CHAPTER I

INTRODUCTION

As the United States’ public school system fell in international rankings in comparison to other countries, it became more important to develop an effective educational system (Higgins, 2002; Wu, 2004). American educators face the monumental task of reinventing the public school system and creating a new design that would close the achievement gap between the high and low-performing students and improving United States’ ranking in international education while maintaining one of the shortest school years in the world (National Association of Elementary School Principals, 2008; Walberg, 2001). In an attempt to make schools more efficient and effective, many American schools did away with their traditional schedules and replaced them with some form of block schedule (Canady, Michael, & Rettig, 1996). Blocked scheduling may provide schools the additional time needed to improve school climate, maximize learning, improve discipline, increase time on task, increase student achievement and remain competitive internationally (Queen, 2000). The block scheduling design was expected to improve the performance of low achieving students such as the special education, English Language Learners (E.L.L.), migrant, economically disadvantaged, and gifted and talented students (Quint, 2006).In 1983, the National Commission on Excellence in Education and in 1994 the National Commission on Time and Learning reported the negative effects of the short school year in the United States. The student achievement gap between American students and students from other industrialized countries could be accounted for by the difference in number of instructional days in the school year and private tutorial services. In addition to a 50 day extended school year, almost fifty percent of Japanese students in the ninth grade attended juku, privately paid tutorial services (Barrett, 1990). In contrast, American students were expected to learn in 180 days a year what European students learn in 190 to 210 days, and Japanese students learn 240 days. In spite of the reports from decades past stipulating the concern, international surveys showed that American students made the least progress and had the shortest school year (Walberg, 2001). When compared to the Japanese school year, in a span of twelve American school years, Japanese students received 720 more instructional days or the equivalent of four additional years of instruction than American students. At the eighth grade level, student achievement is lower than many other countries in mathematics (Silver, 1998). According to the American Institute for Research (2003), “American school reform efforts should not be limited to strengthen mathematics instruction at the higher grade levels but should also encompass improving mathematics instruction at the early elementary levels grades” (p. 1). Compounding the problem of a short academic year is a short school day. While students attended classes for eight hours a day, only four to five hours a day were spent on core area classes; the rest of the time was spent on electives and exchanging classes. Additional time was lost on refocusing students, maintaining discipline, structuring classroom activities, and taking attendance (Northeast and Islands Regional Educational Laboratory, 1998).

Throughout the years, there has been no solid support for increasing days to the American school year. In 1959, 67% of Americans were opposed to increasing the number of days per year and 26% were in favor. In 1984, a year after the Nation at Risk Report, 50% of Americans were opposed to increasing the number of days per year and 44% were in favor. By 1989, 44% opposed increasing the school year, 48% said they were in favor, and 8% were undecided. Proponent of extending the school years has never obtained a clear support for a mandate (Barrett, 1990). Since Americans are unwilling or unable to add additional days to the school calendar or extend the school day, schools must develop creative ways to add instructional time to the school days. Block scheduling may provide the avenue to add instructional time without extending the school day or year. The block scheduling models presented in this study double the amount of instructional time allocated for middle school students in the area of mathematics by making small modifications in the school day, while still maintaining most of the traditional schedule. This model was based on the original idea of J. Lloyd Trump (Queen, 2000). By taking away five minutes from an eight period 55 minute schedule and adding ten minutes to the instructional day, a nine period schedule was created. The extra period gained was used to make a two period 90 to 100 minute math block schedule. The time gain may provide schools with the time allocation structure that may allow more in-depth teaching and learning to improve student performance (The Center for Education Reform, 1996).

The use of block scheduling was widespread in the United States (Canady & Rettig, 1995; Veal, 1999). About 50% of American schools use some form of block scheduling. In Texas, the use of block scheduling at the high school level boomed during the 1990s’ going from 4% in 1992 to 43% in 1999 (National Science Teachers Association, 1997; Rettig & Canady, 1999; Texas Education Agency, 1999).

Statement of the Problem

The biggest constraint that American schools face when trying to extend the school year to equal the same number of days as Japan and other industrialized nations is the cost (Aronson, Zimmerman, & Carlos, 1999). “Additional days and hours are expensive, and changing the school schedule affects not only students and teachers, but parents, employers, and a wide range of industries that are dependent on the traditional school day and year” (Silva, 2007b, p. 3). Compounding the problem was the belief that schools use time ineffectively and that adding days to the school year would not be cost effective because the impact on student learning would be minimal; and therefore schools should concentrate on the quality of instruction rather than quantity (Ellis, 1984: Silva, 2007). American schools must develop creative ways to maximize student learning and add instructional time to improve student performance without adding additional days to the school calendar, extending the school day, or increasing cost. Block scheduling may add instructional time to the school day, provide more time for in-depth instruction and address the students’ needs (Education World, Inc., 1997).

Purpose of the Study

The purpose of this study was to examine the impact of split block scheduling on student academic achievement as measures by TAKS benchmark scores to determine which type of block schedule has the greatest impact on student academic achievement. This study examined the results of a middle school in South Texas that was experimenting with block scheduling. The school’s TAKS scores indicated that the school was doing well in the areas of Reading, Writing, and Social Studies in comparison to the state average in the Texas Academic Indicator System. The area of math has been a major concern for the past three years and many strategies and techniques such as double dosing, giving the same subject two periods, tutorials, and student workshops have been used to address the problem. The problem was chronic, and the current solutions had proven to be temporary. The scores went down as soon as the school resumed its regular schedule. The school was looking for a permanent solution to address the problem in the area of mathematics.

This schedule doubled the amount of instructional time that was scheduled relative to scheduling practices of past years. Evaluation of the consecutive block schedule model and the split block schedule model was necessary to determine if there was a difference in academic achievement between the two models. The goal of the study was to determine which type of block schedule had the best impact on the students’ academic achievement as measured by the TAKS benchmark test. The results of this study provided school administrators the necessary data to determine the type of block model that was most beneficial for students.

Research Questions

The research guiding questions are:1. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model?2. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model?3. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model?Research Hypotheses

H_{1}: There was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model.H

_{2}: There was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model.H

_{3}: There was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model.

Significance of the Study

The goal of the study was to determine which type of block schedule had the greatest impact on the students’ academic achievement as measured by the TAKS benchmark test. The results of this study were significant to middle school administrators interested in using block scheduling. “There is a need for further evaluation of the restructuring of time” (Coil, 2000, p. 12). An evaluation of the consecutive block schedule model and the split block schedule model was necessary to determine if there was a significant difference in academic achievement between the two models. The results of the study were significant because they provided school administrators the necessary data to determine the type of block model that was the most beneficial for students.

Assumptions1. “The dependent variable was normally distributed in population for any specific value of the covariate and any one level of a factor” (Green & Salkind, 2005, p. 210).

2. “The variances for the dependent variable for the conditional distribution describe in assumption one are equal” (Green & Salkind, 2005, p. 210).

3. The cases represented a random sample from the population, and the scores on the dependent variables were independent of each other (Green & Salkind, 2005, p. 210).

4. “The covariate was linearly related to the dependent variable within all levels and the weights or slopes relating the covariate to the dependent variables were equal” (Green & Salkind, 2005).

5. The 2004 TAKS release benchmark instrument used to measure student achievement was a valid and reliable instrument.

Delimitations of the Study

The data for this study was collected from one Texas middle school. The sample included students from sixth, seventh, and eighth grade levels. Math scores have increased in the pass four years from 66% to 87%. Gain may be associated with the pilot test of consecutive bock scheduling.

Limitations of the Study

1. This study did not control for student schedule changes, variations in teachers’ experience, differences in teachers’ strategies, and other factors beyond the researcher’s knowledge and control that improved students’ TAKS benchmark scores.

2. The researcher could not control the estimated 14.9% student mobility rate (Texas Education Agency, 2008).

3. This study accounted for pervious forms of block scheduling that had already improved TAKS benchmark scores.

4. A major limitation was the middle school’s demographic population was composed of 99.7 % Hispanic, 99% economically disadvantaged, and 42% LEP (Limited English Proficient) (Texas Education Agency, 2008). The results were able to be generalized to the middle school corresponding to the study. However, the findings had implications for other middle schools with similar demographic populations in the district, region, or state.

Definitions of Terms

*A/B Alternating Day Block Scheduling*: A schedule in which students met six or eight classes every other day for an entire school year in periods of 85 to 100 minutes of instructional time (Canady & Rettig, 1995).

*Academic Excellence Indicator System*(AEIS): This system compiled a wide range of information on the performance of students in each school and district in Texas every year.

*Alternating Block Schedule*: An eight period schedule in which four classes met 90 minutes each, every other day; also known as 8-block or 4X4 A/B block (McCumber, 2001).

*Block Scheduling*: A school schedule that consists of instructional periods of large blocks of 60 to 90 minutes (Canady & Rettig, 1995).

*Carnegie Unit*: A measurement of the instructional seat time in which 120 instructional hours in a high school course equaled one unit of credit towards high school graduation (Akins, 2000).

*Consecutive Block*: Two period block schedule consecutively or one after the other.

*Copernican Plan*: A paradigm shift based on Nicolaus Copernicus, Polish astronomer and mathematician who was a proponent of the theory that the idea that the universe revolved around the sun instead of around the earth. Joseph M. Carroll’s Copernican plan proposed the education system should not revolve around the Carnegie unit but instead around the students’ needs. The plan was based on relationship building, systemic change, and continuing evaluation (Education World Inc., 1997).

*Effective School Correlates*: The means to achieving high and equitable levels of student learning. It is expected that all children will learn at least the essential knowledge, concepts and skills needed so that they could be successful at the next level the following year (The Association for Effective Schools, 1996).

*Modified or Hybrid Block Schedule*: A schedule that varied short and long terms of instruction over the 180 days of the school year (Canady & Rettig, 1995).

*Rote Memory*: A type of “memory that does not have a long shelf life because it has few hooks in long term memory” (Gregory & Chapman, 2006).

*Split block:* A two period block schedule composed of two 45 minute periods that are not consecutive. A group of students attended one period, exchanged classes and later during the same day, the group of students returned to the same teacher for a second 45 minute block.

*Texas Assessment of Knowledge and Skills (TAKS):*A criterion-referenced test Administered to all students grades third though eleventh grade (Exit Level) in which student had to pass reading and math in order to be promoted at the fifth and eight grades and the exit level tests in eleventh grade to graduate from high school. This criterion reference test was used to determine the academic progress and rating of each school via the AEIS (Academic Excellence Indicator System).

*Time and Treatment:* The amount of instructional time allocated to cover and master a particular subject matter.

*Traditional Schedule*: The traditional schedule was one that involved a standard six to an eight period day, where class length was less than 60 minutes (Keenan, 2000).

Organization of the Study

This study proposal was composed of three chapters. Chapter I included the introduction to the study followed by an overview of the statement of the problem. The purpose of the study was established; the research questions and hypotheses were proposed. Chapter II provided an overview of the review of literature. The history and conceptual foundations of block scheduling were discussed. The different types of block scheduling models were explicated and current block scheduling trends were reviewed. The methodology for the study was discussed in Chapter III.

CHAPTER II

A REVIEW OF THE LITERATURE

Introduction

Educators are on a continuous journey searching for new strategies, activities, techniques, and approaches to enhance teaching and learning, make educational practices more efficient and effective, and maximize time on task. “One of the improvements has centered on having at least part of the daily schedule organized into longer blocks of instructional time, or block scheduling” (Dougherty, 1997, p. 1). While a few school districts had done extremely well, most were mediocre. Even students at the highest levels of achievement were considered mediocre when compared with the rest of the developed world (McCluskey, 2008). “Block scheduling has recently challenged the traditional high school schedule that emerged in the early 20th century. Literature revealed that approximately 50% of high schools in the U.S. used some type of block scheduling” (Andrews, 2003, p. 13). One of the major problems in the improvement of education had been the difficulty in changing the teachers’ instructional strategies, techniques and approaches (Steffe, 1990).

According to the Association for Effective Schools (1996), a school should attempt to educate all students equally regardless of race, gender, and socioeconomic status. Effective comparisons were the characteristic, traits, and attributes that enabled schools to educate all students with the essential knowledge, concepts and skills they needed to be successful in the subsequent years. A school was considered to be effective when all students were treated equitably and were able to achieve high levels of learning. “Identifying the components, indicators, correlates, and attributes that make great schools succeed and good students do extremely well can enable school districts to replicate success” (Association for Effective Schools, 1996, p. 1).

This literature review gave a brief history of the school reform movement, scheduling practices, and types of schedules used by American schools, and block scheduling efficiency issues. The traditional eight period class schedules which most schools used included five subject core areas, two electives, and lunch. The contemporary 4X4 block schedule model was used by many high schools. The A/B alternating block was used typically at middle schools. The modified block schedule used different combinations of block scheduling and was used by different schools for several purposes. While many schools had used different forms of block schedules, few had implemented a hybrid model at middle school that targeted only math and maintained most of the traditional schedule. The advantages and disadvantages of the 90-minute math block schedule were discussed. The literature review concluded by focusing on two types of 90-minute math block schedule models and how they impacted achievement and learning.

Historical Background

The catalyst of the modern education reform movement was the National Education Association's Committee of Ten Report of 1892. The current traditional eight period schedule had its origins in the early 1900. “Prior to 1892 and the work of the National Education Association's Committee of Ten, early high schools and their predecessors, Latin Grammar Schools and Academies, showed some flexibility in their schedules” (Canady & Rettig, 1995, p. 13). The report of the Committee of Ten was the first report that called for a uniform high school structure that had been put together which included recommendations for time allotment (Taylor, 1894). This movement instigated the structure that is known today as the Carnegie Unit of Credit.

Carnegie Unit

The Carnegie Foundation for the Advancement of Teaching, founded by Andrew Carnegie in 1905 as an independent policy and research center, developed The Carnegie Unit in 1914 as a means that measured academic credits with the purpose of setting a standard measure of students' courses via the amount of time students studied in a particular subject (The Carnegie Foundation for the Advancement of Teaching, 2007). Soon after, high schools adopted the Carnegie Unit, which evaluated students’ academic progress and kept track of students’ credits. The Carnegie Unit became the standard unit of measurement used by most colleges, universities, high schools and middle schools (Canady & Rettig, 1996). At the middle school and high school levels, the unit was based on 120 hours of instruction per subject. Classes met five times per week, for 45 to 60 minutes per day, for 30 to 36 weeks a year. The students earned one credit unit per class per year. At the college level, 750 minutes of instruction equaled one Carnegie Unit or a credit hour (The Carnegie Foundation for the Advancement of Teaching, 2007). Today most high school schedules use the 8 period schedule and the Carnegie Unit. The Carnegie Unit was significant to American education because it was the first unit to standardize time and treatment of education (Maeroff, 2009). While different innovative schedules had been developed throughout the years, most of them were still based on the Carnegie Unit, which revolved around the premise that regardless of students’ ability and complexity of the subject matter, a school credit was based on 120 to126 hours of instruction (Wolfe, 2005). The schedule was simplified, modified and rearranged, but no additional time was allocated for additional instruction (Evans, Rice, Sokolow, Sloan, & Vona, 1998). Some students required additional help and some subject matter was more complicated than others.

A Nation at Risk Report

A Nation at Risk Report created rippling effects that reverberated in the educational world for the subsequent 20 years. In 1983, the National Commission on Excellence in Education reported that the, “declines in educational performance are in large part the result of disturbing inadequacies in the way the educational process itself is often conducted” (p. 1). The report classified the inadequacies in the educational process into content, expectations, time and learning. Inadequate articulation and coordination of the curriculum compounded with deficient rigor and relevance in core content areas, and laissez faire states’ educational agencies led to low standards in American schools. “Secondary school curricula have been homogenized, diluted, and diffused to the point that they no longer have a central purpose” (The National Commission on Excellence 1983, p. 12).

According to the report, in some states up to 50% of the graduation requirements were composed of elective classes. “This curricular smorgasbord, combined with extensive student choice, explains a great deal about where we find ourselves today” (The National Commission on Excellence 1983, p. 13). In the area of expectations, the commission found deficiencies in the amount of homework, foreign language, dismal math and science requirements, and minimum competency examinations. In addition, the committee found that textbook companies had lowered the textbooks’ reading due to students’ low reading ability. As a result, “Many books do not challenge the students to whom they are assigned” (The National Commission on Excellence 1983, p. 13). The National Commission on Excellence (1983) contended that American students spent less time studying and lacked basic studying skills, which made studying efforts less effective. In most industrialized countries, students spent at least 8 hours a day and over 220 days per year at school. American students spent only 6 hours a day and time including several noncore electives. American schools also had one of the shortest years in the world, 180 days per year (The National Commission on Excellence 1983).*Prisoner of Time*

The 1994 Prisoner of Time report produced by the National Commission on Time and Learning addressed many of the issues and concerns bought to light a decade earlier by the Nation at Risk Report. In addition to finding that many of the problems that existed in the early 1980s still persisted, the report found the American educational system was a prisoner of the school clock and calendar. The report stipulated that the school clock affected three major components of the educational organization. First, the school calendar and clock controlled how people prearranged their occupation. Second, it affected how administrators managed, organized, and supervised the school. Third, it influenced how teachers developed and implemented curriculum (The National Commission on Time and Learning, 1994).

According to the commission, learning had changed in many ways in the past 150 years, but the amount of time spent on learning had remained constant in American public schools. Improving education was not only a mater of increasing time. Kinley, (2007) pointed out that school districts needed additional funding to increase instructional activities, improve the quality of teachers, administer relevant counseling, and provide meaningful professional development, and student services. American schools were bound by the clock and calendar. “Our time-bound mentality has fooled us all into believing that schools can educate all of the people all of the time in a school year of 180 six-hour days” (The National Commission on Time and Learning, 1994. p. 3). Students with different abilities, backgrounds, and aptitudes learned different materials and subject matter at the same rate regardless of comprehension of the materials. “The rule, only rarely voiced, is simple: learn what you can in the time we make available” (The National Commission on Time and Learning. 1994, p. 4). While students in other countries spent more time in school and on homework, we expected American students to learn as much as their counterparts in only half the time. The principal problem that our education system confronted was still the same one as spelled out in The Nation at Risk Report of 1983. American students spent less time at school and did less homework than students in other nations (The National Commission on Time and Learning, 1994).

Traditional Schedule

What we know today as the traditional schedule was created from the recommendations of the Committee of Ten and the development of the Carnegie Unit. Since the early 1900s, colleges, high schools, middle schools and even elementary schools had utilized the Carnegie Unit to develop their schedules. The Carnegie Unit freed schools from early traditions and established standards of time and treatment for awarding credits (Hampton, 1966). Since its inception in the early 1900s, the Carnegie Unit dominated the course structure and remained unchanged for almost one hundred years. Most high school, college, and university credit hours, time and treatment, and intervention initiatives revolved around the Carnegie Unit. Only a few schools had diverted from the norm to add extra periods (Canady & Rettig, 1995). Queen, (2007), articulated that for the most part, high school schedule structure had remained the same over a century. A few exceptions and modifications occurred during the 1960’s and 1970’s as a result of open education classroom philosophy. During this period of time administrators experimented with the idea of flexible class periods. In a traditional eight period schedule that most schools used, students had five core area subjects, two electives, and lunch. In this type of schedule, classes were 55 minutes long with five minutes for changing classes. Students had to deal with seven different teachers, and each teacher had different requirements, rules, and expectations for their classes.

Middle School Concept

Most American high schools echoed college and university schedules and used some form of the Carnegie Unit to standardize credits. For many years, junior high schools emulated high schools in the use of the credit system. They had similar schedules and classes and were arranged by departments. Junior high schools were usually for grades 7th, 8th, and 9th. The first middle schools were created in 1950’s in order to better serve the developmental needs of students. The conceptual framework behind the idea of the middle school concept was similar to the School within a School Model. It attempted to service students through smaller learning teams, advisory classes, and interdisciplinary teaching and learning (Banks, 2003). This type of setup created several mini schools, learning communities, and clusters within a middle school with team leaders playing the role of mini principals and collaborating with the team in the decisions making process (Dewees, 1999). The middle school concept had promoted a shared vision and mission that recognized student achievement and encouraged administrators, teachers, parents, and students to promote a positive school climate and partnerships for learning and high expectations (Ziebarth, 2006).

William Alexander created the conceptual framework for the middle school concept. The concept gained national attention in 1963 (Anfara, Andrews, & Mertens, 2005). The Middle School Concept revolved around the idea of grouping about 100 students into a team or a cluster with 3-5 teachers to service a common group of students. This group of students rotated only among the same group of teachers (Coffey, 2008). The junior high concept was a traditional approach that mimicked the high school concept in the method of servicing middle school students. Student services were based on a departmentalized configuration. Needs assessment, resource allocations, and academic services were proposed and lead by the different department heads. As the junior high concept decreased in favor and the middle school gained momentum over 25 years, the team leaders had taken hold of many of the department heads’ responsibilities (Ziebarth, 2006).

While the middle school concept brought about substantial structural changes to junior high schools, the Carnage Unit still dominated the credit structure and time allocation of most middle schools. Under a traditional schedule, middle school students still had to deal with seven to eight different subjects a semester and be at nine different locations throughout the school day within a seven hour day. Likewise, teachers taught approximately seven classes per day and kept track of up to 125 students, and it was not uncommon for teachers to have various preparations (Irmsher, 1996). This structure assumed that all courses had the same complexity and that all students learned at the same rate. It did not allow teachers and students the flexibility or time to address the students’ needs. Students were expected to accumulate fragmented information, and teachers relied on lectures as the most effective way to expose students to large amounts of information in a short period of time.

J. Lloyd Trump Flexible Block Schedule

The first attempt to eliminate the traditional eight period schedule and replace it with flexible block schedule that varied in lengths was done by J. Lloyd Trump in 1959 (Queen, 2002; Canady & Rettig, 1995). Trump’s idea was to develop a schedule that was tailored to the needs of the students, based on the complexity of the subjects, and the use of different instructional strategies. The schedule designed called for condensed and extended classes and allocated from 20 minutes for simple subjects to 100 minutes for more demanding subject matters (Canady and Rettig, 1995). A major problem with current block scheduling models was that they did not increase instructional time allocation. Most block schedules reorganized class periods and meeting days, but the total instructional time allocated per subject area remained the same. Trump’s design differed in the way that it added more time to some classes and allowed teachers to experiment with a variety of instructional strategies to better address the needs of the students (Queen, 2007).

Trump’s original intent for block scheduling was to reduce the amount of time students spent in less demanding subject areas and use that time to add instructional time to other subject areas. According to Bennett, (2008) most block schedule models did not increase instructional time in the area of mathematics. In spite of the fact that the block schedule research was inconclusive, most researchers agreed, “School leaders should be empowered to continue to determine the schedule that best meets the needs of the local school programs, students, school climate, and community” (Wright, 2005, p. 91).

Joseph Carroll’s Copernican Plan

In 1960, Joseph Carroll, pilot tested the Copernican Plan in the District of Columbia during the summer school program. The Copernican Plan was a paradigm shift based on Nicolaus Copernicus, Polish astronomer and mathematician, who proposed that the universe revolved around the earth instead of around the sun. In the same manner, Joseph M. Carroll’s Copernican Plan proposed that the education system should not revolve around the Carnegie Unit, but should instead revolve around the students’ needs. The plan was based on relationship building, systemic change, and continuing evaluation (Education World Inc, 1997). The plan proposed the restructuring of schedules that enabled students to focus on a limited number of subjects per semester and allowed teachers more manageable work loads that provided more individualized instruction and therefore improved student performance (Cromwell, 1997; Mell, 2007; Crushman, 1995; Queen, 2007).

The Copernican plan’s major change was to have students enroll in one four-hour class for a period of thirty days. In a period of six month, the students earned a total of six credits per year, and at the same time fulfilled the 180 day school requirement (Carroll, 1989). This plan was implemented by Joseph Carroll during summer school as a pilot program. Many of the current block schedule models used by high schools today are derived from Joseph Carroll’s Copernican Plan (Mell, 2007). The calls continued to be for restructuring school schedules and time usage which allowed schools to provide students and teachers the time for scaffolding lessons and to promote deeper learning. Block scheduling gained momentum in the late 1980’s because it provided the teacher with longer periods that allowed the teacher to interact with students without constant interruptions (Cobb, Abate, & Baker, 1999). “As early as 1984, John Goodlad had warned educators that the traditional school structure does not allow time for individualized instruction, for extended laboratory work, or for remediation and enrichment” (Queen, 2000, p. 3).

Learning at Different Rates

In 1994 the National Commission on Time and Learning proposed that schools that rely less on the 50-minute period, develop new uses of time to ensure the schools’ effectiveness, and block schedule two or more periods for extended exploration or complex topics. “Providing a more flexible school day could also permit American schools to follow international practice between classes students remain in the room and teachers come to them” (National Education Commission on Time and Learning, 1994, p. 5). “The National Commission on Time and Learning stated that if experience, research, and common sense taught nothing else, they confirmed the truism that people learn at different rates and at different rates with different subjects” (Bradford, 2002, p. 3). The need to increase student achievement, provide students with more leaning opportunities, the ability to meet state and national standards, and increase graduation rates, had caused schools to investigate the variable of time. As a result, many schools had developed creative schedules in an attempt to maximize teaching and learning and minimize interruptions and down time (Calvery, Sheets, & Bell, 1999).

There are many benefits associated with block scheduling. Students are able to take more classes, improve attendance, and save time in exchanging classes. There is less disruptive behavior, which means that more students are able to take advanced classes, and students get more individualized attention. There are several models to fit different needs and involve fewer but longer classes than traditional schedules (Northwest Regional Educational Laboratory, 2001). “Block scheduling will create a less pressured, more intimate atmosphere in the school, creating a place where children are excited to learn and teachers are inspired to teach” (Bennett, 2008, p. 2).

The 4X4 Block Schedule Model

Classes in the 4X4 block scheduling are 90 minutes long for only part of the year. The academic year is split into quarters and use a four period day. Students benefit because they have the opportunity to take four courses per semester and receive up to eight full credits per year. Instead of focusing on eight classes throughout the year students focus and complete four classes per semester. Students do not have to wait until next year to retake or to do credit recovery work (Queen & Isenhour, 1998). Teachers also benefit because they have fewer students per day, and fewer classes, which means teachers prepare for fewer courses per semester, and engage in less record keeping. This type of scheduling works well for high school acceleration and credit recovery classes.

While there appears to be many benefits to the 4X4 block schedule, research does not clearly support such claims. According to Wright (2005), data from the years of 2000 to 2003 suggest that there was no significant difference between the Advance Placement United States History examination scores of students on the A/B alternating block schedule, the 4 X 4 block schedule, or the traditional schedule. A major concern about the 4X4 block is that only a few schools have successfully implemented a pure 4X4 block schedule without making some form of modifications (Robbins, Gregory, & Herndon, 2000).

Table 2.1

*Sample of a Basic 4 x 4 Block Plan for Eight Courses*______________________________________________________________________Fall Spring ______________________________________________________________________Course 1 Course 5Course 2 Course 6

Course 3 Course7

Course 4 Course 8

_______________________________________________________________________*LAB at Brown University, 1998, p2*

A/B Block Schedule Model

The A/B Block Schedule Model was an alternating schedule in which students took only half the number of classes per day but double the amount of time per class. Students took the other 3 to 4 classes the next day. Instead of taking six or seven classes every day, students concentrated on only three classes or four classes per day. Students took eight 90 minute classes every day over a six day cycle, with four classes meeting on Day A and four classes meeting on the alternating Day B. Over the span of the entire year, all courses met an equal number of days. The schedule alternated every day and allowed students to receive the same amount of instruction as the traditional schedule (Canady & Rettig, 1995). “The A/B Block scheduling is easier than 4X4 Blocking because it has fewer political and administrative problems” (Robbins, Gregory, & Herndon, 2000, p. 2).

Table 2.2

*Sample Week of an A/B plan (alternative day) for Eight Courses*

_______________________________________________________________________

Monday Tuesday Wednesday Thursday Friday Monday

Day A Day B Day A Day B Day A Day B

_______________________________________________________________________

Course 1 Course 2 Course 1 Course 2 Course 1 Course 2

Course 3 Course 4 Course 3 Course 4 Course 3 Course 4

Course 5 Course 6 Course 5 Course 6 Course 5 Course 6

Course 7 Course 8 Course 7 Course 8 Course 8 Course 7

_______________________________________________________________________

*LAB at Brown University, 1998*

Modified Block Schedule Models

The modified block schedule may not follow the typical block scheduling format or may include several block scheduling models. “Schools may have students attend school based on a 4X4 block on Monday through Thursday, and a regular eight period schedule on Friday. Or, they might have two blocked classes in a day, combined with three regular periods” (Canady & Rettig, 1996, p. 4). The modified block schedule could be used by schools that want to target specific needs of students in a particular area. According to a study by the Washington School Research Center, the 4X4 and A/B Alternating Block schedules were rated as the overall lowest performing schedules. On the other hand, students in the seven period traditional schedule and Modified Block schedules were the highest performing in reading, writing, and math. “It is important to note that there is no statistical difference between the traditional seven period day and Modified Block schedules” (Baker, Joireman, Clay, & Abbott, 2006, p. 13).

*Modified Math Block Consecutive Schedule Model*

A consecutive block schedule consisted of a two period block scheduled consecutively or one after the other. One group of students in the consecutive block schedule would go to math first and second period, another group of students would go to math third and fourth period, and a third group of students would go to math seventh and eighth period. Teachers would have a planning period, a team planning period, and a lunch period.

Table 2.3*Modified Math Block Consecutive Schedule Model*

_____________________________________________________________________

Monday Tuesday Wednesday Thursday Friday

_______________________________________________________________________

1^{st} period Math I Math I Math I Math I Math I

2^{nd} period Math II Math II Math II Math II Math II

3^{rd} period Reading Reading Reading Reading Reading

4^{th} period Writing Writing Writing Writing Writing

5^{th} period Lunch Lunch Lunch Lunch Lunch

6^{th} period History History History History History

7^{th} period Science Science Science Science Science

8^{th} period PE/ Band PE/ Band PE/ Band PE/ Band PE/ Band

9^{th} period Elective Elective Elective Elective Elective

_______________________________________________________________________

Modified Math Split Block Schedule Model

A spilt block schedule was similar to a consecutive block schedule in the way that students had two math periods. It was different in that students went one period to math in the morning and another period of math in the afternoon. In the split block schedule a group of students went to math first period, went to other classes and returned sixth period for the second math class. Another group of students went to math second period and returned to math seventh period. A third group of students went to math third period and returned eighth period to math.

Table 2.4

*Modified Math Split Block Schedule Model*

_____________________________________________________________________

Monday Tuesday Wednesday Thursday Friday

_______________________________________________________________________

1^{st} period Math I Math I Math I Math I Math I

2^{nd} period Reading Reading Reading Reading Reading

3^{rd} period Writing Writing Writing Writing Writing

4^{th} period Science Science Science Science Science

5^{st} period Lunch Lunch Lunch Lunch Lunch

6^{th} period History History History History History

7^{th} period Math II Math II Math II Math II Math II

^{th}period PE/ Band PE/ Band PE/ Band PE/ Band PE/ Band

9^{th} period Elective Elective Elective Elective Elective

______________________________________________________________________

Block Scheduling Conflicting Results

Block scheduling research has yielded conflicting results. Some cases studies have produced no evidence to support academic gains in student achievement. While some experts declared there was little evidence to indicate significant gains in American schools that have implemented block scheduling, other experts pointed out that block scheduling studies have shown promising results. The conflict originated from research that presented positive results in students in G.P.A. and attendance but no difference in standardized tests (Cobb, Abate, & Baker, 1999; The Center for Education Reform, 1996). LAB at Brown University, (1998) had the same opinion. The limited data on block scheduling confirmed that it does not have a negative impact on standardized scores. Retention of instruction and learned materials in several subject matters was a concern under block scheduling. Student retention was deeply debilitated in content areas that constructed upon prior knowledge such as science, math and foreign languages (The Center for Education Reform).

A major criticism of block scheduling was that it had a detrimental effect on students’ retention. Retention suffered because too much information was given at one time, and much of it was lost from one level of a subject to the next (Queen, 2002). In addition, block scheduling required a large amount of time for independent study. (Bennett, (2008) was of the opinion that block scheduling would supply less dominance and freshness to the material covered. On the other hand, shorter classes and more frequent classes provided students more opportunity to increase memory retention. However, the retention problem may have more to do with the nature of retention than with block scheduling. Rote memory, the process of memorizing and regurgitating information without internalizing the substance worked well for low level learning such as multiplication, recitations, and drills. This type of learning put skills into automatic memory with comprehension or understanding (Gregory, & Chapman, 2006).

Memory loss was associated with short-term memory which was lost quicker because it involved information that was not learned as well. On the other hand, the process of transferring information from the short-term memory to the long-term memory involved a more complex physiological process (Intelegen Inc., 2005). Block scheduling may not work well for drill and kill activities and testing strategies designed for short-term gain using short-term memory. Students may be able to learn and retain more knowledge for activities and experiences that create a strong emotional connection and enrich sensory stimulation. “The brain is a pattern seeking devise and enjoys making meaning and connections between new ideas and those previously learned” (Gregory & Chapman, 2006, p. 96). Block scheduling may provide teachers the time for more in-depth instruction, individual instruction, and field experience that provide students the background connection that engages their sensory stimulation and long-term memory.

Queen, (2002) found that block scheduling increased instructional time, reduced the number of classes and preparations. Teachers had time for more in-depth teaching of concepts and student discipline improved. LAB at Brown University, (1998) found that schools that had implemented block scheduling had less discipline problems because teachers spent more time with the students, classes were more challenging and teachers developed a closer relationship with the students. Another advantage to block schedule was that students had less passing periods which reduced the opportunities for disruptions. The Center for Education Reform, (1996) outlined additional benefits of block scheduling to include fewer students failed, higher grade point average, and ensured more students made the honor roll, and less students dropped out of a school. “There is some indication that block scheduling provides benefits to learners who have not thrived in the traditional classroom setting. Block scheduling may indeed be a worth while alternative for reaching a school's most at-risk students” (The Center for Education Reform, 1996, p. 3).

Doubling Time

A major problem with block scheduling was that many schools block all subjects rather than subject areas that need to be blocked, and students ended up in block classes they didn’t need. As a result, no additional time was given to any particular subject and time and learning was simply reorganized. The Center for Education Reform’s, (1996) concern about block scheduling was that students had a short attention span and doubling the length of instruction in classes might double the amount of learning. Teachers might have a hard time keeping students focused on the same subject matter an extended period of time. In addition, American students spent only half the amount of time on core academics than students in Japan, France, Germany, and other industrialized counties. According to The National Commission on Time and Learning reported in Prisoners of Time report,* *(1994) data from the U.S. Department of Education showed, that students in Japan, France, and Germany received two times more instruction in academic core than students in the United States (Sexton, 2003).

While teachers and administrators reported better discipline, attitudes, and student teacher relationships, research on academic achievement under block scheduling had been inconclusive because there was not enough data to corroborate the positive outcomes to block scheduling (The Center for Education Reform, 1996). Most studies did not find significant differences between the block scheduling plan and traditional scheduling (Lewis, Cobb, & Winokur, 2003; Fletcher, 1997). On the other hand, teachers believed that students needed daily instruction take full advantage of the learning process” (Lewis, Cobb, & Winokur, 2003, p. 4). An examination of the students’ advanced placement scores by the College Board concluded that students who were taught AP English literature under an extended period that met everyday scored higher than students in a traditional schedule, and 4X4 schedules (Veal, 1999). Additional research by Wright (2005) on advanced placement on United States history exams indicated that the consecutive block scheduled students’ scores did not significantly differ from students on regular non-block schedules.

Consecutive Block Schedule Verses Split Block Schedule

There were advantages and disadvantages to the traditional consecutive block schedule and the split block schedule. Some of the biggest advantages of the consecutive block schedule were that it reduces discipline problems, reduces time exchanging classes, and reduces class teacher’s clerical duties such as taking attendance, picking up absence slips, homework, and projects. Starting class and refocusing students can take up to ten minutes of class time of class out of every 50 minutes class. Consecutive block scheduling allocated larger blocks of time that allowed the teacher a manageable workload that could lead to a more productive classroom environment. During these extended class periods, teaches could use a variety of teaching methods to provide students better learning (Irmsher, 1996). This process could take up to 10 minutes out of every class period. The consecutive block schedule could save valuable time which could be used for instruction. The biggest strength of the 90 minute traditional consecutive block schedule was also the biggest weakness. “An adequate attention span is an important part of learning in a classroom setting, enabling children to organize and consolidate important features of the subjects being studied” (Gottfried, 2008, p. 1). According to Bennett (2008), students had a limited attention span of 30 to 45 minutes. Research showed students reach a saturation point at which learning capacity was diminished. This idea was supported by Cooper’s (2001) statement that the 90 minute block schedule may exceed the students’ attention span. Block scheduling critics contended that because the average person’s attention span was 15 to 20 minutes, adolescents were unable to remain focused for 90 minutes.

There were opposite advantages and disadvantages to the Split Block Scheduling. Split block scheduling did not exceed the students’ attention span. Teachers could take the time to deliver instruction, have guided practice and independent practice within the allotted 50 minutes without losing the students’ attention and interest. The process could be repeated in the second block. The disadvantages of the split block are that time was wasted in the passing of classes; teachers must restart the lesson, and refocus the students.

Theoretical Framework

This study was based on the guiding principle that giving students more time to learn would result in greater academic achievement. Time allocation and period length should be allotted according to the individual needs of the students (Canady & Rettig, 1995). Blocking classes gave the students, as well as teachers, more time to dedicate to each subject. Having only a few classes per day reduced the work load for students, preparation time for teachers, and permited better interaction between teacher and student which led to the development of interpersonal relationship, a key component of J. Lloyd Trump’s theoretical framework (The Center for Education Reform, 1996). Different subjects had different levels of complexity, and therefore required different amounts of time for mastery (Canady & Rettig, 1995). When properly scheduled to address the needs of individual students, block scheduling provided the teachers the necessary time for in-depth learning by allowing the teachers extended instructional time via elongated classes. These extended classes offered students and teachers opportunities to get involved in a variety of activities such as project based learning, hands on activities, thematic unites, and interdisciplinary activities that enhanced comprehension, higher order thinking skills, and that engaged the long term memory and retention (The Center for Education Reform, 1996). Depending on the level of complexity, subject matter, and abstract concepts, some classes required the use of labs, computers, hands-on activities, manipulatives, and instructional models that required the use of more time. Therefore, some classes should be longer than others (Canady & Rettig, 1995). Block scheduling allowed teachers the time to develop background, build solid foundations, and scaffold lessons.

One of the major advantages of block scheduling was that it allowed for a variety of methods and innovations which could be brought into the lesson making it more conducive for team teaching, thematic units, experiments, and field work (The Center for Education Reform, 1996). The longer periods permitted lesson flexibility, enrichment, and teaching for mastery. It enabled teachers to advance and abandon the old lecture style that depended on delivering large amounts of information on a short period of time without developing deep understanding of content matter (Learning Spark. 2009). Block scheduling was expected to produce higher morale, better attendance, higher grades, and lower failure and dropout rates. “The Commission is convinced that if American students are to meet world class standards all children will need more academic time” (The National Education Commission on Time and Learning, 1994, p. 10).

Some major concerns about block scheduling were that it would exceed the students’ attention span and less frequent meeting periods would result in lower retention rate. On the other hand, block scheduling vowed to provide teachers and students the time for more in-depth teaching and learning to develop strong emotional connections that engaged the long-term memory making the material learned more permanent. In addition, block scheduling provided teachers time for more one to one instruction which benefited at-risk students (The Center for Education Reform, 1996; Gregory & Chapman, 2006). The review of literature does not support either claim.One reason why block scheduling research had been inconclusive may be that some researchers and practitioners misunderstood the original theoretical framework of block scheduling and designed studies based on erroneous ideas. One major misconception about block scheduling was that block scheduling was basically rearranging the time. J. Lloyd Trump’s idea was not to simply rearrange time but to create a schedule according to the needs of the students (Canady & Rettig, 1995). Another misconception was that block scheduling was simply about creating longer periods (Keenan, 2000). It was easy to see the flaw in this concept in that it served no purpose to give a student two periods of electives such as art, band and physical education when the student could not read, write, or do math. By the same token it was not beneficial to the students to provide two periods of instruction in a core area where the student was doing well. J. Lloyd Trump’s idea was to have some short classes and use the time gained to make other classes longer according to the needs of the student (Queen, 2002). Practitioners have altered the idea and created a model such as the 4X4 block and alternating block model and implemented them across the board for all students regardless of the students’ needs. While these models worked well for credit accrual, they did little to increase student achievement.

Choosing a Model

Choosing a model that fits the needs of the district, campus, or school may be as important as the implementation of block scheduling. The goals of the school should be well thought out before implementing block scheduling. A 4X4 block schedule model may work well in a high school that wants to target credit accrual problems. “Students have only four courses to concentrate on at any one time; they have greater opportunities for acceleration” (Cobb, Abate, & Baker, 1999, p. 7). On the other hand, an alternating A/B block schedule model may provide a middle school more time for in-depth or extended learning for writing classes to do essays, long planning periods and reading classes to read novels (Queen, 2002). A Split Block Model is a variation of the modified block and was developed to address scheduling issue, brought about by consecutive block schedules. In Split Block Schedule Model, a class met once a day in the morning and again in the afternoon for a total of 90 minutes. There were several potential benefits to this type of schedule. One benefit was that it allowed students with short attention span to take a break, and then return later to the same teacher to review the same lesson the same day. Another advantage was that it eliminated a lot of the problems associated with scheduling block periods. A modified block which blocks only selected classes may be used to target specific areas of instruction or specific student populations (Northwest Regional Educational Laboratory, 2001). When making some classes shorter to gain instructional time to create longer classes, it was important to meet the minimum state time requirement. Rather than implementing block scheduling for all students and for all classes, data should be analyzed to assess the needs of the students and/or campus. Based on the data evaluated, a master schedule should be developed to address problems based on the needs of the students. New curriculum and instructional strategies should be developed to meet the new challenges and benchmarks should be scheduled to evaluate progress.

Review of Literature Summary

The review of literature has explained the shifts in education. The American Modern Education Reform movement began in 1892 with the National Education Association's Committee of Ten report call for a uniform high school structure that included time allotment (Taylor, 1894). After this, the Carnegie Unit established what we know today as 8 period schedules to provide structure and time and treatment allotments to the educational system. The Carnegie Unit was adopted by most colleges, high schools, junior high schools, and even some elementary schools and was subsequently used for the next 100 years (The Carnegie Foundation for the Advancement of Teaching, 2007). By the 1950’s schools recognized the Carnegie Unit did not meet the needs of at-risk students and special populations. In response, most junior high schools adopted the middle school concept and many high schools experimented with block scheduling. The first middle schools were created in 1950’s with the intent of creating schools that would better meet the developmental needs of the students through smaller learning teams, advisory classes, and interdisciplinary teaching and learning (Banks, 2003). In an effort to address some of the shortcomings of the Carnegie Unit William Alexander adopted the middle school concept in 1950 (Anfara, Andrews, & Mertens, 2005). By the early 1990’s most junior highs schools were converted to middle schools.

At around the same time many high schools experimented with block scheduling. J. Lloyd Trump is credited with developing the first flexible block schedule in 1959 (Canady & Rettig, 1995; Queen, 2002). Trump attempted to use block scheduling for similar reasons that junior high schools adopted the middle school concept. The schedule was to be built based on the individual needs of the students. Some classes would be longer than others depending on the complexity of the subject and the needs of the students (Canady & Rettig, 1995). By 1960, Joseph Carroll, pilot tested the Copernican Plan which restructured schedules to enable students to focus on a limited number of subjects per semester (Cromwell, 1997; Crushman, 1995; Mell, 2007; Queen, 2007). Soon after, different block scheduling models including the 4X4 Block, Alternating Block, and Modified Block schedules were developed and implemented by different schools in the United States. Block scheduling results have been inconclusive. While many areas in education improved such as moral, discipline, attendance, grades and student-teacher relationships, there was no conclusive evidence that block scheduling improved academic achievement (Bennett, 2008). The major draw back of most block scheduling models was that they did not create shorter and longer classes as stipulated by J. Lloyd Trump and Joseph Carroll, but simply reorganized time to block. The schedule was not built around students’ needs, and no additional time was allocated for complex subjects.

Contribution of the Study

The current school schedule at this middle school was very similar to most traditional schools. It was made up of eight 45 minute periods which include Reading, Writing, Math, Social Studies, Science, Physical Education, an elective class and a twenty minute advisory period. The school was departmentalized, and students received instruction from five different teachers in the core areas. The grade levels were divided into teams of five teachers, and each team had five classes a day and two planning periods. Like in many middle schools, each teacher serviced about 125 students (Mattox, Hancock, & Queen, 2005). This study on block scheduling contributed to the current body of knowledge in block scheduling by expanding the exploration and analysis of block scheduling to include contrasting differences between split block scheduling and consecutive block scheduling. The findings of the study were significant because they can provide school administrators interested in implementing the data to make an informed decision about the models cost and benefits.

CHAPTER III METHODOLOGY Introduction

“In an attempt to address the issue of time management, districts are experimenting with different configurations that ‘recover’ lost time and organize the day to maximize every moment” (LAB at Brown University, 1998, p. 1). Block scheduling offered alternatives to the traditional 50 minute eight period schedule for school principals and administrators wanting to provide additional instructional time for struggling students and for difficult subjects that required deeper understanding. The concept of block scheduling had been extensively explored and widely used by many school districts. (Northwest Regional Educational Laboratory, 2001). Different block scheduling models had been developed to meet different instructional needs. While several research studies had been conducted to evaluate the effectiveness of the consecutive block schedule, no research had been conducted to evaluate the effects of split block scheduling or the impact on students’ academic achievement. For this reason, “there is a need for further evaluation of the restructuring of time” (Coil, 2000, p. 12).

This study examined the impact that a 90 minute math block schedule would have on the academic achievement of students at a South Texas middle school. This schedule doubled the amount of instructional time that was scheduled relative to scheduling practices of past years. Evaluation of the consecutive block schedule model and the split block schedule model was necessary to determine if there was a significant difference in academic achievement between the two models. The goal of the study was to determine which type of block schedule had the most impact on the students’ academic achievement.

Research Questions

The research guiding questions were:1. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model?2. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model?3. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model?Null Hypotheses

H_{01}: There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model.H

_{02}: There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model.H

_{03}: There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model.

Research Methodology

This quantitative study used a systematic process to measure the relationship between variables (Ackerman, 2008). These statistical procedures were used to determine if there was a significant difference in student achievement on the Texas Assessment of Knowledge and Skills benchmark test between the split block schedule model and the consecutive block schedule model. This matter was important because it helped determine which type of block scheduling model had the most positive effects on student academic achievement (Walker, 2000). The data could be reused on sequel studies to test different hypotheses and may yield different conclusions and results (Ackerman, 2008). Analysis of covariance allowed the researcher to include supplementary variables (covariates) to account for inter-group variation among covariates (Statistics.com, 2009).

Research Design

The design for this study was causal comparative and used ANCOVA. A causal-comparative research study allowed the researcher to select an experiential group, introduce an independent variable, and compare to a control group which did not have the independent variable (Wasson, 2008). This quantitative study examined the difference between scores of students in split block scheduled group and scores of students in consecutive block scheduled group in the Texas Assessment of Knowledge and Skills benchmark test scores. The study analyzed if there was a difference in the TAKS benchmark tests between split block schedule and consecutive block scheduling. “One of the problems with the causal-comparative research is that because the pupils are not randomly placed in the groups, the groups can differ on other variables that may have an effect on the dependent variable” (Wasson, 2008, p. 8). However, this study ensured randomness by dividing the students into two groups according to academic achievement using TAKS data from the previous year. Additionally, the ANCOVA procedure controlled for preexisting differences among the groups. This research analyzed and compared the data the impact that a 90 minute consecutive block schedule and a 90 minute split block schedule model had on students’ academic achievement during the 2009-2010 school in one South Texas Middle School. The results of the study can be generalized to the sixth, seventh, and eighth grade students who took math block classes (Wasson, 2008). “This is an effective method of analysis because it allows one to compare the effect of the independent variable…on the dependent variable” (Walker, 2000, p. 11). This study was a quasi-experimental study conducted in a span of three months and included a pre and a posttest TAKS benchmark.

Population and Sample

The school involved in the study is composed of 660 students: 220 sixth graders, 220 seventh graders, and 220 eighth graders. While all students participated in the experimental research project, only data from students who participated in the pretest and the posttest were aggregated to the study. Due to the high migrant population and high mobility rate, some students came into school after the pretest and others left before the posttest. The student population was divided into two groups within each grade level. The 2008-2009 TAKS scores were used to rank students from lowest to highest. One team got the even number students, and the other team got the odd number students. This gave each team an equal number of high, medium, and low scoring students and students were academically distributed evenly.

The sample distribution model used for this study was based on the Keenan, (2000) population sample distribution model. The first quartile represented the top 25% of academically achieving students based on TAKS scores for the 2008-2009 school year. The second quartile represented the second 25% of academically achieving students based on TAKS scores for the 2008-2009 school year. The third quartile represented the third 25% of academically achieving students based on TAKS scores for the 2008-2009 school year. The fourth quartile represented the lowest 25% of academically achieving students TAKS scores for the 2008-2009 school year (Keenan, 2000, p. 40).

InstrumentationThe 2004 Texas Education Agency TAKS Release Tests was used as a pretest and posttest instrument to determine which type of block schedule had the greatest impact on the students’ TAKS benchmark scores. The data collected for this study consisted of TAKS benchmark scores. Instrumentation is the “process of selecting or developing measuring devices and methods appropriate to a given evaluation problem” (Gall et al., 1996, p. 105). The Microsoft Excel computer program was used to collect and maintain students’ TAKS benchmark scores. Microsoft Excel program is a spreadsheet program used to collect and maintain the campus student’s benchmark scores. The data was housed in a secure area in the principal’s office.

Tango is a benchmark data collection and analysis program and was used to collect the TAKS benchmark data used in this study. Tango is an automated assessment program that uses handheld computers to collect and desegregate assessment data. The program ensured accurate collection and desegregating of data beyond simple scores by providing a clearer picture of students’ gains and losses though individual and group analysis by TAKS objectives and student expectations (TEKS).

Data from Tango and Microsoft Excel was extracted and placed into the Statistical Package for the Social Sciences (SPSS) software. This software was used to conduct the ANCOVA statistical analysis on all data gathered. The variables included student instructional group, pretest scores, and posttest scores.

Procedures

1. The researcher sent a letter to the superintendent of the school district to request permission to conduct the quasi-experimental research study at the middle school.

2. The researcher sent an application form for approval of investigation involving the use of human subjects to the Human Subjects Review Committee at Texas A&M University-Kingsville Educational Leadership, then requested approval to conduct the quasi-experimental research at the middle school where the research was conducted.

3. In August 2009, students in each grade level were assigned into one of two teams, Team A or Team B. The teams were composed of 100 to 130 students per team in each grade level totaling 300 to 350 students per team. The 2008-2009 TAKS scores were used to rank the students. Students were assigned equally to each cluster according to academic quartile, top, middle top, middle bottom, and bottom. The student population was divided into two groups within each grade level. Team A got the even-numbered students and team B got the odd-numbered students. This gave each team an equal number of high, medium, and low scoring students and academically evenly distributed.

4. In September 2009, the parents of the students were asked to sign a consent form for the students’ participation in the study.

5. In September 2009, the students were administered the 2004 math TAKS release test which was used as a pretest. All students took the test. Data was collected via the Tango program.

6. In November 2009, all students were administered the 2004 math TAKS release test which was used as a posttest. All students took the test. Data was collected via the Tango program.

Data AnalysisStudents’ progress was tracked over a period of three months, September to November and data for this study was collected though Tango data collection and desegregation software and Microsoft Excel. The data was imported into SPPS software. The SPSS software was used to analyze the data collected. This study analyzed several variables. “When a group comparison or difference question is asked, the independent variable and design can be classified as between groups or within subjects” (Leech, Barrett, & Morgan, 2004, p. 46). The data analysis yielded the means and standard deviations for the two groups for both test times and a histogram was used to examine the variable distributions for normality.

The independent variable, measured on a nominal scale, was group membership. The independent variable had two levels: split block schedule model or consecutive block schedule model. “Because parametric tests are used to examine for significant difference, between mean, that required the dependent variable be measured on an interval scale” (Kerr, Hall, & Kozub, 2002, p. 53). The dependent variable was the TAKS benchmark scores on the November exams and the covariate was the benchmark test scores from September TAKS benchmark exams.

The ANCOVA procedure was the most appropriate for this study because it allowed the use of pretest and posttest data (Green & Salkind, 2005, p. 206). In addition, an ANCOVA procedure evaluated mean differences across factor levels, adjusted for preexisting differences on covariates when group means differed significantly, and controls for pretest differences to analyze whether there was a significant difference in posttest data, between split block scheduling, and consecutive scheduling (Green & Salkind, 2005, p. 206). The goal of the analysis was to assess the differences among group means and to make adjustments to scores on the dependent variable in order to remove the effect of third variable (Warner, 2007).

Controlling for preexisting differences between the groups, an analysis of covariance (ANCOVA) was used to determine if there was a significantly statistical difference between split block schedule and consecutive block schedule in students’ TAKS benchmark scores. The ANCOVA procedure was repeated a second, time but did not include only 130 Special Education students in the same groups, Team A and Team B. The ANCOVA procedure was repeated a third time but included only 180 English Language Learner students in the same groups, Team A and Team B. The dependent variable, measured on the interval scale, was students’ academic posttest performance in the math TAKS benchmark scores. The covariate, pretest scores, was used to control out preexisting differences between the groups.

This study used a fixed level testing analysis in which the researcher predetermined the acceptable alpha level (α) before the analysis began (Sue & Ritter, 2007). The significant alpha level was predetermined at .05 (*p *value) and was the criterion used for rejecting or failing to reject the null hypothesis. The alpha level of .05 must be met for the results to be considered significant (Mackey & Gass, 2005). “An alpha of .05 means that the probability of error will occur 5 times out of 100” (Sexton, 2003, p. 59). If the probability alpha level of .05 was not met, the hypothesis of no difference would not be rejected, and the study would conclude that there was no difference between the means split block schedule and consecutive block schedule models. These factors would be analyzed using** **Analysis of Covariance (ANCOVA), a general linear model. “ANCOVA is usually a superior choice purely on statistical grounds. It makes use of the correction formula that removes as much as possible of the error valance” (Harris, 2001, p. 40).

Reliability and Validity

Reliability and Validity are two crucial components of any questionnaire, survey, or assessment system. “The reliability of the scores resulting from an assessment should be demonstrated before issues such as validity, fairness, and interpretability can be discussed” (Technical Digest, 2007, p. 167). Reliability is the ability of an instrument, experiment, or test to measure uniformly and consistently when used under the same conditions with the same subjects (Howell et al., 2005).

Reliability is important because it enables a study to be replicated, hence generalized. The 2004 TAKS benchmark test that was used to assess the students’ participation in this study had gone though a thorough evaluation process to ensure the reliability of each item in the test. According to Technical Digest (2007):

Test reliability was an indication of the consistency of the assessment, SDAA II, RPTE, EOC, and TAAS exit level test reliability data are based on internal consistency measures. These include, in particular on the Kuder Richardson Formula 20 (KR20) for tests involving dichotomously scored (multiple choice) items and the stratified coefficient alpha for TAKS tests involving a combination of dichotomous and polytomous (short-answer and extended response) items. Most internal consistency reliabilities were in the high .80’s to low .90’s range (1.0 being perfectly reliable), with reliabilities for TAKS assessments ranging from .83 to .93, for SDAA II assessments ranging from .71 to .86, and for RPTE assessments ranging from .93 to .94. The reliability for the Algebra I EOC Assessment was .92. (Note: SDAA II tests were lengthened in 2004–2005 to increase reliabilities. However, reliabilities may still be lower on some SDAA II tests such as those for grades K–2 because they are shorter to reduce the burden on this population of students.). (p. 167)

Validity is the degree of correlation between the test and a criterion that the researcher is trying to measure. Constructing validity is an on-going process that involves compared scores on an instrument performance with other measures (Siegle, 2009, p. 3). Validity estimates how accurate an evaluation tool or procedure assesses the model that a researcher is trying to evaluate. “While reliability is concerned with the accuracy of the actual measuring instrument or procedure, validity is concerned with the study's success at measuring what the researchers set out to measure” (Howell et al., 2005, p. 16). The 2004 TAKS benchmark test that was used to assess the students’ participation in this study had gone though a thorough evaluation process to ensure the validity of each item in the test. The validity of the items in the TAKS test was reviewed by experts at TEA, Educational Testing Service, Pearson Educational Measurement, and Questar, Inc.

Summary of Methodology Descriptive and inferential analyses (ANCOVA) for each question was conducted to determine the impact of split block scheduling on TAKS scores and to determine which type of block schedule had the greatest impact on the students’ academic achievement. The scores of each variable were compared between the groups using ANCOVA to evaluate if there were statistical differences between consecutive block scheduling and split block scheduling in students’ TAKS benchmark scores. The schools’ 700 students were divided into two groups. Each group had approximately the same number of students and same aptitudes. The quasi-experimental study collected TAKS benchmark scores over a three month period through Tango and Microsoft Excel. SPSS (Statistical Package for the Social Sciences) software was used to analyze the data collected. An alpha level of .05 was used to determine significance.

CHAPTER IV

RESULTS

Introduction

The purpose of this study was to examine the impact of a 90-minute consecutive math block schedule model versus the impact of a 90-minute split math block schedule model on student academic achievement as measured by the Texas Assessment of Knowledge and Skills 2004 benchmark test scores in a Texas middle school. The schedule for the 2009 - 2010 school year was a modified block schedule composed of five traditional 45-minute periods and one two-period math block. This study examined the results of students at a Texas middle school over a period of three months in 2009. A brief review of the implementation of the 90-minute consecutive math block and the 90-minute split math block model was explicated.

Research Questions

The research questions guiding the study were:1. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model?2. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model?3. Was there a difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model?

Demographic Data Analysis

The data were collected from two campus benchmark tests and consisted of the 2004 Math TAKS release pretest and posttest. The ANCOVA procedure from the Statistical Package for Social Sciences (SPSS) was used to determine if there were statistically significant differences in students’ posttest math test scores from a 90 minute consecutive math block schedule model to scores from a 90 minute split math block schedule model, when controlling for preexisting differences using the pretest math scores. The pretest and posttest data were recorded as percents. The raw score, which is simply the number of questions answered correctly on the 2004 TAKS release test, was converted into a percentage. The number of problems was divided by 100 and each question was given an equal value. Because a scale score was not used, the study was unable to interpret differences across sets of test questions and did not take into account the complexity level of the individual questions.

The two block scheduling models were implemented at three grade levels: sixth, seventh, and eighth grade between September 1, 2009 and November 30, 2009. The 2009-10 middle school class was composed of a population of 228 sixth grade students, 231 seventh grade students, and 203 eighth grade students, for a total 662 students. Students were divided into two groups in each grade level.

Table 4.1

*Eligible Study Participants*

_____________________________________________________________________

Special E.L.L. All Split Consecutive

Education Students Block Block

_______________________________________________________________________

6^{th} Grade 34 197 226 101 125

7^{th} Grade 26 97 230 136 94

8^{th} Grade 25 66 205 101 104

Total 85 360 661 337 323

Split 45 172 337

Consecutive 40 188 323

_______________________________________________________________________

From the target population of 226 sixth grade eligible participants, 125 participants, 55%, were assigned to the 90 minute consecutive math block and 101, 45%, were assigned to the 90 minute split math block model. The special education populations for each grade level were proportionally assigned. The sixth grade population was composed of 34 special education students. Fifteen, 44%, were placed in the 90 minute consecutive math block schedule model, and nineteen students, 56%, were placed in the 90 minute split math block schedule model. The sixth grade population included 197 English Language Learners (ELLs). One hundred eleven students, 56%, of sixth grade ELLs, were placed in the 90 minute consecutive math block schedule model, and 86 students, 44%, of the sixth grade ELLs, were placed in the 90 minute split math block schedule model.

The seventh grade target population consisted of 230 participants. One hundred students, 41%, were assigned to the 90-minute consecutive math block, and 130 students, 59%, were assigned to the 90 minute split math block model. The seventh grade special education population was composed of 27 special education students. Eleven students, 41%, were placed in the 90 minute consecutive math block schedule model. Sixteen, 59%, were placed in the 90 minute split math block schedule model. The seventh grade population included 97 English Language Learners (ELLs). Forty-five students, 46%, were placed in the 90 minute consecutive math block schedule model. Fifty-two, 54%, of the seventh grade ELLs were placed in the 90 minute split math block schedule model.

The eighth grade group was comprised of 205 eligible participants. One hundred four participants, 51%, were assigned to the 90-minute consecutive math block and 104 students, 49%, were assigned to the 90 minute split math block schedule. The eighth grade special education population was composed of 25 special education students. Thirteen students, 52%, were placed in the 90 minute consecutive math block schedule model. Twelve students, 48%, were placed in the 90 minute split math block schedule model. The eighth grade population included 66 English Language Learners (ELLs). Twenty nine students, 44% of eighth grade ELLs, were placed in the 90 minute consecutive math block schedule model. Thirty seven, 28%, were placed in the 90 minute split math block schedule model.

A total of 323 participants were assigned to the 90 minute consecutive math block and 337 participants were assigned to the 90 minute split math block model. From the total sample population of 85 Special Education students, 40 were assigned to the 90 minute consecutive math block and 45 special education students were assigned to the 90 minute split math block model. Of a total sample population of 359 English Language Learners, 188 were assigned to the 90 minute consecutive math block and 172 English Language Learners were assigned to the 90 minute split math block model.

Students were instructed by a total of 12 math teachers. Four math teachers were assigned to each grade level, and each grade level had two teams. Each team consisted of one Science teacher, one Language Arts teacher, one History teacher, one Reading teacher, and two Math teachers. One team in each grade level instructed the students using the consecutive block schedule and the other team used a split block schedule. Because students attended two math periods with the same teacher, each teacher serviced only 50 to 65 students. This would be opposed to its equivalent of 100 to 130 students on a traditional schedule. Several nonessential elective subjects were eliminated, and teaching slots were allocated for additional math teachers. Math teachers on the same team were given a common planning period to coordinate instructional activities. Weekly department meetings were scheduled to articulate the math curriculum in the sixth, seventh, and eighth grade levels. The average class size was 17 students per teacher, and the range was 12 to 18. The Texas Assessment of Knowledge and Skills (TAKS 2004 Release Test) was administered as a pretest on September 1, 2009 and again as a posttest on November 20, 2009.

Data for the dependent variable were collected via the Tango data analysis program, and the results were aggregated using the Microsoft Excel program. The data were disaggregated into subpopulations to identify Special Education and English Language Learners. The ANCOVA test from the Statistical Package for Social Sciences (SPSS) was used to determine if there were statistically significant differences between students in the 90 minute consecutive math block and the 90 minute split math block model.

Data Analysis

The null hypothesis was used to test the reverse of what the experimenter believed: There was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model.

By putting forward data to contradict the hypothesis, the researcher was able to test the validity of the null hypothesis. The procedure tested whether the differences in data were sufficient enough to establish statistically significant differences in order to reject or fail to reject the null hypothesis.

Three hypotheses were developed to determine the difference in academic achievement as measured by the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model. The first hypothesis encompassed all students in grades sixth, seventh, and eighth. The second hypothesis included all sixth, seventh, and eighth grade students in the special education program. The third hypothesis took into account all sixth, seventh, and eighth grade students in the English Language Learning program. Test scores were calculated and entered into SPSS as percentages.

*Null Hypothesis 1*

There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model.

An ANCOVA test was conducted to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model. The analysis indicated that there were statistically significant differences in student achievement between students in the 90 minute consecutive math block and the 90 minute split math block model.

A one way analysis of covariance (ANCOVA) was conducted on the first hypotheses to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between students in the 90 minute consecutive math block and the 90 minute split math block model. The factor, the type of block schedule, included two levels: consecutive block and split block. The dependent variable was students’ TAKS benchmark scores on a posttest and the covariate was students’ TAKS benchmark scores on a pretest.

Before conducting a One Way Analysis of Covariance (ANCOVA), a pretest was conducted to check if the data met the homogeneity-of-slopes assumption. The test evaluated the interaction between the covariate and the factors in the predictor of the dependent variable. The preliminary analysis evaluating the homogeneity-of-slopes assumption indicated that the relationship between the covariate and the dependent variables did not differ significantly as a function of the independent variable, *F*(1, 656) =.18, *p *= .647, partial η^{2 }= .00, therefore, the assumption for homogeneity of the slopes was met.

Table 4.2

*One-Way Analysis of Covariance Summary for*

*Texas Assessment of Knowledge and Skills benchmark test scores for all students in the 90 minute consecutive math block and the 90 minute split math block model.*

Source | Df | MS | F | Partial η^{2} |

01 | 1920.166 | 10.84** | .016 | |

Error | 657 | 177.08 | | |

Total | 660 | | |

*p*< .05

A One Way Analysis of Covariance (ANCOVA) test was conducted. Results of the main effect and the Covariate for a One-Way ANCOVA indicated that the One Way ANCOVA was significant; the group source evaluated the null hypothesis that the population adjusted means were equal. The results of the analysis indicated that the hypothesis should be rejected. Table 4.2 summarizes the results of the analysis for all sixth, seventh, and eighth grade students who took the Math Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) as a pretest on September 1, 2009 and as a posttest on November 30, 2009. There were statistically significant differences in academic achievement as measured by the 2004 Texas Assessment of Knowledge and Skills test between students in the 90 minute consecutive math block and the 90 minute split math block model. The ANCOVA was significant, *F*(1, 657) =10.84, *MSE *= 177.08 *p *< .01. The strength of the relationship between the type of block schedule, factor and the dependent variable was small as assessed by the partial η^{2}, with the block schedule group accounting for 2% of the variance of the dependent variable, holding constant the pretest TAKS benchmark score.

The mean of TAKS benchmark scores adjusted for the initial differences suggested a small effect size between the factor, type of block schedule, and the dependent variable, academic achievement as measured by the 2004 TAKS scores. The test adjusted means for the two groups were reported in the Estimated Marginal Mean box as 61.11 for the split block schedule group and 64.53 for the consecutive block schedule group. The mean of the consecutive block schedule students, adjusted for the initial differences, had the largest adjusted mean (*M* = 64.53), and the mean of the split block schedule students, adjusted for the initial differences, had a smaller adjusted mean (*M*=61.11)

*Null Hypothesis 2*

There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block Model.

An ANCOVA test was conducted to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model. Hypothesis 2 was to reveal if there were no statistically significant differences in special education student achievement between students in the 90 minute consecutive math block and the 90 minute split math block model.

A One way Analysis of Covariance (ANCOVA) was conducted on the second hypotheses to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between special education students in the 90 minute consecutive math block and the 90 minute split math block model. The factor, type of block schedule included two levels: consecutive block and split block. The dependent variable was students’ TAKS benchmark scores on a posttest and the covariate was students’ TAKS benchmark scores on a pretest.

Before conducting a One Way Analysis of Covariance (ANCOVA), a pretest was conducted to check if the data met the homogeneity-of-slopes assumption. The test evaluated the interaction between the covariate and the factors in the predictor of the dependent variable. The preliminary analysis evaluating the homogeneity-of-slopes assumption indicated that the relationship between the covariate and the dependent variables did not differ significantly as a function of the independent variable, *F*(1, 81) = 7.45, *p *= .008, partial η^{2 }= .08, therefore, the assumption for homogeneity of the slopes was not met. Because the assumption for homogeneity of the slopes was not met, a One Way ANCOVA was not appropriate for the special education group. Therefore, it was not conducted.

*Null Hypothesis 3*

There was no statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model.

An ANCOVA test was conducted to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between ELL (English Language Learner) students in the 90 minute consecutive math block and the 90 minute split math block model. Hypothesis 3 was to reveal if there were statistically significant differences in student achievement between ELL (English Language Learner) students in the 90 minute consecutive math block schedule and the 90 minute split math block schedule.

A One Way analysis of Covariance (ANCOVA) was conducted on the third hypotheses to determine if there was a statistically significant difference in the Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) scores between English Language Learning students in the 90 minute consecutive math block schedule and the 90 minute split math block schedule. The factor, type of block schedule included two levels: consecutive block and split block. The dependent variable was English Language Leaning students’ TAKS benchmark scores on a posttest and the covariate was students’ TAKS benchmark scores on a pretest.

Before conducting a One Way Analysis of Covariance (ANCOVA), a pretest was conducted to check if the data met the homogeneity-of-slopes assumption. The test evaluated the interaction between the covariate and the factors in the predictor of the dependent variable. The preliminary analysis evaluating the homogeneity-of-slopes assumption indicated that the relationship between the covariate and the dependent variables did not differ significantly as a function of the independent variable, *F*(1, 354) =.02, *p *= .886, partial η^{2 }= .00, therefore, the assumption for homogeneity of the slope was met.

*One-Way Analysis of Covariance Summary for*

*Texas Assessment of Knowledge and Skills benchmark test scores for all English Language Learners in the 90 minute consecutive math block and the 90 minute split math block model.*

Source | df | MS | F | Partial η^{2} |

01 | 3.74 | 0.021** | .016 | |

Error | 355 | 181.34 | | |

Total | 358 | | |

*p*< .05

A One Way Analysis of Covariance (ANCOVA) test was conducted. Results of the main effect and the covariate for a One-Way ANOVA indicated that the One-Way ANCOVA was significant; the group source evaluated the null hypothesis that the population adjusted means were equal. The results of the analysis indicated that that the hypothesis should be rejected. Table 4.3 summarizes the results of the analysis for all sixth, seventh, and eighth grade students who took the Math Texas Assessment of Knowledge and Skills benchmark test (2004 TAKS release) as a pretest on September 1, 2009 and as a posttest on November 30, 2009. There were no statistically significant differences in academic achievement as measured by the 2004 Texas Assessment of Knowledge and Skills test between English Language learning students in the 90 minute consecutive math block and the 90 minute split math block model. The ANCOVA was significant, *F *(1, 355) = 16.98, *MSE *= 180.84, *p *< .01.

The partial η^{2 }of 0.05 suggested a moderate relationship between the factor, type of block schedule, and the dependent variable, academic achievement as measured by the 2004 TAKS scores. The test adjusted means for the two groups were reported in the estimated marginal mean box as 63.37 for the split block schedule group and 57.49 for the consecutive block schedule group. The strength of the relationship between academic achievement and dependent variables was moderate, as assessed by a partial η^{2}, with consecutive block scheduling accounting for 5% of the variance of the dependent variable. The mean of the consecutive block schedule students, adjusted for the initial differences, had the largest adjusted mean (*M* = 63.37), and the mean of the split block schedule students, adjusted for the initial differences, had a smaller adjusted mean (*M* = 57.49).

Interpretation

The findings in this study supported the theoretical framework designed by J. Lloyds Trump and the guiding principle that giving students more time to learn could result in greater academic achievement. According to Trump’s idea, time allocation and period length was to be allotted according to the needs of the students (Canady & Rettig, 1995), (The Center for Education Reform, 1996). Based on the idea that different subjects had different levels of complexity and required different amounts of time for mastery, a ninety minute math schedule was created (Canady & Rettig, 1995). Two types of block schedules were created to address some of the major concerns about block scheduling. One major concern was that block scheduling had detrimental effects on student retention (Queen, 2002). Another major concern about block scheduling was that students with a short attention span may not benefit from block scheduling (The Center for Education Reform, 1996). “An adequate attention span is an important part of learning in a classroom setting, enabling children to organize and consolidate important features of the subjects being studied” (Gottfried, 2008, p. 1). Bennett (2008) asserted that students had a limited attention span of 30 to 45 minutes and Cooper’s (2001) contention that block scheduling may result in students reaching a saturation point at which learning capacity was diminished. To address these concerns, a consecutive and a split block schedule were created.

In the first hypothesis, which included all students, students in the 90 minute consecutive math block had a higher adjusted mean. For the second hypothesis, which included all special education students, the assumption for homogeneity of the slopes was not met. A One Way ANCOVA was not appropriate for the special education group. Therefore, it was not conducted. For the third hypothesis, which included all English Language Learners, students in the 90 minute consecutive math block had a higher adjusted mean. This research found that all students and English Language Learners students in the 90 minute consecutive block schedule had greater academic achievement than students in the 90 minute split block schedule.

Results Summary

Chapter 4 presents an analysis of the data of Math TAKS benchmarks scores between students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. The data was collected from two campus benchmark tests and consisted of the 2004 Math TAKS pretest and posttest. The data presented the independent variable as the type of block schedule, and the dependent variable as the Math TAKS benchmark test scores.

The three hypotheses analyzed included: the main group composed of all eligible students in the campus, and two subgroups, special education students and ELL (English Language Learners). All students in sixth, seventh, and eighth grades were divided into two groups. All students were assigned two 45 minute math periods. One group was instructed in a consecutive math block and the other group was instructed in a split math block. A pretest was given on September and a posttest was given on November. The data was entered into the Statistical Package for Social Sciences (SPSS) and analyzed using an ANCOVA procedure to determine if there were statistically significant differences in the student’s math TAKS benchmark posttest test scores.

For the first hypothesis, which included all students, the ANCOVAs determined that there were statistically significant differences in achievement as measured by the 2004 Math TAKS benchmark test between students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. Students in the 90 minute consecutive math block had a higher adjusted mean. For the second hypothesis, which included all special education students, the assumption for homogeneity of the slopes was not met; a One Way ANCOVA was not appropriate for the special education group. Therefore, it was not conducted. For the third hypothesis, which included all ELL students, the ANCOVA determined that there were statistically significant differences in achievement as measured by the 2004 Math TAKS benchmark test between students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. Students in the 90 minute consecutive math block had a higher adjusted mean.

This research found that there were significant differences in mean scores for TAKS Math benchmark scores between all students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. It also found that there were significant differences in mean scores for TAKS Math benchmark scores between ELL students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. The research was able to analyze special education students’ data. Schedule type had a significant effect on the scores for all students and ELL students for the Texas middle school researched in this study.

CHAPTER 5

SUMMARY, CONCLUSIONS, RECOMMENDATIONS

Analysis of Data Summary ConclusionsThis chapter interprets, examines, and qualifies the results of the investigation. The chapter reiterates the statement of the problem, methodology, null hypotheses, and findings. The final section of the chapter includes implications of the study, recommendations, and the summary.

This study was designed to investigate the effects of two types of block schedules on students’ academic achievement of a South Texas middle school in 2009-2010. One group of students was instructed using a consecutive block schedule system, and the other group of students was instructed using a split block schedule system.

The purpose of the study was to determine which type of block schedule had the greatest impact on students’ academic achievement as measured by the TAKS test. The information and data in the study were obtained via the administration of two benchmarks, 2004 TAKS release tests.

An ANCOVA statistical procedure was used to determine if there was a significant difference in student achievement on the Texas Assessment of Knowledge and Skills benchmark test between the split block schedule model and the consecutive block schedule model. This quantitative study examined the difference between scores of students in a split block scheduled group and scores of students in consecutive block scheduled group in the Texas Assessment of Knowledge and Skills benchmark test scores. The study analyzed if there was a difference in the TAKS benchmark tests between split block scheduling and consecutive block scheduling.

In the first hypothesis, which included all students, students in the 90 minute consecutive math block had a higher adjusted mean. For the second hypothesis, which included all special education students, the assumption for homogeneity of the slopes was not met; a One Way ANCOVA was not appropriate for the special education group. Therefore, it was not conducted. For the third hypothesis, which included all English Language Learners, students in the 90 minute consecutive math block had a higher adjusted mean. This research found that all students and English Language Learners students in the 90 minute consecutive block schedule had greater academic achievement than students in the 90 minute split block schedule.

Conclusions

The study concluded that students in the 90 minute consecutive math block had a higher adjusted mean. For all special education students, the study concluded that the assumption for homogeneity of the slopes was not met. A One Way ANCOVA was not appropriate for the special education group. Therefore, it was not conducted. For all English Language Learners, the study concluded that students in the 90 minute consecutive math block had a higher adjusted mean.

The results of the study demonstrated that for the group of all students and for English Language Learners, the 90 minute consecutive block schedule had greater academic achievement than students in the 90 minute split block schedule.

Findings of the study suggest that type block scheduling was statistically important for the all students group and for the English Language Learning students in the area of mathematics when attempting to improve students’ academic achievement. The study did not control for student schedule changes, variations in teachers’ experience, differences in teachers’ strategies, and other factors beyond the researcher’s knowledge and control that improved students’ TAKS benchmark scores.

Contributions to Literature

This study added to the current body of knowledge on block scheduling. While many studies have been conducted on the impacts of block scheduling, few studies have evaluated the impact of time allocation. Most studies that have been conducted on block scheduling models, such as A/B and 4X4, concentrated on rearrangement of time without adding instructional time (Canady, R. L., & Rettig, M. D. 1995), (Rettig, M. & Canady, R. 2000), (Bennett, K. J. (2008).

This study examined the impact that a 90 minute math block schedule had on the academic achievement of students at a South Texas middle school. The study was conducted on a block scheduling model that added time to the instructional day. The study identified whether a difference existed in mathematical academic achievement between students who were scheduled on a two period consecutive block and students who were scheduled on a split block. The study contributed to the literature by providing a basic blueprint for other schools to follow because findings of this study can be used as a baseline for other middle schools with similar demographic populations in the district, region, or state.

Schools administrators looking for alternatives to traditional scheduling can take this study into consideration, examine and evaluate the result, and make decisions regarding applicability of this type of block scheduling to their individual situation. The study makes available statistics to teachers and administrators on the impact of the 90 minute consecutive math block and the 90 minute split math block model. Based on this information, counselors, curriculum and instruction supervisors can make decisions as to what type of block scheduling best benefits student achievement. The concept of block scheduling has been extensively explored and widely used by many school districts (Northwest Regional Educational Laboratory, 2001). While this study did not provide conclusive evidence as to the effects of the 90 minute consecutive math block and the 90 minute split math block model, it provided a framework for further studies.

Recommendations

Findings revealed in this study demonstrated the impact of block scheduling on student achievement. The findings in this study suggested that consecutive block scheduling had a greater impact on student achievement than split block scheduling.1. Adding instructional time to math classes improves student achievement. The current year’s Math benchmark scores for all students were significantly higher than the previous year’s benchmark scores.2. Students in consecutive block scheduling have a greater academic achievement than those in split block scheduling. 3. English Language Learners in consecutive block scheduling have a greater academic achievement than those in split block scheduling. 4. The ANCOVA was unable to determine the impact of consecutive block scheduling and split block scheduling for special education students. However, the current year’s benchmark scores were scientifically higher than the previous year’s benchmark scores for special education students.5. When creating block schedules, priority should be given to students with the low academic scores because they have the greatest need and may benefit the most.Further research is needed in the area of consecutive block scheduling to ascertain apparent benefits of consecutive block scheduling.

SummaryThe data for this study was collected from one South Texas middle school. The participants in this study were students from sixth, seventh, and eighth grade. The school involved in the study was composed of 660 students: 220 sixth graders, 220 seventh graders, and 220 eighth graders. The only data that was aggregated was the students who participated in the pretest and posttest. Students’ academic achievement was measured by the 2004 TAKS benchmark test. The instruments consisted of a sixth grade 45 item test, a seventh grade 48 item test, and an eighth grade 50 item test. The purpose of the study was to provide school administrators the necessary data to determine the type of block model that would be most beneficial for students.

Review of the literature explained the trends in education. In 1892, after the National Education Association’s Committee of Ten called for a uniform high school structure that included time allotment, the American Modern Education Reform began (Taylor, 1894). The Carnegie Unit then established what is known today as 8 period schedules which provided structure, time and treatment allotments to the educational system. This became a groundbreaking movement, as the Carnegie Unit was adopted by most colleges, high schools, junior high schools, and even some elementary schools and was subsequently used for the next 100 years (The Carnegie Foundation for the Advancement of Teaching, 2007). By the 1950’s, schools began to realize that the Carnegie unit did not meet the needs of at-risk students and special populations. In response to this, most junior high schools implemented the middle school concept and many high schools experimented with block scheduling. The first middle schools were created in 1950’s with the intent of creating schools that would better meet the developmental needs of the students through smaller learning teams, advisory classes, and interdisciplinary teaching and learning (Banks, 2003). In an effort to address some of the shortcomings of the Carnegie Unit, William Alexander adopted the middle school concept in 1950 (Anfara, Andrews, & Mertens, 2005). Most junior highs schools were converted to middle schools by the 1990’s.

At around the same time, many high schools experimented with block scheduling. J. Lloyd Trump is credited with developing the first flexible block schedule in 1959 (Canady & Rettig, 1995; Queen, 2002). Trump attempted to use block scheduling for the same reasons that junior high schools adopted the middle school concept. The schedule was to be built based on each individual student’s needs. Some classes would be longer than others depending on the complexity of the subject and the needs of the students (Canady & Rettig, 1995). By 1960, Joseph Carroll, pilot tested the Copernican Plan which restructured schedules to enable students to focus on a limited number of subjects per semester (Cromwell, 1997; Crushman, 1995; Mell, 2007; Queen, 2007). Soon after, different block scheduling models which included the 4X4 Block, Alternating Block, and Modified Block schedules were developed and implemented by different schools in the United States. Block scheduling was tried for a few years, but the results of these trials were inconclusive. While many areas in education improved such as morale, discipline, attendance, grades and student-teacher relationships, there was no conclusive evidence that block scheduling improved academic achievement (Bennett, 2008). The major draw back of most block scheduling models was that they do not follow up on the original concept by J. Lloyd Trump and Joseph Carroll. They originally intended for their concept to create some shorter classes and some longer classes, but schools simply reorganized time to block without following through. The schedule was not built around students’ needs, and no additional time was allocated for more complex subjects.

Descriptive and inferential analysis (ANCOVA) for each question was conducted to determine the impact of split block scheduling on TAKS scores and to determine which of the two types had the greatest impact on the students’ performance. The scores of each variable were compared between the groups using ANCOVA to evaluate if there were statistical differences between consecutive block scheduling and split block scheduling in students’ TAKS benchmark scores. The schools’ 700 students were divided into two groups, and each group had approximately the same number of students and aptitudes. The quasi-experimental study collected TAKS benchmark scores over three months through Tango and Microsoft Excel. SPSS (Statistical Package for the Social Sciences) software was used to analyze the data collected. An alpha level of .05 was used to determine significance.The results chapter presented an analysis of the data of Math TAKS benchmark scores between students in a 90 minute consecutive math block and a 90 minute split math block. The data was collected from two campus benchmark tests and consisted of the 2004 Math TAKS pretest and posttest. The data presented the independent variable as the type of block schedule, and the dependent variable as the Math TAKS benchmark test scores.

The three hypotheses that were analyzed included: the main group composed of all eligible students in the campus, and two subgroups, which were the special education students and ELL (English Language Learners). All students in sixth, seventh, and eighth grade were divided into two groups and assigned two 45 minute math periods. One group was instructed in a consecutive math block and the other group was instructed in a split math block. A pretest was given in September and a posttest was given in November. The data was entered into the Statistical Package for Social Sciences (SPSS) and analyzed using an ANCOVA procedure which determined if there were statistically significant differences in the students’ math TAKS benchmark posttest test scores.

For the first hypothesis, which included all students, the ANCOVA determined that there were statistically significant differences in achievement as measured by the 2004 Math TAKS benchmark test. The ANCOVA took into account the difference between students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. Students in the 90 minute consecutive math block had a higher adjusted mean than their counterparts. For the second hypothesis, which included all special education students, the assumption for homogeneity of the slopes was not met. A One Way ANCOVA was not appropriate for the special education group, consequently it was not conducted. For the third hypothesis, which included all ELL students, the ANCOVA found there were statistically significant differences in achievement as measured by the 2004 Math TAKS benchmark test between students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. Students in the 90 minute consecutive math block had a higher adjusted average.

This research found there were significant differences in mean scores for TAKS Math benchmark scores between all students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. It also found there were significant differences in mean scores for TAKS Math benchmark scores between ELL students in a 90 minute consecutive math block schedule and a 90 minute split math block schedule. The research was able to analyze special education students’ data, and concluded that schedule type had a significant effect on the scores for all students and ELL students for the Texas middle school used in this study.