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A peer-reviewed scholarly
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Arizona State University
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Volume 11 Number 41 November 11, 2003 ISSN 1068-2341
The Effects of Full and Alternative Day Block Scheduling on
Language Arts and Science Achievement in a Junior High
School
Chance W. Lewis
R. Brian Cobb
Marc Winokur
Colorado State University
Nancy Leech
University of Colorado--Denver
Michael Viney
Wendy White
Poudre School District
Citation: Lewis, C. W., Cobb, R.B., Winokur, M., Leech, N., Viney, M. & White, W. (2003,
November 11). The effects of full and alternative day block scheduling on language arts and
science achievement in a junior high school. Education Policy Analysis Archives, 11(41). Retrieved
[Date] from http://epaa.asu.edu/epaa/v11n41/.
Abstract
The effects of a full (4 X 4) block scheduling program and an
alternate day (AB) block scheduling program in a junior high
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school were under investigation in this study through the use of
an ex post facto, matched sampling design. Measures
investigated were standardized achievement tests in science and
language arts. Both forms of block scheduling had been in place
for several years, and one teacher in science and one teacher in
language arts had taught students under both forms of
scheduling. Because the sampling designs and analyses were
different for the science and the language arts areas, two studies
are reported here—each examining the effects of 4 x 4, AB, and
traditional scheduling with attribute variables of gender and
student skill levels in each analysis. Results consistently show
students in both forms of block scheduling outperforming students
in traditional scheduling, and that AB block scheduling has the
largest positive impact on low-achieving students.
Defined as 90 – 120 minute class periods versus the traditional 45 – 55 minute
class period, block scheduling is one of the fastest growing educational reform
initiatives in secondary public education during the last two decades. Although
block scheduling has been a viable scheduling choice for many schools for over
forty years, it was not until the late 1980s that block scheduling became more
widespread throughout secondary schools in the United States. The growth in
block scheduling was a reaction to the notion that “close, personal relationships
among students and teachers had become less likely in traditional
environments as student numbers and student-teacher ratios increased”
(Nichols, 2000, p. 135). As of 1995, Canady and Rettig estimated that 50% of
American high schools had implemented some form of block scheduling, with
some states (e.g., North Carolina, Virginia) having much higher rates.
In the literature, block scheduling first appeared as modular scheduling, flexible
scheduling, or modular flexible scheduling (Stewart & Shank, 1971; Wood,
1970). Accordingly, block scheduling can be implemented in many different
ways with numerous modifications, often called “hybrids” in current literature.
Whether called an intensive block, 4 x 4 block, AB plan, or modified block—all
types of block scheduling have the commonality of increasing the time available
for instruction by extending classes beyond the traditional 50-minute class
(Weller & McLeskey, 2000).
Full Block (4 x 4) Semester Plan
The most popular method of block scheduling is the 4 x 4 semester plan, also
known as “Accelerated Schedule” or “Copernican.” In a 4 x 4 semester plan,
students attend the same four 90-minute classes every day of the week. By
attending each class every day, a student can complete four yearlong
equivalent courses in one semester, although the amount of time spent in the
course may be slightly less than in traditional scheduling (Queen, Algozzine, &
Eddy, 1997). The plan offers teachers a manageable timetable, as they teach
three classes with a daily planning period rather than five or six classes with a
planning period every other day (Edwards, 1995).
Many researchers have explored student, teacher, and administrator
perceptions of the 4 x 4 semester plan. Specifically, researchers have offered
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findings on classroom climate, instructional approaches, student/teacher
relationships, and overall satisfaction with block scheduling. As for perceptions
regarding the overall effectiveness of the 4 x 4 semester plan, parents have
consistently perceived improvement in the academic and social outcomes of
students participating in a block scheduling format (Eineder & Bishop, 1997;
Thomas & O’Connell, 1997a). As for teachers, Edwards (1995) found that after
one semester with a 4 x 4 schedule, they reported significant improvements in
teaching effectiveness. Staunton (1997) found that teachers with five or more
years of teaching in the 4 x 4 semester plan had significantly higher perceived
ratings of assessment techniques than did teachers in a traditional scheduling
environment. In a survey of four 4 x 4 block scheduling programs, Wilson and
Stokes (2000) found that, overall and over time, students perceived block
scheduling to be an effective approach, especially if they thought that teachers
used a greater variety of teaching strategies in class. Thomas and O’Connell
(1997b) found that students felt 4 x4 block classes offered fewer chances to
cheat and increased fairness in grading. Additionally, Edwards (1995) found
that a majority of students found it easier to focus on assignments and
understand the lessons better.
As for class size and classroom climate, two recent studies have found that
teachers perceived an increase in class size with 4 x 4 semester plan
scheduling (Limback & Jewell, 1998; Moore, Kirby, & Becton, 1997). However,
Wilson and Stokes (2000) found that students perceived the 4 x 4 semester
plan to offer a better instructional environment than in traditional scheduling
(e.g., teachers get to know them better, greater variety of instruction). In
addition, teachers perceived student/teacher relations to be better with 4 x 4
semester plan as there was more time for concentrated interactions (Eineder &
Bishop, 1997; Skrobarcek et al., 1997; Thomas & O’Connell, 1997b). O’ Neill
(1995) also argued that discipline problems have dropped at many of the
schools using block schedules because of this enhanced climate. These
findings suggest that the 4 x 4 semester plan format may increase the number
of students per class while creating a more productive learning environment.
The 4 x 4 semester plan is designed to create a new and different teaching and
learning experience for students and teachers. Staunton (1997) found that
teachers with more years of experience were significantly more satisfied with
instruction in 4 x 4 semester plan scheduling than in traditional scheduling.
However, Baker and Bowman (2000) found that teachers with less experience
were more likely to view block scheduling positively than were more
experienced teachers, as they appeared more willing to make the necessary
instructional changes. Using direct observations and in-depth interviews,
Queen, Algozzine, and Eddy (1997), found that teachers appreciated the
flexibility in classroom instruction, longer planning periods, greater course
offerings, and more time for in-depth study that block scheduling provided.
Alternate Day Block (AB) Plan
The Alternate Day Plan for block scheduling is also known as AB, Odd/Even,
and Day 1/Day 2 respectively. With AB scheduling, students take three or four
90-120 minute classes on alternating days for an entire school year. Many
school districts have found this mode of block scheduling conducive to school
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environments versus the 4 x 4 block schedule and the traditional 45-55 minute
class schedule.
The research literature much more sparse on AB scheduling. However,
Buchman, King, and Ryan (1995) found that both scheduling formats produced
very positive perceptions regarding the impact of AB block scheduling on safety,
success, involvement, commitment, interpersonal competency, and satisfaction.
According to Payne and Jordan’s (1996) study on the instructional impact of AB
block scheduling, “teachers reported that they enjoyed having more time to give
students individual assistance; opportunities to get to know the students
personally; time for more creative and meaningful student work; and the ability
to structure a full lesson” (p. 18). Thus, these advantages of an 85-minute block
period led to a less stressful and more flexible classroom climate (Payne &
Jordan, 1996; Weller & McLeskey, 2000). As a result, supportive teachers
working under this type of block scheduling develop curricula focused on
cooperative learning exercises to take advantage of the longer blocks of time
(Weller & McLeskey, 2000). Payne and Jordan (1996) also found that teachers
were positive about the way classes were scheduled, staff development, and
planning time afforded by an AB schedule.
As for the impact on learning Payne and Jordan (1996) did not find significant
differences in students’ perceptions regarding the efficacy of the AB scheduling
plan as compared with traditional scheduling. On the downside, Payne and
Jordan (1996) found that teachers reported needing more resources for varying
instruction and more time for planning. Shortt and Thayer (1995) found that
teachers believed that students needed instruction in a subject every day to
maximize the learning process.
4 x 4 Semester Plan and AB Plan Compared
As many school districts look to take on some form of block scheduling, it is
necessary to look at literature for analysis of which block scheduling option
seems most favorable by students, teachers, and administrators. The majority
of the literature on these two forms of block scheduling has focused on the
following characteristics: student grades, class size, classroom climate, time
issues, instruction, and dropout and attendance rates.
Pisapia and Westfall (1997a; 1997b) found that teachers in the 4 x 4 semester
plan were more satisfied with students’ grades than were teachers in AB
schedule. However Hamdy and Urich (1998) explored teachers’ perceptions of
class size and classroom climate in both block scheduling formats compared
with traditional scheduling and found teachers did not think class size was
reduced with block schedules nor was classroom climate perceived more
favorably with either block schedule formats.
The way class time is used has also been an important factor in implementing
either 4 x 4 semester plan or AB block plans. Teachers often perceived a
greater need to change the pace and type of instruction (e.g., group learning)
with both the 4 x 4 semester plan and AB plans (Pisapia & Westfall, 1997b;
Swope, Fritz, & Goins, 1998).
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Research has also shown mixed findings in attendance and dropout rates for
students in both the 4 x 4 semester and AB plans. Pisapia & Westfall (1997a,
1997c) found that teachers perceive better attendance with the 4 x 4 semester
plan than with the AB plan. Conversely, other studies show no reduction in
dropouts or increased attendance with either the 4 x 4 semester or AB plans as
compared to traditional scheduling (e.g., Skrobarcek et al., 1997).
As for overall satisfaction, students in the 4 x 4 semester plan were found to be
more satisfied with the number of courses available for them in which to enroll
than both students in AB plan and in traditional scheduling (Pisapia & Westfall,
1997b). According to Lapkin, Harley, and Hart (1997), three-quarters of
students believed that the longer periods in both the 4 x 4 semester and AB
plans made it easier to speak French and to interact with the teacher. However,
a similar majority of students reported being more tired, less attentive, and more
bored in the longer French periods as compared with the shorter classes in
traditional scheduling plans.
Conclusion
It is difficult to produce any consistent conclusions from the recently published
literature on block scheduling as most researchers disagree about the positive
and negative effects of 4 x 4 semester plan and AB scheduling. However, there
are certain advantages and disadvantages to block scheduling that have been
identified through both quantitative and qualitative research on the subject.
Advantages
Overall, the research provides modest support for the presumed advantages of
block scheduling (Payne & Jordan, 1996). According to Lapkin et al. (1997),
block scheduling may promote higher levels of reading and writing proficiency.
Students participating in block scheduling plans are also appear to show greater
gains in grade point average as compared with traditional instructional formats
(Edwards, 1995). Nichols (2000) concluded that longer class periods
encourage teachers to develop more effective behavioral management
techniques rather than relying on administrative disciplinarians. In addition,
Nichols (2000) argued that the decrease in quantitative minutes of classroom
instruction is more than offset in the quality of student-teacher interaction in a
block scheduling format.
Disadvantages
Adopting a block schedule has its disadvantages, especially around designing
instruction appropriate for the longer classes (O’Neill, 1995). Additionally,
although time is extended on a daily basis for all types of block scheduling, the
actual class time may actually drop around ten percent (Queen et al., 1997). As
a result, some teachers will inevitably cover less material because of the
reduced number of total instructional minutes (O’Neill, 1995). Advocates of
Advancement Placement programs have also expressed concerns about the
preparation of students who take fall class and spring exams (O’Neill, 1995), a
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concern associated with 4 x 4 block scheduling in particular. In addition to
concerns about the scheduling of advanced placement courses, the sequencing
of foreign language and music are also challenges to the block scheduling
format (Shortt & Thayer, 1995).
Furthermore, there are concerns about the effectiveness of block scheduling for
all student populations. Specifically, transfer students and lower-achieving
students may not garner the same benefits as the other students because of
the faster pace and tighter structure of block scheduling (Nichols, 2000; Shortt &
Thayer, 1995). These students may actually experience lower levels of
achievement and success “in schools where block scheduling was poorly
planned for and quickly implemented” (Nichols, 2000, p. 145). Students may
also have difficulty in keeping track of their books, due dates for assignments,
and when quizzes and exams are scheduled (Weller & McLeskey, 2000). In
addition, “absences are magnified within the block schedule because of the
time between class periods and because there is limited time within the
schedule for students to contact teachers to see what work they have missed”
(Weller & McLeskey, 2000, p. 215). Thus, “students who miss class or do not
keep up with their studies are more likely to fail” (Edwards, 1995, p. 27).
Finally, Shortt and Thayer (1995) concluded that academic pacing is a concern
when switching to block scheduling, as teachers may struggle with meeting
instructional objectives and curriculum standards. According to Queen et al.
(1997), other negative aspects of block scheduling include too much
independent study, limited number of electives, overemphasis on lecture, and
teacher fatigue toward the middle of the second semester.
Research Questions
Because of the equivocation in the research literature on achievement effects of
block scheduling a priori research hypotheses were not posed. Instead research
questions were developed around the major main effects and interactions of the
instructional format variable (4 x 4, AB, and traditional schedules) attribute
variables (gender and achievement level) and outcome variables (science
process, science content, and language arts).
What is the effect on science content, science process, and language arts
achievement of learning that content in 4 x 4 block scheduling, AB block
scheduling, or traditional scheduling?
How do those effects vary depending on student gender and prior student
achievement levels?
Although these research questions are posed across all outcome and
independent variables, the language arts study and the science studies were
sufficiently different in sampling designs and analyses to merit separate
methodological and results sections.
Language Arts Study
Method
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Population, Sample, and Sampling Design
The theoretical population for this ex post facto study is students who attend
either junior high school or middle school in moderately sized cities in the
mountain west. The actual sample for this study was 111 students who
attended two different junior high schools in a city of approximately 125,000 in
Colorado. In an attempt to overcome some of the weaknesses in causal
inferences associated with ex post facto designs, a two-stage sampling design
was used and is described below.
School selection stage of the sampling design. Block Schedule School (BSS)
was the school of interest in this study primarily because the school had
implemented both 4 x 4 block scheduling and AB block scheduling
simultaneously for several years, representing a relatively unique opportunity to
examine differential effects of both forms of block scheduling while controlling
for school effects. Additionally, the same language arts teacher taught in both
the 4 x 4 and AB block scheduling modalities, and taught the same curriculum
across both modalities, adding important internal controls for both curriculum
and instruction across both conditions. Finally, this teacher taught both 4 x 4
and AB block scheduling modalities in the same academic years of this study
(i.e. 4 x 4 classes in the morning; AB classes in the afternoon) thus helping to
control for differential historical threats across these two conditions.
To generate a comparison sample of students from a traditionally-scheduled
school, a comparable school—Traditional Schedule School (TSS) was selected.
Although TSS was considerably smaller in total number of students (450
students versus 750 for BSS), the similarities of these two schools on other
important features were quite close. Both had a relatively mature teaching force;
both were located on the same sector of the city, that is very heterogeneous in
the types of families that live there; and both had very similar 2001 reading
(72% - BSS versus 69% - TSS); writing (48% versus 41% respectively); and
mathematics (51% versus 52% respectively) proficiency ratings on the state’s
high stakes examinations. TSS also averaged approximately 4 students less
across all grade levels in student/teacher ratio than BSS.
Student selection stage of the sampling design. The sample of students from
BSS in the 4 x 4 block scheduling and AB block scheduling groups were those
students in the 1998-1999 and 1999-2000 academic years who were taught
their language arts courses by the instructor associated with this study. These
students numbered 131 students in 4 x 4 block scheduling and 134 in AB
scheduling groups. From these initial numbers, data were collected from the
school district database on these students’ 6th grade language arts Iowa Test of
Basic Skills (ITBS) test scores, converted into Normal Curve Equivalents
(NCE’s). Due to missing data on these ITBS scores, these initial sample sizes
were reduced to 102 and 95 language arts students in 4 x 4 and AB block
scheduling respectively.
A random sample of approximately 60 students from each of the two years was
then drawn from TSS and 6th grade language arts ITBS test scores, converted
into NCE’s were collected on each of these students. Again, missing ITBS test
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score data reduced these TSS samples down to 97 students. A Pearson
correlation was then conducted for these 294 correlating these ITBS scores with
the outcome variable of interest – the students’ 9th grade language arts RIT
score (described below). The correlation was .75, which suggested the 6th
grade ITBS score was an excellent matching variable on which to equate
individual students.
The final student sampling process then, involved matching individual students
in each of the three instructional format groups by gender and by 6th grade
ITBS scores. To do this matching process the students were sorted by group,
and then by gender and ITBS scores in language arts. The process was then
followed wherein, for example, a male student who was in the 4 x 4 block
scheduling group and who might have had a language arts 6th grade ITBS
score of 33.2 was matched with a male from each of the other two instructional
groups who also had a language arts ITBS score of 33.2. This matching
process was followed producing a 100% match on gender, and a better than
90% exact match on ITBS scores. In those cases where there was not a perfect
3-group match on ITBS scores, at least two of the three scores were an
identical match, and the off-matched score was never more that +/- 2 NCE’s. In
order to maintain this high level of matching, however, a significant attrition
occurred in each database. The final language arts sample ended up having 37
complete cases with the dataset organized for a mixed ANOVA analysis.
Interventions
Students in the BSS science and language arts classes were enrolled in either
a 4 x 4 block format or an AB block format. Students in the AB block format met
every other day throughout the entire school year. Students in the 4 x 4 block
format met every day of the week for a single semester. Those students in the 4
x 4 block format who enrolled in the fall semester took the outcome
achievement tests in language arts and science (see description below) in the
first week of December. Students in the 4 x 4 block format who enrolled in the
spring semester and all students in the AB block format took the outcome tests
in second week of April. The curriculum, instructional formats, laboratory
activities, projects, and other in-class activities were identical for students in
both block formats and within each of the science and language arts curricula.
Students in the TSS received instruction in science and language arts for the
entire academic year in 50 minute classes every day of the week.
Variables
The dependent variable for this study was the students’ 9th grade language arts
RIT score on the criterion-referenced levels test which was administered in the
late fall and late spring of each year of this study. The levels test (Northwest
Evaluation Association, 1997) is a well-established achievement test battery
that allows school districts to measure growth in student learning from one year
to the next
The within subjects variable was the instructional format used to teach language
arts – with three levels – 4 x 4 block scheduling, AB block scheduling, and
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traditional scheduling. The between groups variables for this study were the
students’ gender, and the students achievement levels in language arts as they
entered junior high school. To create this achievement level variable, the
students’ 6th grade ITBS scores were sorted above and below the median level
of this ITBS score creating a two-level variable.
Analysis
The data for this study were analyzed using a 3 x 2 x 2 mixed ANOVA with
repeated measures on the first factor (instructional format). Gliner & Morgan
(2000) asserted that the appropriate analytic technique for matched student
sampling designs is to treat the grouping variable as a within subjects variable
and use repeated measures analyses as the statistic. A total of 37 complete
cases were used in this analysis.
Results
Table 1 presents descriptive information about the samples of students who
were included in the language arts analysis. Levene’s test for equality of
variances proved non-significant for all three instructional formats and
Mauchly’s test for sphericity also proved non-significant (X
2
= 0.129, df = 2, p. =
.938).
Table 2 presents the ANOVA source table for this language arts analysis. As
can be seen, achievement in language arts at the 9th grade level varied
significantly across instructional format, F (2, 66) = 4.89, p = .01. The strongly
significant differences on the main effect of achievement level suggest
appropriate separation between the two achievement level groups; similarly, the
negligible main effect on gender suggests relative equality of these two groups.
Statistically significant effects were also found on the interaction between
instructional format and gender, F (2, 66) = 3.16, p < .05, and between
instructional format and achievement level F (2, 66) = 8.06, p < .01. Post hoc
analyses using a Tukey HSD are presented in Table 3 for all statistically
significant pairwise comparisons (excluding gender and achievement level main
Table 1. Means and Standard Deviations for 9th Grade Language Arts
Achievement Broken out by Instructional Format, Gender, and
Achievement Level
Males Females
Instructional Format M n SD M n SD
Low Achieving Group
4 x 4 Block Scheduling 222.50 8 4.44 218.50 8 8.18
AB Block Scheduling 225.38 8 4.14 226.50 8 7.09
Traditional Scheduling 212.00 8 7.87 220.13 8 7.49
High Achieving Group
4 x 4 Block Scheduling 230.78 9 7.31 227.42 12 5.76
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AB Block Scheduling 230.00 9 7.26 230.83 12 7.71
Traditional Scheduling 232.56 9 7.33 231.17 12 5.69
effects, and the instructional format by gender interaction – see Figure 1 and
corresponding narrative for explanation) along with effect sizes.
As can be seen in Table 3 and Figure 1, AB block scheduling generated a small
to moderate main effect over traditional scheduling (Cohen, 1988); 4 x 4 block
scheduling did not. Much more interesting and powerful, however, were the
effects that both forms of block scheduling seemed to hold for those students
who entered junior high school in the bottom half
Table 2. Analysis of Variance for 9th Grade Language Arts Achievement as
a Function of Instructional Format, Achievement Level, and Gender
Source df SS MS F p
Instructional Format 2 385.60 179.30 4.89 .01
Achievement Level 1 2501.30 2501.30 38.58 .00
Gender 1 1.33 1.33 0.02 .89
Instructional Format x Gender 2 231.31 115.65 3.16 .045
Instructional Format x Achievement Level 2 590.85 295.42 8.06 .001
Achievement Level x Gender 1 63.02 63.02 0.97 .33
Instructional Format x Achievement Level x Gender 2 141.75 70.87 1.93 .15
Error (Instructional Format 66 2419.22 36.66
Table 3. Statistically Significant Pairwise Comparisons and Effect Sizes
for the Language Arts Analyses
Pairwise Comparisons M diff p
d
a
AB Block Schedule versus Traditional Schedule 3.54 .006 .40
Low Achievers in 4 x 4 Block Schedule versus Low Achievers in Traditional
Schedule
3.90 .025 .51
Low Achievers in AB Block Schedule versus Low Achievers in Traditional
Schedule
7.09 .000 1.39
a
calculated using weighted, pooled standard deviation formula
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Figure 1. Mean language arts RIT Scores for students in 4 x 4, AB, and
traditional schedules broken out by gender and achievement levels.
of language arts achievement distribution. Here, both forms of block scheduling
had significant advantages over traditional scheduling, with 4 x 4 block
scheduling generating a moderately strong effect size, and AB block scheduling
demonstrating a very large effect size – nearly three times that of 4 x 4 block
scheduling. Looking at Figure 1, it appears that the significant format by gender
interaction was due in large part to the disparity of scores in the
traditionally-scheduled school and hence does not appear to be a genuine
effect worth reporting.
Science Content and Process Study
Method
Population, Sample, and Sampling Design
The theoretical population for this ex post facto study is identical to the
language arts study above. The actual sample for both of these science
analyses was 340 students. These students were drawn from the same two
schools as the language arts study; however, the lack of a well-suited matching
variable changed the sampling design and subsequent analyses. Hence the
school selection stage of the two stage sampling design described in the
language arts study was exactly the same for this science content and process
study. For example, the same science teacher taught in both the 4 x 4 and AB
block scheduling modalities, and taught the same curriculum across both
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modalities and in the same academic years of this study.
Student selection stage of the sampling design. The sample of students from
BSS in the 4 x 4 block scheduling and AB block scheduling groups were those
students in the 1998-1999 and 1999-2000 academic years that were taught
their science courses by the instructor associated with this study. These
students numbered 114 students in 4 x 4 block scheduling and 102 in AB
scheduling groups. Similar to the language arts study, data were collected from
the school district database on these students’ 6th grade mathematics ITBS test
scores, converted into Normal Curve Equivalents (NCE’s). Due to missing data
on these ITBS scores, these initial sample sizes were reduced to 88 and 83
students in 4 x 4 and AB block scheduling respectively.
A random sample of approximately 60 students from each of the two years was
then drawn from TSS and 6th grade mathematics ITBS test scores, converted
into Normal Curve Equivalents (NCE’s) were collected on each of these
students. Again, missing ITBS test score data reduced these TSS samples
down to a total of 97 students across the two years of the study. Then, two
Pearson correlations were conducted for these 264 students correlating these
ITBS scores with the outcome variables of interest – the students’ 9th grade
science process and content RIT scores. These correlations were .39 for the
science content/ITBS math correlation and .41 for the science process/ITBS
math correlation, which, although both statistically significant at the p < .01
level, did not correlate well enough to justify their use as a criterion for a
matched sampling design. Hence, this study was conducted and analyzed as a
factorial between groups design.
Variables
The dependent variables for this sub-study were the students’ 9th grade
science content and process RIT scores on the criterion-referenced levels test
which was administered in the late spring of each year of this study. The three
between groups variables for this study were: (a) the grouping variable, with
three levels (4 x 4 block scheduling, AB block scheduling, and traditional
scheduling); (b) students’ gender; and (c) the students achievement levels in
6th grade mathematics as they entered junior high school, blocked into two
groups—those at the median and above, and those below the median.
Analyses
A preliminary one-way ANOVA was conducted using the mathematics ITBS
NCE scores as the dependent variable and the instructional formats as the
grouping variable. This analysis tested the viability of the assumption that the
matching process using math ITBS scores served to equate, in some measure,
the students in the three groups. This ANOVA proved non-significant F (2, 267)
= .149, p = .862, lending some credibility to the assumption of equality of
groups.
The outcome data for this sub-study were analyzed using two 3 x 2 x 2 between
groups ANOVA’s. The decision was made not to use a single MANOVA due to
the high correlation (r = .70) between the two dependent variables (science
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process and science content). Cole, Maxwell, Arvey, & Salas (1994) recently
recommended using separate univariate ANOVA’s when the expected effect
sizes for both analyses are reasonably large and consistently in the same
direction, and when there is a high correlation between the two dependent
variables.
Science content. Table 4 presents descriptive information about the science
content sample. Levene’s statistic, testing the assumption of equality of
variances across the various
Table 4. Means and Standard Deviations for 9th Grade Science Content
Achievement Broken out by Instructional Format, Gender, and
Achievement Level
Males Females
Instructional Format M n SD M n SD
Low Achieving Group
4 x 4 Block Scheduling 218.74 19 15.11 218.59 22 10.81
AB Block Scheduling 214.76 17 13.95 217.29 21 6.07
Traditional Scheduling 210.83 24 9.30 207.85 20 6.17
High Achieving Group
4 x 4 Block Scheduling 223.30 30 11.50 220.94 17 9.59
AB Block Scheduling 221.33 15 8.15 222.00 30 9.62
Traditional Scheduling 222.54 26 8.36 219.68 28 8.41
levels of the three independent variables proved statistically significant, F (11,
257) = 2.04, p < .03. Hence, for all post hoc tests the Games-Howell test was
used which Field (2000, p. 276) recommended to be used when samples sizes
are relatively small and unequal, and the assumption of homogeneity of
variance has been violated.
Table 5 presents the ANOVA source table for this science content analysis. As
can be seen, achievement in science content at the 9th grade level varied
significantly by instructional format, F (2, 257) = 6.40, p = .002. Statistically
significant effects were also found on the interaction between instructional
format and achievement level, F (2, 257) = 4.22, p < .016. Of course, the
statistically significant main effect for achievement level was not of interest in
this
Table 5. Analysis of Variance for 9th Grade Science Content Achievement
as a Function of Instructional Format, Achievement Level, and Gender
Source df SS MS F p
Instructional Format 2 1279.65 639.82 6.40 .002
Achievement Level 1 3095.66 3095.66 30.96 .000
Gender 1 47.34 47.34 0.47 .49
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Instructional Format x Gender 2 220.73 110.37 1.10 .33
Instructional Format x Achievement Level 2 844.69 422.35 4.22 .016
Achievement Level x Gender 1 27.65 27.65 0.28 .60
Instructional Format x Achievement Level x Gender 2 18.01 9.01 0.09 .91
Error (Instructional Format) 257 25693.37 99.99
analysis; no significant main or interaction effects were found on the gender
variable. Post hoc analyses using the Games-Howell statistic along with effect
size estimates are presented in Table 6 for all statistically significant pairwise
comparisons; Figure 2 graphically displays these comparisons.
Table 6. Statistically Significant Pairwise Comparisons and Effect Sizes
for Science Content Analyses
Pairwise Comparisons M diff p
d
a
4 x 4 Block Schedule versus Traditional Schedule 4.82 .009 .44
Low Achievers in 4 x 4 Block Schedule versus Low Achievers in Traditional
Schedule
9.18 .003 .89
Low Achievers in AB Block Schedule versus Low Achievers in Traditional
Schedule
6.68 .022 1.01
a
calculated using weighted, pooled standard deviation formula
As can be seen in Table 6 and Figure 2, 4 x 4 block scheduling generated a
moderately strong main effect over traditional scheduling; AB block scheduling
did not. This finding is a reversal of the block scheduling main effect found in
the language arts analysis above, but still suggests an advantage for block
scheduling formats over traditional scheduling. As with the language arts
analysis, the more interesting and powerful effects were found in favor of both
forms of block scheduling for those students who entered junior high school in
the bottom half of mathematics achievement distribution. Here, both forms of
block scheduling had significant advantages over traditional scheduling, with
both forms of scheduling demonstrating large effect sizes over traditional
scheduling. Figure 2 displays this pattern of findings. Of equal interest,
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Figure 2. Mean science content RIT scores for students in 4 x 4, AB, and
traditional schedules broken out by gender and achievement levels.
although not reported below in Table 6 is that the only subgroup that the high
achievers in traditional scheduling format outperformed with statistically
significant differences was the traditionally scheduled low achievers. Thus it
appears that block scheduling may be capable of
bringing low achieving students to the levels of their high achieving counterparts
who receive science instruction in traditional scheduling formats.
Science process. Table 7 presents descriptive information about the science
process sample. Levene’s statistic, testing the assumption of equality of
variances across the various levels of the three independent variables proved
statistically significant, F (11, 255) = 2.68, p < .003. Again, then, all post hoc
tests used the Games-Howell statistic.
Table 7. Means and Standard Deviations for 9th Grade Science Process
Achievement Broken out by Instructional Format, Gender, and
Achievement Level
Males Females
Instructional Format M n SD M n SD
Low Achieving Group
4 x 4 Block Scheduling 220.63 19 9.62 222.09 22 12.56
AB Block Scheduling 213.35 17 17.69 219.86 21 10.86
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Traditional Scheduling 210.54 24 11.75 206.15 20 7.80
High Achieving Group
4 x 4 Block Scheduling 223.43 >30 13.13 220.00 17 8.78
AB Block Scheduling 220.40 15 7.89 224.77 31 10.55
Traditional Scheduling 223.35 26 7.58 222.82 28 7.41
Table 8 presents the ANOVA source table for the science process analysis. As
can be seen, achievement in science process at the 9th grade level varied
significantly by instructional format, F (2, 258) = 6.77, p = .001. Statistically
significant effects were also found on the interaction between instructional
format and gender, F (2, 258) = 3.10, p = .047, and on the interaction between
instructional format and achievement level, F (2, 258) = 10.08, p < .000. Again,
the statistically significant main effect for achievement level was not of interest
in this
Table 8. Analysis of Variance for 9th Grade Science Process Achievement
as a Function of Instructional Format, Achievement Level, and Gender
Source df SS MS F p
Instructional Format 2 1598.50 799.25 6.77 .001
Achievement Level 1 3164.46 3164.46 26.79 .000
Gender 1 28.33 28.33 0.24 .63
Instructional Format x Gender 2 732.08 366.04 3.10 .047
Instructional Format x Achievement Level 2 2381.28 1190.64 10.08 .000
Achievement Level x Gender 1 17.74 17.74 0.15 .70
Instructional Format x Achievement Level x Gender 2 227.99 113.99 0.97 .38
Error (Instructional Format) 258 30477.58 118.13
analysis. Post hoc analyses using the Games-Howell statistic along with effect
size estimates are presented in Table 9 for all statistically significant pairwise
comparisons; Figure 3 graphically displays these comparisons.
As can be seen in Table 9 and Figure 3, 4 x 4 block scheduling generated a
moderately strong main effect over traditional scheduling, almost identical to the
effect seen in the science content analysis in Table 6. As with the science
content analysis, AB block scheduling did not produce a statistically significant
advantage over traditional scheduling. As with the science content effect size
analysis, the interactions between instructional format and entering
Table 9. Statistically Significant Pairwise Comparisons and Effect Sizes
for Science Content Analyses
Pairwise Comparisons Mdiff p
d
a
4 x 4 Block Schedule versus Traditional Schedule 5.28 .006 .46
Low Achievers in AB Block Schedule versus Low Achievers in Traditional
Schedule
12.87 .000 1.20
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Females in AB Block Schedule versus Females in Traditional Schedule 8.40 .044 .69
Low Achievers in 4 x 4 Block Schedule versus Low Achievers in Traditional
Schedule
7.56 .015 .69
a
calculated using weighted, pooled standard deviation formula
achievement level strongly favored both block scheduling formats over
traditional scheduling although the relative strength of the particular block
format was reversed in this analysis. The gender x instructional format
interaction was the first time a gender effect appeared in any of these analyses.
Looking at the graphs in Figures 1 and 2 compared with Figure 3, this effect
would seem to be related to the relatively wide dispersion of mean scores by
gender for the AB format in Figure 3 compared with this dispersion in Figures 1
and 2. Given the lack of consistency in this gender x instructional format
interaction, however, it is questionable how much confidence can be placed in
the veracity of this interaction. Again, as with the science content analysis, the
only subgroup that the high achievers in traditional scheduling format
outperformed with statistically significant differences was the traditionally
scheduled low achievers.
Figure 3. Mean science process RIT scores for students in 4 x 4, AB, and
traditional schedules broken out by gender and achievement levels.
Discussion
What is to be made of these findings, especially given Veal and Schreiber’s
(1999) recent statement “The literature is consistent on the inconsistency of
18 of 25
achievement of students within the block schedule (p. 3)” in their review of
literature? It probably makes the most sense to start by considering the
non-achievement literature on block scheduling as well. Here, the findings are
much more consistent (although not uniformly so), and they to tend favor both
forms of block scheduling over traditional scheduling on such things a school
climate (i.e. Bickel, 1999), student satisfaction with school (Lapkin et. al, 1997;
Knight, De Leon, & Smith, 1999)—except students in AP classes (Knight et al,
1999), and teacher, parent, and counselor satisfaction with school (Edwards,
1999; Wilson & Stokes, 1999; Deuel, 1999). Hence, if the main and interaction
effects of block scheduling on student achievement can be “held harmless”
versus traditional scheduling then the relatively consistent results on these kinds
of “softer” measures above might tip the scales in favor of block scheduling.
Thus, if the “standard” for consistent findings on student achievement of block
scheduling is that it does not produce worse outcomes rather than that it does
produce positive outcomes, then the consistency picture does clear up
somewhat. Here, Veal and Schreiber (1999) and their follow up study
(Schreiber, Veal, Flinders, & Churchill, 2001) found no adverse effects on
mathematics, reading, and language arts of attending block scheduled high
school classes. Their findings, then, are in conflict with this study on language
arts, but at least are consistent on a “no adverse effect” criterion. These
researchers also looked only at 4 x 4 and traditional scheduling (and a 4 x
4/traditional hybrid) and did not look at effects of AB block scheduling. Bickel
(1999) found no differences between block scheduling and traditional
scheduling on mathematics achievement. Wallinger (1998) found no differences
on foreign language achievement although Lapkin et al, (1997) found
differences in favor of block scheduling on foreign language achievement.
Finally, Edwards (1999) found very cautious positive effects of block scheduling
on science achievement.
Thus it would seem that the sum of this prior research (our own prior research
notwithstanding – see Cobb, Abate, & Baker, 1999) and the findings of this
current study would tend to support the use of block scheduling. However, there
are a number of limitations both with this current study and with the empirical
literature set in general that make this judgment one to be viewed with caution.
First, most of the studies cited that looked at student achievement were at best
causal-comparative in design, and in some cases, purely correlational. Many of
these studies did not even exercise the attempt at controls that this present
study did – that is equating schools and students in them. Seldom was there a
reporting of the procedures of the block scheduling intervention (except of
course, that the length of the class period was longer) and hence there are a
whole host of additional variables about the integrity of the block scheduling
intervention that are unreported and uncontrolled in these causal-comparative
research studies and that bring unmeasured effects into the research results.
Also, with multi-school studies, the variable of instructional quality of the
teachers independent of the scheduling format, adds a significant unmeasured
dimension to the research results.
These limitations notwithstanding, we believe we have findings worth adding to
the theoretical mix, and paradoxically, they are characterized by consistency.
Looking at the consistency in three graphs and in the magnitude of the
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corresponding effect size tables, we consistently found sizeable gains in favor
of block scheduling. These gains persevered across both the language arts and
science domains of achievement; and these gains were largest consistently in
favor of lower achieving students while consistently holding harmless upper
achieving students. These are the findings of one junior high school, however,
and need to be replicated with high quality quasi-experiments and ex post facto
studies in order to be generalized to other settings.
In future research efforts we have a number of observations and
recommendations that seem particularly germane with the escalating demands
for “scientific rigor” in educational research associated with current federal
education legislation. First, we recommend qualitative research—particularly
case studies, ethnographies, or grounded theory research—that explores
several very likely and important sources of variation in prior research results.
For example, differing instructional practices by teachers in blocked and
traditional scheduled classes are doubtless sources of error variance in
achievement results, especially in studies that use only one or a few schools
and teachers. Clearly, the context within which block scheduling and traditional
scheduling is delivered also has much to do with efficacy of achievement
results. Desimone (2002), for example, has recently affirmed in her review of
comprehensive school reform model literature Porter, Floden, Freeman,
Schmidt, & Schwille’s (1988) policy attributes theory about successful
implementation of whole school reform. Exploring how schools move to block
scheduling by focusing on the attributes of specificity, consistency, authority,
stability, and context, case study or grounded theory research can add
immense understandings as to how and why achievement results vary as they
do across implementation sites.
From the quantitative paradigm, we recommend that university and
school-based researchers aim as high as possible within the methodological
boundaries they attach to their studies. With group-based studies, we
recommend that research begin, if at all possible with schools that are planning
a move to block scheduling in order to move the design characteristics from ex
post facto to quasi-experimentation, with attention to the attendant
improvements to controls over threats to internal validity. Documentation of the
adoption processes and implementation activities will go a long way to remove
and explain sources of error variance that plague ex post facto designs and are
likely to be the source of the inconsistencies in earlier research.
Nonetheless, we recognize that the preponderance of future quantitative
research on block scheduling is likely to be causal-comparative. As such we
believe that with careful attention to internal validity features within this design,
credible research results can weigh into the discussion about block scheduling
such that evidence-based judgments can be made that draw, in part from these
kinds of research studies. First, more and more schools are going to hybridized
versions of either 4 x 4 or AB block scheduling, and these hybrids must be
documented and described. Second, we recommend that outcome measures
focus on math, science, and language arts—domains that are likely to be tested
more and more with the implementation of No Child Left Behind legislation.
These are the achievement domains of the first decade of the 21st century and
the “social validity” of this research will be enhanced by attention to these
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domains. Third, ex post facto studies absolutely must measure pre-block
scheduled achievement levels of students on measures that are highly
correlated with the outcome measures. Whether or not these pre-measures
result in matched sampling designs or ANCOVA statistical designs will be more
of a judgment call of the researchers, but these pre-measures must be included
in the research. Fourth, researchers have to measure the length of time
students attended block scheduled and traditional (comparison) schools and
eliminate students who were not in those school long enough (i.e. 1-2 years) to
demonstrate the effects of those schools’ scheduling formats. Finally
recommend longitudinal follow up of students, if possible to explore the
durability of block scheduling effects (see, for example, the Veal & Schreiber,
1999 and the Schreiber et. al, 2001 studies as an example). We can envision,
for example, a methodologically appealing line of research that looked at
students in middle/junior high school who were in block scheduled and
traditional formats and who then attended, differentially, block scheduled or
traditionally scheduled formats in high school.
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About the Authors
Chance W. Lewis is an Assistant Professor in the School of Education at
Colorado State University and a Research Associate at the Research and
Development Center for the Advancement of Student Learning.
Brian Cobb is a Professor in the School of Education at Colorado State
University and Co-Director of the Research and Development Center for the
Advancement of Student Learning.
Marc Winokur is a doctoral candidate in Educational Leadership at Colorado
State University and an Evaluation Fellow for the Center for Learning and
Teaching in the West at Colorado State University.
Nancy L. Leech is an Assistant Professor in the School of Education at the
University of Colorado at Denver.
Mike Viney is the Science Chair at Blevins Junior High School in Poudre
School District, Ft. Collins, CO and the Professional Development Science
Instructor for the Center for Learning and Teaching in the West at Colorado
State University.
Wendy White is a secondary Language Arts teacher and Language Arts
Department Chair at Blevins Junior High School in Poudre School District, Fort
Collins, Colorado.
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