“Bridging the Digital Divide and Increasing CRCT Scores

“Bridging the Digital Divide and Increasing CRCT Scores

Through Computer Based Online Tutorials and Internet Access”

Deana L. Shade

Augusta State University

Abstract

This study evaluated the effects of the Catapult Online Tutorial program on students’ academic performance on the Criterion Referenced Competency Test (CRCT) for Louisville Middle School students. Utilizing a Non-Equivalent Group Design, this study examined the relationship between students’ academic performance and computer internet access. To examine the effect of the Catapult program in improving students’ academic performance, paired samples t-tests and One Way Analysis of Variance were conducted for each of the components of the measures of academic performances (Reading and Math). The study revealed students who participated in the Catapult Online tutorial Program had increases on the standardized CRCT in the content area of Math but not Reading.

No Child Left Behind

On January 8, 2002, President Bush signed the No Child Left Behind Act (NCLB) of

2001, which reauthorized the Elementary and Secondary Education Act (ESEA). A key aim of the federal NCLB Act of 2001 is to provide new educational options to parents whose children attend Title I schools that are identified for improvement, corrective action, or restructuring because the school did not make adequate yearly progress (AYP) toward meeting state standards

for two or more years (U.S. Department of Education, 2007). The NCLB Act of 2001 is the

most recent reauthorization of ESEA. NCLB raises expectations for states, local school districts,

and schools in that all students are expected to meet or exceed state standards in reading and mathematics within 12 years (Georgia Department of Education, 2007). NCLB requires all states, including the state of Georgia, to establish state academic standards and a state testing systems that meet federal requirements (Georgia Department of Education, 2007). Under NCLB, all students must meet Georgia’s proficient level of academic achievement by 2013-2014 (U.S.

Department of Education, 2007).

As part of the NCLB Act of 2001, the Enhancing Education through Technology (ED Tech) program was introduced. The ED Tech programs seeks to improve student academic achievement in elementary and secondary schools through technology by helping students to become technically literate by the eighth grade and to ensure that teachers integrate technology into the curriculum to improve student achievement (Judge, Puckett, & Bell, 2006). More recent reports on the use of computers for instruction are beginning to demonstrate evidence of direct relationships between computer use and academic achievement (Brush, Armstrong, Barbrow, & Ulintz, 1999; Coley, Cradler, & Engel, 1998; Wenglinsky, 1998).

Supplemental educational services such as tutoring, remediation and other educational interventions designed to increase the academic achievement of students in low-performing schools in reading, and math are provided outside of the regular school day. The supplemental services are designed to increase academic performance in Reading and Math. The supplemental services are available to low-income families whose children attend a Title I school that are in at least the second years of being identified for needs improvement status (Georgia Department of Education, 2007). One of Louisville Middle School’s responses to the requirements of the provision of supplemental educational services is the Catapult Online Tutorial program.

Catapult Online

The Catapult Online tutorial program was first introduced to Louisville Middle School (LMS) by Dr. Pamela Bell-Smith, through the Central Savannah River Area Regional Educational Service Agency (CSRA RESA) during the 2004-2005 academic school year (Personal Communication with LMS Principal Samuel Dasher, December 7, 2006). The CSRA RESA is a state affiliated agency which provides direct services to school systems in a 12 county area, inclusive of Jefferson County (CSRA RESA, 2006). Catapult Online is an at-home tutoring program designed to provide students with the supplemental educational services component of NCLB. The purpose of Catapult Online is to boost reading and math skills for students in grades 3-12. The tutorials are delivered over the Internet, direct to students’ homes, on a computer provided free of charge by Catapult Online (Catapult Learning, 2006).

Purpose and Significance

The effects of the Catapult Online Tutorial Program on the academic performance of students from LMS have not been evaluated and so its effectiveness remains unknown. The purpose of this study is to determine if the Criterion-Referenced Competency Test (CRCT) standardized test scores of LMS students increase as a result of the receipt of Catapult Online supplemental educational services. This is significant because if there are increases in standardized test scores as a result of the Catapult Online Tutorial Program, then this internet tutorial program should be made accessible to the entire student body at LMS instead of the current coverage of only 38 (eight percent of) students. If the CRCT standardized test scores of LMS students do not increase as a result of the receipt of Catapult Online supplemental educational services, then recommendations will be made to the administration with regard to seeking alternative methods of fulfilling the supplemental educational services requirement.

Hypotheses

This research is motivated by the need to determine the effectiveness or otherwise of the Catapult Online program in improving students’ academic performance. It is believed that this study, among other things, will help program administrators to improve the program delivery and/or expand the program coverage. This is important considering that the effect of the Catapult Online program on the academic performance of LMS students has not been determined. Findings from past studies have indicated that technology has positive effects on education and students’ achievement. Based on these, it is expected that the Catapult Online program will improve student’s academic performance. Specifically, this researcher hypothesizes that:

H1: Students who participate in the Catapult Online Tutorial Program will experience greater improved academic performance than the control group who neither participated in the Catapult Online tutorial nor had home internet access and students who reported having home internet access.

H2: Students who participate in the Catapult Online Tutorial program will demonstrate greater differences between the mean CRCT pretest scores and the mean CRCT post test scores than both the comparable group who neither participated in the Catapult Online Tutorial program nor had home internet access and the comparable students who reported having home internet access.

Background

Louisville Middle School (LMS) is located in Louisville, Jefferson County, Georgia. Jefferson County is a rural community located approximately 30 miles south of Augusta,

Richmond County, Georgia. According to the 2005 Census Bureau quoted by the Jefferson

County Board of Education (2006), the estimated population for Jefferson County was 16,926.

The per capita income for 2004 was $21,117 and the unemployment rate for the same period was 8.3 percent, compared to 5.1 percent for the entire state of Georgia that same year (Jefferson County Board of Education, 2006). In 1995, Wrens High School and Louisville High School consolidated to form Jefferson County High School. At that time, the Louisville campus began to house 6th-8th graders and the name was changed to LMS (Jefferson County Board of Education, 2006). According to the Jefferson County Board of Education, LMS has approximately 430 students in grades six through eight. In addition, LMS has an almost 90 percent minority student population with almost the same percentage qualifying for free or reduced lunch. This is significant because qualification for school meal benefits requires that students live in a household whose combined family size and annual income is at or below the poverty level. This suggests the majority of the students in LMS are from households living at or below the national poverty levels. Prior to the 2005-2006 academic school year, LMS had not met Adequate Yearly Progress (AYP) since its inception in 1995, and therefore met the criteria requiring that options for supplemental educational services are made available to the students attending LMS.

Literature Review

The Digital Divide

The digital divide is the term coined to describe the disparity that exists between the minority of people with regular, effective access to digital technologies and those without (Hawkins, 2005). The concept of a digital divide was developed by the U.S. National Telecommunications and Information Administration (NTIA) in the series “Falling through the Net” to represent the unequal diffusion of information and communication technology in our information age (Hawkins, 2005). In the mid- 1990’s, the NTIA popularized the term digital divide to describe the societal split between those with and those without access to computers and the Internet (Warschauer, 2003). In an effort to bridge this gap, an influx of tax dollars, corporate money, and charitable efforts went into bringing hardware, software, and internet connection to all schools. However, equipment and connections are only part of the problem of the digital divide. For students and teachers to take full advantage of the digital revolution in teaching and learning, they must know how to use the tools and have unfettered access to them (Vail, 2003). Vail has also noted that, increasingly, the technology gap between poor and rich children is not in school access but in the bigger issues of home access, instruction and content.

There are three threads that consistently characterize the digital divide phenomena. The first thread is physical access which refers to one’s ability to access information communication technology (ICT), that is, where does one access a computer. Second, one’s geographic location, that is, residing in a rural community dictates one’s ICT access. In rural areas, infrastructures that would allow ICT access may be limited or nonexistent. Evidence suggests the community of origin (urban, rural, or suburban) impacts digital access with rural areas having less internet access than urban areas (U.S. Department of Commerce, 2004; Wilson, Walin & Reiser, 2003; Kastsinas & Moeck, 2002). Cable modem service may not extend to remote customers, who often do not have cable system infrastructures available to their homes and schools. Additionally, the costs related to the building of out cable modem service are higher in rural and remote areas, where the subscriber base is low (U.S. Department of Commerce, 2004; Wilson et al., 2003; Kastsinas & Moeck, 2002). The last thread is two fold and refers to the relationship between socioeconomic conditions and internet connectivity. Specifically, economic advantage is correlated with the ability to access information and communication technology (Warschauer, 2003).

Using the U.S. Census Bureau’s Current Population Survey of 57,000 households containing 134,000 persons, the U. S. Department of Commerce found that the proportion of U.S. household with computers reached 61.8 percent in 2003, and 87.6 percent of those households used their computers to access the Internet. Also, 54.6 percent of U.S. household had Internet connections. With regard to Internet use, ease of access is a fundamental issue, but it is not the sole factor. Effective access also depends on ability to use ICT effectively, and on the quality of digital content that is available and can be provided. The quality of connection, auxiliary services and other factors that affect effective use are also important (U.S. Department of Commerce, 2004).

Digital equity is a social justice goal that seeks to ensure all students have access to information and communication technologies for learning, regardless of socioeconomic status (SES), disability, language, race, gender, or any characteristics that have been linked with unequal treatment (Judge et al., 2006). For students without physical access to computers, the problem is not simply that they are unable to manually operate computers, but it also involves the lack of a set of sophisticated academic or social competencies required to participate effectively (Street, 1998) and to navigate the broader information society (Czerniewicz, 2004). Equitable access to technology resources (e.g., computers, software, and connectivity) is one aspect of the concern for digital equity. Other dimensions include effective use of technology for teaching and learning; access to high quality and culturally relevant content, and opportunities to create new content (National Institute for Community Innovations, 2003).

Social Economic Status and Race

Computer and internet access varies between different ethnic and racial groups. The digital divide particularly affects students who are African American, Hispanic, Native American, and the poor (U.S. Department of Commerce, 2000). In August 2000, 56.8 percent of Asian Americans and Pacific Islander households had internet access and 46.1 percent of White households had internet access. This compares to 23.5 percent for African American households and 23.6 percent for Hispanic households (U.S. Department of Commerce, 2000; Lindsay & Poindexter, 2003). According to a “A Nation Online,” the last major federal study on the subject published in 2004, Caucasian and Asian-American households were more likely to be online than African-American households (Kastsinas & Moeck, 2002). The report also revealed that more than 80 percent of households earning more than $70,000 annually are online, compared to barely 30 percent of households earning less than $15,000 annually.

Hess and Leal (2001) found that there are still race inequities in providing schools with computers. Schools with higher percentages of Black students have less access than White students. They also reported that school districts’ spending had an impact on access to classroom technology, with higher-income districts providing somewhat more classroom technology.

Technology in Education

DeBell and Chapman (2003) reported that in 2001, more children and adolescents used computers at school (81%) than at home (65%). Despite the fact that schools across the country achieved near parity in availability and quality of access, evidence shows continued significant disparities across different groups of children in terms of computer and internet use (Becker, 2000; DeBell & Chapman, 2003; Fairlie, 2002; Puma, Chapin, & Pape, 2003; Solomon, 2002). For example, students in schools with the highest poverty concentrations used computers more frequently than did students in schools with low poverty concentrations. However, computer use was not associated with academic gains for students from high poverty schools i.e., larger numbers of students had to use a smaller number of available computers (Becker, 2000; Norris, Sullivan, Poirot, & Soloway, 2003; Swain & Pearson, 2002; Wenglinksy, 1998). Most children and adolescents use the computer primarily for recreational purposes such as playing games, E-mail, and listening to music, rather than for academic learning (Becker, 2000; Giacquinta & Lane, 1990; Kafai & Sutton, 1999). A Gallup Poll (1997) found that a higher percentage of low-income youth used the computer to play video games daily, compared to their wealthier peers. Other research suggests that socioeconomically disadvantaged youth would be less likely to use internet technology (IT) for academically productive purposes because their parents are less able to provide educational software, computer hardware, technical assistance, and supervision, compared to wealthier parents (Attewell & Battle, 1999; Becker, 2000; Giacquinta & Lane, 1990). A similar argument has been applied to low-resource schools, to which poor and minority youth are more likely to attend. Low teacher-student ratios, outdated technology, and teachers with few IT skills, factors that are associated with low-resource schools, would likely result in low levels of supervision and unproductive educational uses of IT (Becker, 2000; Ryan, 1991; Wenglinsky, 1998). Cattagni and Westat (2001), reporting information from the National Center for Education Statistics, found that schools with the highest concentration of poverty had approximately 16 students per instructional computer with Internet access, compared to 7 among schools with the lowest concentrations of poverty. In addition, 54 percent of public elementary and secondary schools provide students Internet access outside regular school hours. Public schools with high minority enrollments reported Internet availability outside of regular school hours more frequently than schools with the lowest minority enrollment (61% compared with 46%). Of the 54 percent that made Internet available outside regular school hours, 98 percent made it available after school, 94 percent before school, and 16 percent on weekends (Cattagni & Westat, 2007).

Computer Technology and Student Achievement

In a 2000 study commissioned by the Software and Information Industry Association, Sivin-Kachala and Bialo (1999) reviewed 311 research studies on the effectiveness of technology on student achievement. Their findings revealed positive and consistent patterns when students were engaged in technology-rich environments, including significant gains and achievement in all subject areas, increased achievement in preschool through high school for both regular and special needs students, and improved attitudes toward learning and increased self-esteem.

In a research project presented to the Shawnee Mission Board of Education, LaVergne (2007) sought to determine if the use of the ALEKS Web-Based Learning System would have an impact on the standardized math scores of students in Algebra 1A. ALEKS is a program accessed online that serves as an interactive tutor for math students, in much the same way as the Catapult Online Tutorial program. According to LaVergne (2007), all Algebra 1A students were required to take the Measures of Academic Progress (MAP) test two times per year and the MAP Test taken in 2006 served as the pretest score for comparison with the MAP Test taken in 2007. LaVergne (2007) deduced, based on data collected from the MAP Test, the ALEKS program significantly and positively impacted students’ standardized test scores. The district average for improvement over the same period of time was 1.0 points and the national average over that same period of time from the previous year (2005) was 1.6 points

In examining large-scale state and national studies, as well as some innovative smaller studies on newer educational technologies, Schacter (1999) found that students with access to any of a number of technologies (such as computer assisted instruction, integrated learning systems, simulations and software that teaches higher order thinking, collaborative networked technologies, or design and programming technologies) show positive gains in achievement on researcher constructed tests, standardized tests, and national tests. In their meta-analysis review of research conducted between 1993 and 2000 on the effectiveness of discrete educational software (DES) programs, Murphy, Klemz, Young, and Penuel (2003) found evidence of a positive association between use of DES products and student achievement in reading and mathematics, an association consistent with earlier reviews of the research literature on the effectiveness of computer-based instruction (Kulik & Kulik, 1991; Kulik, 1994; Fletcher-Flinn & Gravatt, 1995; Ryan, 1991).

Middle and high school students in Georgia that used an interactive software system to learn pre-algebra and algebra scored significantly higher on standardized state mathematics tests than students in traditional classrooms. Designed for at-risk, academically disadvantaged students, the 326-lesson curriculum covered basic mathematics through advanced algebra concepts (Kirby, 2004).

O'Dwyer, Russell, Bebell, and Tucker-Seeley (2005) found that controlling for both prior achievement and socioeconomic status, fourth-grade students who reported greater frequency of technology use at school to edit papers were likely to have higher total English/Language Arts test scores and higher writing scores on fourth grade test scores on the Massachusetts Comprehensive Assessment System (MCAS) English/Language Arts test. Michigan's Freedom to Learn (FTL) initiative, an effort to provide middle school students and teachers with access to wireless laptop computers, has been credited with improving grades, motivation and discipline in classrooms across the state. One exemplary school examined reading proficiency scores on the Michigan Education Assessment Program (MEAP) test, administered in January 2005 and reported increases from 29 percent to 41 percent for seventh graders and increases from 31 to 63 percent for eighth graders (Bennett, 2002).

Research Methodology

As stated previously, the effects of the Catapult Online Tutorial Program on the academic performance of students from LMS had not been evaluated and so its effectiveness remained unknown. The purpose of this study was to determine if the CRCT standardized test scores of LMS students increase as a result of the receipt of Catapult Online supplemental educational services. It was expected that the Catapult Online Program would result in increased CRCT scores, and these findings could be generalized to the entire LMS student body and possibly to the entire student population of the Jefferson County school system.

Study Design

The Non-Equivalent Groups Design (NEGD) was used for this study. NEGD is probably the most frequently used design in social research. According to the United States General Accounting Office (1991), classic experiments are not always feasible in social research, especially when it involves the study of actual programs, service delivery, treatments, etc., as they are being administered in the real world. This is especially the case when it is difficult or impossible to randomly assign clients and create equivalent groups. Classic randomized experiments are also problematic where there are ethical issues with regard to deciding who should or should not get access to a service. Also, when data has to be analyzed on the basis of existing archival information, it may be impossible to randomize subjects, and pretest data may be absent.

One weakness of the NEGD is that the treatment and comparison groups are not randomly assigned; therefore, it is usually difficult to accurately attribute observed differences to the effects of the treatment. In other words, the groups might differ with regard to other factors that affect the difference in outcome, so that the observed difference should be adjusted to compensate for the lack of equivalence between the groups.

Despite the weaknesses of the NEGD, it was ideal for this study considering that participation in the Catapult Online program did not permit the opportunity for a randomized experiment. Catapult Online was already being implemented and the students were not randomly assigned. The selection of students for participation in the Catapult Online tutorial program was based on academic need, so a randomized experiment would have been difficult to use even if evaluation was planned as part of the design before implementation of the tutorial program.

The NEGD provides the opportunity to match groups closely around important characteristics such as gender, race, and social economic status, and allowing differences that exist to be revealed and factored into analysis (Steinberg, 2004). This helps improve on the NEGD and its ability in inferring causality. The process involved for selecting Catapult Online tutorial candidates was based on academic need, so matched groups were used for comparisons. In selecting students for the Catapult Online Program, each homeroom teacher was asked by the LMS principals, to identify two students from each homeroom class, whom the teacher felt would benefit from the online tutorials. The only criterion was for the nominated students to have an active telephone line in the home for internet accessibility.

The treatment group for this study consisted of students who participated in the Catapult Online tutorial program and the comparable group consisted of students who did not participate in the Catapult Online Program. Considering the possibility that access to computer and/or internet might affect students’ performance and possibly contaminate the effect of the Catapult Online program, student access to computer and/or internet (other than the Catapult Online program) was controlled in this study. This was achieved by including in the study another group of students who did not participate in the Catapult Online program but had access to computer internet access at home. In effect, this study consisted of a treatment group and two comparable groups. One of the comparable groups consisted of students who had home computer internet access but did not participate in the Catapult Online tutorials, and the other comparable group which neither participated in the online tutorials nor had home computer internet access.

To improve on the design of the study and the ability to attribute changes in students’ academic performance to the catapult online program, the groups were matched based on demographic factors identified in the literature as having the greatest influence on academic performance. Using secondary data from the LMS Schools Administrative Student Information system, the students were matched using a portion of those demographic factors: grade level, sex, race, and socioeconomic level.

Livingston and Livingston (2003) found that, in the state of Georgia, African American children trailed the state average in the Reading component of the CRCT, in 122 of 159 county school districts analyzed. In the 140 counties in which African Americans reside in Georgia, African American children in 120 of these counties fell farther behind white children, academically, over the three years the study was conducted. Furthermore, when socioeconomic data was paired with CRCT test scores, the primary determinates of sixth grade CRCT Reading failure were children living in poverty, having unwed mothers which contributed to poverty status, and being a racial minority. With regard to sixth grade Math CRCT scores, they found a correlation between socioeconomics, race, and failing the Math portion of the CRCT. They also found that of the 159 counties analyzed, 50 percent of students who resided in 15 of the poorest counties in the state, failed. More specifically, an average of 29 percent of the white students failed compared to a mean of 55 percent of those who attended predominately African American schools (Livingston and Livingston, 2003).

Sample

The population of interest for this study consisted of middle school students at LMS. The population that was accessible for this study was all LMS students who 1) had a record of standardized testing data for the Georgia CRCT; 2) were enrolled at LMS; and 3) participated in the Catapult Online Tutorial program during the 2005-2006 and 2006-2007 academic school years; or 4) had not participated in the Catapult Online Tutorial program but had home internet access; or 5) had not participated in the Catapult Online Tutorial program nor had home internet access.

The sampling frame was obtained from academic records maintained by the Jefferson County Board of Education. A list was obtained of all LMS students who received a Catapult Online Computer and participated in the Catapult Online tutorial program during the 2005-2006 and 2006-2007 academic school years.

Next, a questionnaire was distributed to the six connections teachers at LMS for the purpose of obtaining information on students who have home internet access. Connections teachers are the teachers who support content area subject matter with additional and more detailed instruction in other areas such as Science, Math, Language Art, Business, Computer Technology, Physical Education, and Band. The questionnaire basically asked if students had computer internet access in their homes, each student’s full name, race, sex, and grade level. The questionnaire was distributed to these six teachers to administer because they come in contact with the entire LMS student body on a daily basis; and the small number of teachers allowed for ease of administrative control and assured responses from students.

The researcher then created comparable groups that were matched exactly, according to the demographic characteristics (race, gender, grade level, and socioeconomic status) of the treatment group, based on the student information obtained from the questionnaire and LMS student records. For the purposes of this research, the criterion for the determination of socioeconomic status was qualification for free or reduced lunch. As stated previously, qualification for school meal benefits requires students live in a household whose combined family size and annual income is at or below the poverty level. The total number of students (n) included in the sample was 111.

Measurement of Variables

The dependent variable was academic performance and was measured by mean CRCT scores of students. The dependent variable was measured for Reading and Math for all the students in the study before and after the receipt of the Catapult Online program; pre- and post tests respectively. For the purposes of this research, the pretest for all three groups was the CRCT standardized test scores from the previous school year for each student. For instance, those students who received Catapult computers during the 2005-2006 academic school year, had their CRCT scores from the 2004-2005 school year used as pretest data. Conversely, the post-test for the treatment group and both comparable groups, consisted of CRCT scores from the academic school year immediately following the pretest school year for each student.

The independent variable was measured by students’ exposure to different treatment conditions, namely the Catapult Online tutorial program for the treatment group, home computer internet access for the comparable group and neither Catapult Online tutorial nor home computer access for the comparable control group.

Procedure

Secondary data from CRCT standardized testing scores was accessed and analyzed.

Standardized test scores were examined for students who participated in the Catapult Online tutorials (treatment group) and compared to standardized test scores for students with home computer internet access and the scores for students who received neither Catapult Online tutorials nor home computer internet access (the comparable groups).

First, the relationship of the pretest and post test of standardized test scores for only those students who received Catapult Online tutorials needed to be examined for baseline data. Next, a mean comparison was done of all pretest groups before doing a comparison of all three post test groups. The mean scores of the three groups were examined. This research determined which comparable group means were significantly different from the treatment group mean. Means testing was used to uncover the main effects of the independent variable and the comparable groups (Catapult Online tutorial, Internet access and neither Catapult Online tutorial nor Internet access) on a dependent variable (CRCT mean scores). Descriptive statistics were also calculated and the Statistical Package for the Social Sciences (SPSS) was used for all analyses.

Results and Discussion

Descriptive Findings

The independent variable for the treatment group was the Catapult Online Tutorial program. One comparable group’s treatment condition was home internet access, and another comparable control group’s treatment condition was participation in neither Catapult Online nor home internet access. The Catapult Online treatment group contained exactly 33.3 percent of the sample, as did the comparison group with home internet access and the comparable control group with neither. The Catapult Online treatment group consisted of 37 students, as did both comparable groups. Frequencies were conducted to investigate possible distribution imbalances in gender, race, grade level and socioeconomic status. The treatment group and both comparable groups contained 19 females and 18 males each. The treatment group and both comparable groups contained 17 sixth grader students, 19 seventh grader students, and one eighth grade student each. With regard to race, the treatment group and both comparable groups each contained 34 black students, one white student, one Hispanic students and one biracial student. Finally, for the purposes of identifying and categorizing socioeconomic status, the treatment group and both comparable groups each contained 29 students who received free lunch, four students who received reduced lunch, and four students who were not eligible to receive school meal benefits. Because the groups were matched, there was no imbalance and there were no missing values.

Participant Demographic Characteristics

Table 1

Grade Level and Internet Access Distribution

% of Total

Seventh Grade

% of Total

Eighth Grade

% of Total

			Internet Access			Total
			Catapult Online	Home Internet Access	Neither Catapult Online nor Home Internet Access	Total
Grade Level
	Sixth Grade	Count	17	17	17	51
	Sixth Grade		15.3%	15.3%	15.3%	45.9%
		Count	19	19	19	57
			17.1%	17.1%	17.1%	51.4%
		Count	1	1	1	3
		.9%	.9%	.9%	2.7%
Total		Count	37	37	37	111
Total			33.3%	33.3%	33.3%	100.0%

Table 1 shows the frequency and equal distribution of matched groups by grade level and among the treatment and comparable groups. The majority of the students in the sample were in the sixth and seventh grades. Fifty one students (45.9%) were in the 6th grade, 57 students (51.4%) were in the 7th grade, and the remaining three students (2.7%) were in the 8th grade. There was only one eighth grade student in the treatment group and subsequently only one eighth grade student in each of the comparable groups.

Figure 1

Racial Frequencies Chart

As stated previously, LMS has an almost 90 percent minority student population with almost the same percentage qualifying for free or reduced lunch. The Racial Frequencies Chart in Figure 1 demonstrates how the research sample approximates the demographics of the school with 103 Black students (92.8%) and White, Hispanic and the other racial group making up the remaining eight students (7.2% of the sample).

Figure 2

Socioeconomic Status Frequency Chart

According to the Socioeconomic Status Frequency Chart in Figure 2, 78.4 percent (87 students) in the sample receive free lunch with an additional 12.6 percent (14 students) qualifying for reduced lunch benefits. In contrast to the larger LMS student population, White students are not represented in the “not eligible” category. Additionally, Black students in the sample account for 94.3 percent of students who qualify for free lunch and 85.7 percent of student who qualify for reduced lunch.

Table 2

Mean Score Data of Independent Variable Groupings by Content Area

		Mean Scores	Minimum CRCT Scores	Maximum CRCT Scores	Std. Deviation	Std. Error Mean
Catapult Online Reading	Pretest Mean Post Test Mean	802.70 801.54	763 769	850 839	22.41 18.25	3.68 2.99
Catapult Online Math	Pretest Mean	796.68	753	827	17.83	2.93
Catapult Online Math	Post Test Mean	797.30	755	843	22.29	3.67
Home Internet Reading	Pretest Mean	811.30	756	856	26.25	4.32
Home Internet Reading	Post Test Mean	815.08	763	854	22.59	3.71
Home Internet Math	Pretest Mean	811.30	759	867	24.27	3.99
Home Internet Math	Post Test Mean	814.04	755	923	33.40	5.49
Neither Catapult Online nor Home Internet Reading	Pretest Mean	809.59	775	874	21.36	3.51
Neither Catapult Online nor Home Internet Reading	Post Test Mean	816.16	779	865	18.47	3.04
Neither Catapult Online nor Home Internet Math	Pretest Mean	807.56	768	879	22.30	3.67
Neither Catapult Online nor Home Internet Math	Post Test Mean	810.97	774	863	22.92	3.77

Table 2 shows the mean pre and post test scores for each of the independent variable groups. The minimum and maximum scores are shown for each content area within independent variable groups. Again, the content areas are Reading and Math, and the total sample size for each independent variable group was 37 (n=37).

According to Table 2, the mean pretest scores for both content areas in the Home Internet Access group were 811.30. The standard deviation for the Home Internet Math pretest means was 24.27 while the standard deviation for the Home Internet Reading pretest mean was 26.25.

The minimum and maximum CRCT mean scores also differed. The minimum score for the Home Internet group Reading pretest group was 755 while the Home Internet group Math pretest minimum score was 763. The maximum score for each was 843 and 854 respectively. The standard error of the means was 4.32 for the Home Internet Reading Group pretest and 3.99 for the Home Internet Math group pretest.

It is also interesting to note that all the groups showed an increase in mean scores from the pretest to post test in all the content areas except Reading for the Catapult Online group. The mean scores decreased 1.16 points. The lowest mean scores occurred in the Catapult Math pre and post test scores with 796.68 for the Math pretest mean and 797.30 for the Math post test mean. The lowest CRCT score also occurred in the Catapult Online Math pretest with a score of 753. The highest CRCT score occurred in the Home Internet Math post test with a score of 923. This may indicate that the Catapult Online recipients may have received tutelage primarily in Math and not Reading.

Inferential Statistics

It was important to note that the students selected for the receipt of Catapult Online tutorials were identified as being generally academically deficient in either Reading or Math. For the purposes of the research, academically deficient meant that the students identified as such, either passed or failed a portion of the CRCT standardized test by a margin of + or – 20 points. These students are commonly identified as “bubble kids” in the Georgia public school systems. The CRCT uses a scale score of 650-900. The Georgia Performance Standards (GPS) Score Scaling System was constructed independently for each content area and each grade level. Scores at or above 850 indicate a level of performance that Exceeds the Standards set for the test. Scores from 800-849 indicate a level of performance that Meets the Standards set for the test. Scores below 800 on a GPS based CRCT indicate a level of performance that Does Not Meet the Standard set for the test (i.e., the state of Georgia’s minimum level of proficiency). It was therefore expected, that the mean pretest scores for the treatment group might be lower than both comparable groups’ pretest means. This was tested by conducting a one way ANOVA for the pretest scores. All the analyses were conducted at the .05 alpha level and observed differences between the scores was deemed significant if the p-value was less than .05.

Table 3

Analysis of Variance for CRCT Reading and Math Pretest Scores

		Mean	Std. Deviation	Std. Error	Minimum	Maximum	df	F	Sig
CRCT Pretest Reading Score	Between Groups						2	1.396	.252
	Within Groups						108
	Catapult Online
	Catapult Online	802.70	22.408	3.684	763	850
	Home Internet Access	811.30	26.251	4.316	756	856
	Neither Catapult Online nor Home Internet Access	809.59	21.357	3.511	775	874

CRCT Pretest Math Score	Between Groups						2	4.579	.012
CRCT Pretest Math Score	Within Groups						108
	Catapult Online	796.68	17.826	2.931	753	827
	Home Internet Access	811.30	24.268	3.990	759	867
	Neither Catapult Online nor Home Internet Access	807.65	22.302	3.667	768	879

Table 3 shows an analysis of variance indicating the mean pretest scores of the treatment groups and both comparable groups. As expected the mean score of the Catapult Online recipients was lower than the both comparable groups in Reading and Math respectively. While the Catapult Online group Meets the Standards according to the GPS, the mean Reading score for Catapult Online students was only 802.70 (SD=22.41) compared to 811.30 (SD= 26.25) for those students with home internet access and 809.59 (SD=21.36) for those students with neither Catapult nor home internet access. Furthermore, in examining Reading CRCT pretest scores in relation to type of internet access, we found the comparisons to be insignificant.

The mean math score for Catapult Online students was 796.68 (SD=17.83) compared to 811.30 (SD= 24.27) for those students with home internet access and 807.65 (SD=22.33) for those students with neither Catapult nor home internet access. According to the GPS, the Catapult Online groups’ mean Math score indicated a level of performance that Does Not Meet the Standard set for the test. In examining Math CRCT pretest scores in relation to type of internet access, we found the comparisons to be significant F(2,108)=4.579; p<.05. We therefore concluded that there seemed to be a significant difference overall in the Math CRCT pretest group scores according to types of internet access. Mean Math CRCT scores for the Catapult Online group were different from both the home internet access group and the comparable group who had neither the Catapult Online nor home internet access. These findings supported the academic borderline status of the Catapult Online recipients according to the GPS and their need for the additional tutelage. These findings also supported the literature which stated that students with access to computer internet access demonstrate higher academic performance.

To examine the effect of the Catapult program in improving students’ academic performance on the standardized CRCT test, a paired samples t-test, comparing the mean pre and post test standardized scores was conducted for both of the components of the measures of academic performances (Reading and Math) for the Catapult Online recipients. The paired samples t-test was the most appropriate technique for comparing mean scores from the same group of subjects.

Table 4

Catapult Online Recipients Pre and Post Paired Samples Test and Statistics

Paired Differences
		Mean	Std. Deviation	Std. Error Mean	Std. Deviation	Std. Error Mean	Mean	t	df	Sig. (2-tailed)
Pair 1	CRCT Pretest Reading Score	802.70	22.408	3.684
	CRCT Post Test Reading Score	801.54	18.245	2.999	18.771	3.086	1.16	.377	36	.709
Pair 2	CRCT Pretest Math Score	796.68	17.826	2.931
	CRCT Post Test Math Score	797.30	22.296	3.665	22.063	3.627	-.62	-.171	36	.865

The results for the Reading and Math pre and post paired sample test and statistics are presented in Table 4. Table 4 shows both the mean pretest and post test scores of only the Catapult Online students, for Reading and Math standardized CRCT tests. The mean Reading score for students prior to participating in the Catapult program (pretest) was 802.70 (SD=22.48) as against 801.54 (SD=18.25) for the Reading score after participating in the program. The observed difference between the reading scores was not statistically significant (t=.377, p=.709). The mean Math score for students prior to participation in the Catapult Online program (pretest) was 796.68 (SD=17.83) as against 797.30 (SD=22.30) for the Math score after participation in the Catapult program. The observed difference between the Math scores was not statistically significant (t=-1.71, p=.865). The Math scores showed an increase for the Catapult recipients but the Reading scores declined.

Table 5

Analysis of Variance for CRCT Post Test Reading Scores with Post Hoc Test (Tukey HSD)

		Mean Difference (I-J)	Std. Error	Sig.	df F
Between Groups				.003	2	6.222
Within Groups					108
Catapult Online	Home Internet Access	-13.54*	4.620	.011
	Neither Catapult Online nor Home Internet Access	-14.62*	4.620	.006
Home Internet Access	Catapult Online	13.54*	4.620	.011
	Neither Catapult nor Home Internet Access	-1.08	4.620	.970
Neither Catapult nor Home Internet Access	Catapult Online	14.62*	4.620	.006
	Home Internet Access	1.08	4.620	.970

*The mean difference is significant at the .05 level

According to Table 5, a one way analysis of variance of Reading CRCT post test scores show the internet access group and the Catapult Online tutorial group to be significantly different F(2,108)=6.22; p<.05. We therefore concluded that there seemed to be a significant difference overall between the Reading CRCT post test groups according to types of internet access.

Having established there was a significant difference overall between the three groups, it was necessary to identify which particular pairs of groups could be judged to be significantly different. The Tukey HSD test results in Table 4 detected significant differences in mean Reading CRCT post test scores between two groups only: Those students who participated in Catapult Online and those students who neither participated in the Catapult Online tutorial nor have internet access at home (p=.006). Both of the remaining possible comparisons were found to be insignificant.

Table 6

Analysis of Variance for CRCT Post Test Math Scores with Post Hoc Test (Tukey HSD)

		Mean Difference (I-J)	Std. Error	Sig.	df F
Between Groups				.018	2	4.158
Within Groups					108
Catapult Online	Home Internet Access	-16.84*	6.207	.021
	Neither Catapult Online nor Home Internet Access	-13.68	6.207	.075
Home Internet Access	Catapult Online	16.84*	6.207	.021
	Neither Catapult nor Home Internet Access	3.16	6.207	.867
Neither Catapult nor Home Internet Access	Catapult Online	13.68	6.207	.075
	Home Internet Access	-3.16	6.207	.867

*The mean difference is significant at the .05 level

The Table 6 ANOVA of Math CRCT post test scores found internet access and the Catapult Online tutorial to be significant F(2,108)=4.16; p<.05. Again we concluded there appeared to be a significant difference overall in the Math CRCT post test groups according to types of internet access. Again, after having established from the interpretation of the ANOVA Table 6, a significant difference overall between the three groups, it became necessary to identify which particular pairs of subgroups could be determined to be significantly different. Included in Table 6 are the results of the Tukey HSD test which detected a significant difference in mean Math CRCT post test scores between those students who participated in Catapult Online and those students who had home internet access (p=.021). Both of the remaining possible comparisons were found to be insignificant.

Discussion

Addressing the needs of students who have not met proficiency has become increasingly important because of the emphasis of the NCLB Act. Schools and school districts must demonstrate progress is being made toward all children being proficient. For this reason, the ability to identify educational interventions that raise proficiency rates in schools is essential (McDonald, Trautman, & Blick, 2005). This study examined the efficacy of the Catapult Online tutorial program, utilizing it as one of three levels of internet accessibility available to students at LMS to achieve gains on the CRCT standardized test scores. The levels were the Catapult Online Tutorial program, home internet access, or nonparticipation in neither the Catapult Online Tutorial program nor home internet access. While the results of this study were encouraging for the employment of a systematic internet intervention, and the ANOVA found the marginal means for content area post test scores were significantly different: F(2,108)=6.22; p<.05 for Reading, and F(2,108)=4.16; p<.05 for Math, the effect was small.

The first hypothesis (H1) stated that students who participated in the Catapult Online Tutorial program would have higher academic performance on their mean CRCT standardized test scores than the control group who neither participated in the Catapult Online program nor home internet access. The mean score for the treatment group in Reading was 801.54 compared to 816.16 for the comparable control group who participated in neither for a mean difference of 14.62. Not only did the treatment group mean Reading score not exceed the comparable control group mean Reading score, but the treatment group’s mean Reading score actually declined from the mean pretest score of 802.70 to 801.54 for a mean difference of 1.15.

The mean score for the treatment group in Math was 797.30 compared to 810.97 for the control group who participated in neither for a mean difference of 13.67. While the treatment group’s mean Math score did not exceed the comparable control group mean Math score, the treatment group’s mean Math score increased from the mean pretest score to 797.30 with a mean difference of -.62.

The first hypothesis (H1) also stated that students who participated in the Catapult Online Tutorial Program would have higher academic performance on their mean CRCT standardized test scores than students who reported having home internet access. The mean score for the treatment group in Math was 797.30 compared to 814.14 for the comparable group who had home internet access, for a mean difference of 16.84. The mean score for the treatment group in Reading was 801.54 compared to 811.30 for the comparable group who had home internet access for a mean difference of 9.76. As stated previously, the treatment group’s mean Reading score did not exceed the comparable group’s mean Reading score and declined from the mean pretest score.

The second hypothesis (H2) stated that students who participated in the Catapult Online Tutorial program would demonstrate greater differences between the mean pretest scores and post test scores, than both the comparable group who neither participated in the Catapult Online Tutorial program nor had home internet access and the comparable students who reported having home internet access. The Catapult Online group demonstrated a difference of 1.16 for Reading and -.62 for Math. The greatest difference between pre and post tests means occurred within the group that neither participated in Catapult Online nor had home internet access. Reading score mean for this group increased 6.52 and the Math mean score for this group increased 3.41.

Limitations and Threats to Validity

A major limitation to any study is that the groups may not be necessarily the same before any comparisons takes place and may differ in important ways that could influence research outcomes. At the start of this study, the researcher empirically assessed one major difference between the groups, that is, the treatment group was identified based on low academic performance. If groups differ at the onset of a study, any differences that occur in test scores at the conclusion are difficult to interpret. This was the case in this study. As stated previously, the students chosen to participate in the Catapult Online Tutorial program were chosen precisely because they were academically deficient in one of the CRCT content areas. The strongest comparisons come from true experimental designs in which subjects (students, teachers, classrooms, schools, etc.) are randomly assigned to program and comparison groups. It is only through random assignment that evaluators can be assured that groups are truly comparable and that observed differences in outcomes are not the result of extraneous factors or pre-existing differences.

This researcher would argue, however, that even if the groups were in fact completely similar on the pretest and normal development resulting from typical home literacy practices or other instruction could have been identified as explanations for the differences, some problems still might have resulted from students in the comparison groups being incidentally exposed to aspects of the treatment condition. These could have included differentiated tutoring techniques or simply having availed themselves of other online resources. Other, more simplistic intervening variables could have been in the form of having been more motivated than students in the other groups, or just having had more motivated or involved parents in the learning processes.

Recommendations for School/Principal

As a result of these findings, my recommendation to the administration of LMS was to actively expand the opportunities for more students at LMS to receive free online tutoring. Another way for educators to consider the effect of the outcome more meaningfully is to consider the research hypothesis (H1): Students who participated in the Catapult Online Tutorial Program will have higher academic performance on their mean CRCT standardized test scores than the comparable group who had home internet access and the comparable control group who neither participated in the Catapult Online tutorial nor had home internet access. While the students who participated in the Catapult Online tutorial program, in fact, did not have higher academic performance on their mean CRCT standardized test scores than the comparable group who had home internet access nor the comparable control group that had neither Catapult Online tutorials nor home internet access, the mean Math scores for the 37 students who participated in the Catapult Online program increased. We should qualify this statement by stating first that the lowest mean scores were in Math content area of the treatment group and that both the mean Math pre and post test scores Did Not Meet the state of Georgia’s minimum standard for proficiency. Due to the format of this study and questions of construct validity, it may have been impossible to determine if the mean gains of this group were attributable entirely to Catapult Online. It was also impossible to determine whether students participated in the Reading or Math tutorials provided by Catapult. All that can be claimed was that the students who participated in the Catapult Online Tutorial Program produced higher mean scores on the Math content area post test than their mean pretest scores. This could possibly have been attributed to any number of factors such as social maturity, mental and physical growth, and educational factors that were not addressed here.

The study neither analyzed individual components of the Catapult Online Program, nor did the research delve into more personalized demographic characteristics of the students that may have impacted score performance on the CRCT standardized test such as family size and construct. While this study was being conducted, other literature pertaining to the digital divide and its effects on academic performance became available to this researcher that suggested there may be a correlation between household composition and internet access and subsequent academic performance. More specifically, there appears to be a relationship between households headed by poor, unwed mothers and inaccessibility to the internet and subsequent lower academic performance of students who are products of those households.

Now that LMS has made AYP for the past two years, the funding for after school programs, transportation, and equipment has been greatly reduced by the state. Conversely, Catapult Online has recently expanded its services to the general public instead of just school systems. I would further recommend administrators attempt to educate parents and other community stakeholders invested in the academic success of students at LMS, regarding the resources available to ensure students attain academic proficiency in all the content areas.

Recommendations for Future Researchers

I would recommend future researchers utilize a time series design if feasible. The federal NCLB Act states that all schools in the United States should meet a level of academic proficiency no later than 2013; so theoretically, there are only five more years to fulfill the requirements of NCLB. However, in time series designs, several assessments (or measurements) are obtained from the treatment group as well as from the control group prior to and after the application of the treatment. The series of observations before and after could provide rich information about students' growth; and because measures at several points in time prior and subsequent to the program are likely to provide a more reliable picture of achievement, the time series design could be more sensitive to trends in performance. This design, especially if a comparison group of similar students were used, would provide a strong picture of the outcomes of interest. Since students start taking CRCT standardized test in as early as the first grade, future researchers might consider constructing a more sophisticated study that could quite realistically track students from pre-primer grades to high school.

Another recommendation for future researchers would be to expand the scope of the study to include the entire Jefferson County student population in the sample. Students in the state of Georgia are administered the CRCT starting in the first grade. As of 2007, all students now have the opportunity to participate in the Catapult Online program independent of the school system. Because the population of interest is larger, a study of this caliber could be expanded and the study sample could be randomly sampled.

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