9–12 grade enrollment passing biology, “Aver-
age experience of course teacher” reflects the average number of years of teaching experience of faculty teach-
ing Regents Biology. “Course faculty with masters” rep- resents the portion of the faculty teaching Regents
Biology that has a master’s education or above. Similar procedures were followed for all other subjects.
Given the percentage points noted above and the mean pass rates of global studies, English, and biology, the
effect of awarding variances becomes more meaningful. Absence of approved variances in those subjects would
likely result in 3 fewer students passing global studies, 3.4 fewer students passing English, and a striking
10.2 fewer students passing biology. These improved pass rates suggest that implementation of a standards
policy can influence curricula mastery.
4. Discussion and implications for public policy
This 6-year study has traced the effect of awarding variances on average student performance in all public
school districts in New York State, excluding New York City. It is presumed that pursuit of this policy is reflec-
tive of broader standards-based plans. The results of this study yield mixed reviews on the impact of educational
policies relying on using curriculum standards as a means of reforming education.
The significant and positive association between the award of a subject variance and the portion of graduates
receiving Regents diplomas implies that this policy is successful. This finding, coupled with the insignificant
association with retention rates, suggests that pupils can be challenged to “jump higher” without being discour-
aged from finishing high school. However, since students still had the option to take RCTs even after a district’s
receipt of a “50–64” variance, it is unclear that this association will hold when this option is removed. More-
over, the insignificant association between the variance policy and 4-year college attendance rates suggests that
357 N.A. Alexander Economics of Education Review 19 2000 351–361
Table 3 Definitions and simple statistics of the variables used in this study
Variable N
Mean weighted Standard Definitions by 9th–12th
deviation grade student
population Curriculum policy
STDS 3864
0.0664 0.249 dummy variable representing receipt of any subject variance; coded 1 if
received; 0 otherwise BISTD
3864 0.0174
0.131 dummy variable representing receipt of variance in Regents Biology; coded 1 if received; 0 otherwise
ENSTD 3864
0.0528 0.223 dummy variable representing receipt of variance in Regents Comprehensive
English; coded 1 if received; 0 otherwise GSSTD
3864 0.0544
0.226 dummy variable representing receipt of variance in Regents Global Studies; coded 1 if received; 0 otherwise
MASTD 3864
0.0550 0.228 dummy variable representing receipt of variance in Regents Mathematics I;
coded 1 if received; 0 otherwise USSTD
3864 0.0584
0.235 dummy variable representing receipt of variance in Regents US History; coded 1 if received; 0 otherwise
Management AVGEN
3822 21.41
3.072 average number of students in a 10th grade English class AVGMA
3616 20.65
3.57 average number of students in a 10th grade mathematics class
AVGSC 3793
20.81 3.21
average number of students in a 10th grade science class AVGSOC
3833 21.78
3.09 average number of students in a 10th grade social studies class
HIGHT 3893
1657 1884
number of public school children in 9–12 grades in the district SIZEBI
3718 22.9
89.32 average number of students in a Regents Biology class
SIZEEN 3755
21.3 87.79
average number of students in a Regents Comprehensive English class SIZEGS
3793 22.1
82.20 average number of students in a Regents Global Studies class
SIZEMA 3857
22.5 82.13
average number of students in a Regents Math I class SIZEUS
3812 21.9
84.99 average number of students in a Regents US History class
PCENT 4450
0.076 0.081 portion of administrative personnel assigned to the central office relative to
total administrative personnel; used as a proxy for degree of centralization Faculty
EXPTOT 3893
19.4 2.67
average number of years of teaching experience of faculty teaching 9th–12th grade in the district
EXPBI 3695
19.87 6.29
average number of years of teaching experience of faculty teaching Regents Biology
EXPEN 3740
20.88 5.30
average number of years of teaching experience of faculty teaching Regents level English
EXPGS 3773
19.49 6.25
average number of years of teaching experience of faculty teaching Regents Global Studies
EXPMA 3855
20.41 4.68
average number of years of teaching experience of faculty teaching Regents Math I
EXPUS 3807
21.65 5.81
average number of years of teaching experience of faculty teaching Regents US History
MASTER 3755
0.74 0.15
dummy variable representing the portion of teachers with a master’s degree or above; coded 1 for teachers with at least a masters; 0 otherwise
MASTBI 3718
0.777 0.300 dummy variable representing the portion of faculty teaching Regents Biology
with a master’s degree or above MASTEN
3755 0.763
0.287 dummy variable representing the portion of faculty teaching Regents Comprehensive English with a master’s degree or above
MASTGS 3793
0.734 0.297 dummy variable representing the portion of faculty teaching Regents Global
Studies with a master’s degree or above MASTMA
3857 0.756
0.246 dummy variable representing the portion of faculty teaching Regents Math I with a master’s degree or above
MASTUS 3812
0.77 0.291 dummy variable representing the portion of faculty teaching Regents US
History with a master’s degree or above continued on next page
358 N.A. Alexander Economics of Education Review 19 2000 351–361
Table 3 continued Variable
N Mean weighted Standard Definitions
by 9th–12th deviation
grade student population
Diversity PADV
3893 0.022
0.016 portion of courses that are devoted to an advanced curriculum, including Advanced Placement and college credit courses; used as a proxy for portion
of high achievers PMIN
3893 0.073
0.153 portion of district’s 9th–12th grade student population comprised of black and Latino students
SRPMA 4087
91.34 4.47
percentage of students scoring above the NYS reference point for mathematics; used as a proxy for degree of preparedness
SRPRD 4087
96.71 7.41
percentage of students scoring above the NYS reference point for reading; used as a proxy for degree of preparedness
WELF 3893
0.127 0.125 portion of children from families whose primary means of support is a public
welfare program. Data originally coded in ranges; study uses midpoint of that range; used as a proxy for poverty
Outcomes P4YR
3868 0.429
0.16 portion of high school graduates planning to attend a 4-year college
PAGBI 3919
39.13 19.08
percent of average grade enrollment 9–12 passing Regents Biology PAGEN
3919 55.20
18.78 percent of average grade enrollment 9–12 passing Regents Comprehensive
English PAGGS
3919 55.87
17.20 percent of average grade enrollment 9–12 passing Regents Global Studies
PAGMA 3919
40.26 20.43
percent of average grade enrollment 9–12 passing Regents Mathematics PAGUS
3919 42.05
20.49 percent of average grade enrollment 9–12 passing Regents US History
PRDIP 3873
0.301 0.078 portion of regular degree graduation candidates that received the more
prestigious Regents Diploma RETENT
3954 0.97
0.022 the portion of students currently in school as a portion of previous 9–12 enrollment; calculated as 12the dropout rate
there is more that can be done to improve student per- formance in that area.
The results are promising with regard to the effect on curricula mastery of receiving a variance. In three of the
five subjects examined, awarding a subject-specific vari- ance appears to have a positive and significant associ-
ation with the portion of enrolled students passing selec- ted subjects. This positive association is there even after
district-specific attributes are controlled for. Neverthe- less, the typical pass rates in these subjects remain low—
ranging from 39.1 of students for Regents Biology to 55.9 for Global Studies. If it is assumed that it is the
discipline and other intangible interpersonal skills trans- ferred during high school that is important to post-sec-
ondary activities, then these low rates may not be very important. If, however, it is assumed that the skills trans-
ferred during classes have more practical and direct implications, then this limitation becomes more substan-
tial.
As currently designed, standards policies do not appear to affect the relationship between race, poverty,
and student outcomes. There remains substantial associ- ations between student achievement and the portion of
poor andor minority students attending school. These findings suggest that the level of preparedness provided
to students in schools with high portions of disadvan- taged students is inadequate to meet the challenges of
the new standards. Consequently, the transfer costs involved in switching from the status quo to the new
system are potentially higher for these schools, suggest- ing the need for a higher level of initial commitment to
these areas. This strategy seems to be consistent with a recent conceptual proposal for state aid to schools made
by the Board of Regents. In that document, it was rec- ommended that Basic Operating Aid be calculated in a
manner that provides more aid to medium and low- wealth districts with demonstrated high-tax effort. The
recommendations also included the provision of sup- plementary funding for the purchase of additional
instructional materials required to implement new cur- riculum standards NYS Department of Education, 1996,
pp. 1–2.
Ultimately, these findings suggest that standards and other schooling policies need to be designed carefully
to ensure that they improve generic and course-specific educational attributes. The results, however, indicate that
oftentimes there are trade-offs involved in achieving a particular result. Moreover, while pursuing curriculum
359 N.A. Alexander Economics of Education Review 19 2000 351–361
Table 4 The relationship between imposition of at least one variance and generic educational outcomes, 198990 through 199495
a
Four-year college Portion of regents
Retention rate attendance
diplomas Award of any subject variance
0.004 0.005
20.0006 0.006
0.003 0.001
Portion advanced 0.386
0.477 0.013
0.148 0.078
0.031 Portion minority
20.046 20.080
20.002 0.065
0.034 0.014
Portion poor 0.002
20.003 0.009
0.022 0.011
0.004 Degree of centralization
20.037 20.034
20.003 0.031
0.016 0.006
Average size of English100 0.232
0.065 0.033
0.003 0.001
0.067 Average size of English100
2
20.004 20.002
20.0007 0.008
0.004 0.002
Average size of math100 20.12
0.117 0.010
0.194 0.102
0.041 Average size of math100
2
0.003 20.002
20.00005 0.005
0.003 0.001
Faculty with masters 20.015
0.006 0.001
0.024 0.012
0.005 Average faculty experience
0.013 0.006
0.003 0.006
0.003 0.001
Average faculty experience
2
20.0004 20.0002
20.00009 0.0002
0.00009 0.00003
High school enrollment per 100 0.005
0.001 20.0003
0.002 0.001
0.0004 High school enrollment per 100,000
2
20.0005 20.0001
0.0001 0.000
0.0000 0.000
Degree of preparednessMA 20.0003
0.0001 20.000005
0.0003 0.0002
0.00007 Degree of preparednessEng
20.00008 20.00004
0.00006 0.0002
0.0001 0.00004
Year 0.012
0.004 0.0017
0.007 0.0004
0.0002 Portion minority
× award of any variance
20.014 20.011
0.002 0.021
0.011 0.004
Portion poor ×
award of any variance 20.033
20.011 0.009
0.036 0.019
0.007 n DF
3470 652, 2818 3471 652, 2819
3474 2822, 652 R
2
0.916 0.902
0.808 F value
47.14 39.58
18.25 Prob.F
0.0001 0.0001
0.0001
a
Key: : significant at a
= 0.1; : significant at
a =
0.05; : significant at a
= 0.01. Standard errors are in parentheses.
standards policies appears to improve overall student output, it does not seem to address equity concerns quite
as well. Finally, the results of this study imply that there is a role for standards in the educational arena; state pol-
icy-makers need to decide the nature of that role. Below are three recommendations to consider.
1. Foster partnerships between secondary schools and tertiary institutions. This is suggested by the
