Your assignment is to find and select a quantitative research article to critique. I suggest you select an article that could later be used as one of your research proposal resources.

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NOTE: This is an example of very good work.

It is NOT necessarily PERFECT.

The final source for meeting assignment requirements

is the assignment instructions AND assessment rubric.

Be sure your submission follows 7th edition APA.

A Critique of “‘FRIENDS for Life’: The Results of a Resilience-Building, Anxiety-

Prevention Program in a Canadian Elementary School”

Sarah Foster

University of West Alabama

EDU 604: Advanced Educational Research

May 24, 2020

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Problem Statement

Anxiety disorders in children are correlated with poor school performance, and thus

should be addressed through a universal, preventative program.

Purpose of Study

The study’s purpose was to determine whether the FRIENDS program, a program that

uses cognitive behavioral principles to build emotional resilience and reduce mental illness

symptoms in elementary school students, was an effective approach to building resilience and

reducing anxiety in fourth grade Canadian students.

Hypothesis

The hypothesis of this study was that there would be a reduction in students’ self-

reported levels of anxiety after the intervention.

Description of the Quantitative Research

Quantitative research often seeks to apply existing theories in new situations, to test

whether the theory is applicable in all or other settings. Quantitative studies use instruments that

yield data that can be translated into numbers for statistical analysis. The results of quantitative

studies are presented using that statistical analysis and reported as summative responses,

rather than individual responses. Finally, those results are used to discuss further implications

and generalizations that can be made from the current study (Patten & Newhart, 2018). The

study “‘FRIENDS for Life’: The Results of a Resilience-Building, Anxiety-Prevention Program in

a Canadian Elementary School” meets these descriptors of a quantitative research study. The

authors of this research study sought to take existing research on the FRIENDS program and

apply it to a new scenario, Canadian elementary students, in order to extend the generalization

and objectivity of the previously determined theories. They used an instrument, the

Multidimensional Anxiety Scale for Children, that allowed participants’ responses to be

converted into numerical data. They then analyzed this data statistically and used that statistical

analysis to provide the results of the study. The results were presented as the statistical mean

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of the group’s responses, rather than reporting individual participants’ responses. The authors

concluded the research article by providing further implications for school counselors,

generalizing the results of the study.

Description of Subjects

The participants in this study were 52 Canadian fourth-grade students from an urban

school in western Canada. The researchers used intact classes of 26 students each for the

control and experimental groups.

Description of Instruments

The primary research instrument used was the Multidimensional Anxiety Scale for

Children (MASC), which was used as a pre-test and post-test. The MASC is a self-reported

measure of child anxiety, asking 39 total questions about physical symptoms, harm avoidance,

social anxiety, and separation anxiety. Students responded using a 4-point Likert-type scale,

where responses ranged from 0 (never true) to 3 (often true). The student responses were

converted into T-scores. The MASC is a standardized measure of anxiety which has shown to

have high test-retest reliability and acceptable levels of convergent and divergent validity.

Data Analysis

The researchers converted the pre-test and post-test student responses from the MASC

into T-scores for both groups. They calculated the mean, standard deviation, and standard error

mean, of the T-scores for the total responses and each subscale (physical symptoms, harm

avoidance, social anxiety, and separation anxiety). Then they found the difference between the

mean T-scores of the experimental group and control group, ran t-tests, and analysis of

variance.

Results

After analysis of the data, the authors found no statistical significance in the pre- and

post-test data for either group. Both groups showed reduced mean post-test scores when

compared to the pre-test results, which shows practical significance. The data shows that the

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control group had statistically significantly lower levels of anxiety at the start of the study. Both

the control group and the intervention group showed anxiety levels within the normal range at

the beginning and end of the study. Overall, the results opposed the hypothesis and did not

show that the FRIENDS for Life program decreased anxiety levels in these fourth grade

students.

Strengths and Limitations

The authors of this study used a quasi-experimental design and implemented the

program with fidelity. They used a reliable instrument and ran appropriate statistical analyses to

determine the results. However, there are several limitations to this study. First, the authors did

not use a random sample, instead using two intact classrooms. Second, the sample size of 52 is

relatively small. Third, the study used only student self-reported measures, rather than

assessing anxiety symptoms using multiple informants, such as teacher or parent observations.

Fourth, neither group showed elevated anxiety levels at the start of the study, which may have

limited the effects of the FRIENDS program. Finally, the authors did not or were unable to

control for other factors that may have decreased anxiety symptoms, such as maturation,

increased comfort levels within the school setting as the year progressed, or increased levels of

teacher training or attention.

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References

Patten, M. L., & Newhart, M. (2018). Understanding research methods: An overview of the

essentials (10th ed.). Routledge.

Rose, H., Miller, L., & Martinez, Y. (2018). “Friends for life”: The Results of a resilience-building,

anxiety-prevention program in a Canadian elementary school. Professional School

Counseling, 12(6), 400-407. https://doi.org/10.1177/2156759X0901200612

The Journal of the International Association of Special Education21(1) 2021 3

Relationship Between Class Size and Academic Achievement of Students with Learning Difficulties in Kakamega County, Kenya

Naomi Khakasa Wafula Masinde Muliro University of Science and Technology, Kenya

Eric Kiago Kabuka Maseno University, Kenya

N. K. Bota Masinde Muliro University of Science and Technology, Kenya

Abstract

Class size is an essential factor in student academic achievement. Small class sizes improve student achievement and teacher morale. For this reason, the researchers of this study set out to determine the relationship between class size and academic achievement among students with learning difficulties in secondary schools in Kakamega County, Kenya. The researchers used descriptive survey and correlational research designs. The target population was 36,453 third form and 37,532 fourth form students (eleventh and twelfth grade); 1,288 class teachers; and 12 sub-county education directors. Stratified random, purposive, and saturated sampling techniques were used. Data collection tools included questionnaires, interview schedules, and focus group discussion guides. Data were analyzed using percentages, means, standard deviations, Pearson’s (r) correlation and ANOVA. Findings indicated a statistically significant relationship between class size and academic achievement among underachieving students. Findings show that increase in class size leads to decrease in academic achievement among these students.

Keywords: class size, academic achievement, students with learning difficulties

INTRODUCTION

As they implement education for all and the Sustain- able Development Goals (SDGs), many governments in developing countries have been faced with the challenge of aligning available physical structures and personnel with the student population (UNESCO, 2010; Katiwa, 2016; Njenga, 2019). For instance, the Ken- ya government introduced a free secondary schooling education program whose target was to increase student enrollment to 1.4 million by the end of 2008. Enroll- ment increased from 1.18 million in 2007 (639,393 boys and 540,874 girls) to 1,701,501 (914,971 boys and 786,530 girls) in 2010 (Katiwa, 2016; Kapelinyang & Lumumba, 2017). The 100% transition policy led to a population explosion in secondary schools, thus putting strain not only on the physical facilities, but also on the personnel (Njenga, 2019; Teachers Service Commis- sion, 2019). The teacher-student ratio increased sig- nificantly, thus reducing the close interaction between teacher and learner.

Notably, efforts towards inclusive education have raised concern about students with learning difficulties in large classrooms. Inclusion is a policy and practice of

placing students with disabilities and special education needs in a regular class for the purpose of instruction (Zigler et al., 2017; Lerner, 2009). The basis of inclu- sion is that homes, schools, and society at large should be restructured to ensure that all individuals, regardless of their differences, have the opportunity to interact, play, learn, work, and experience the feeling of be- longing, and develop in accordance with their potential and difficulties (Kenya Ministry of Education, 2018). Therefore, implementing inclusive education calls for accommodating students with learning difficulties with- in all schools and all classrooms. However, concerns are growing about the influence of increasing class size on the academic achievement of students with learning difficulties.

Students with learning difficulties tend to learn and acquire skills at a slower rate, compared to typical- ly-developing students (Abosi, 2007; Ndani & Muru- gami, 2009; Sebastian, 2016). Sebastian (2016) further elaborated that students with learning difficulties do not keep pace with the teaching-learning process. Williamson and Ryan (2012) described students who have learning difficulties as being characterized by poor concept formation, with difficulties in reading, writing,

The Journal of the International Association of Special Education 2021 21(1)4

and arithmetic skills. These learners struggle to grasp the curriculum, and some may have mild intellectual disabilities with characteristically below-average cogni- tive abilities and scholastic performance (Borah, 2013; Reynolds & Fletcher-Janzen, 2006; Vasudevan, 2017; Qian, 2008).

Environmental factors such as poverty are argued to have direct and circumstantial impact on learners’ academic achievement (Bota, 2007; Ferguson et al., 2007; Olszewski-Kubilius & Corwith, 2017). Poverty limits students’ access to financial, emotional, mental, and physical resources, as well as appropriate support systems and role models (Lacour & Tissington, 2011). Furthermore, schools in rural and urban poor environ- ments are characterized by inadequate personnel and poor infrastructural development, resulting in large class sizes (Kihoro & Kabunga, 2016). This leads to the contention that poverty increases the chances that students with learning difficulties will be placed in large class sizes.

The authors of this paper argue that students with learning difficulties are entitled to meaningful learning experiences that enhance feelings of belonging along- side academic achievement. However, obstacles in the school undermine these goals (Bota, 2007; Borah, 2013; Metto & Makewa, 2014; Vasudevan, 2017). Class size is one of the major risk factors in academic achievement of the general student population (Monks & Schmidt, 2010; Owoeye & Yara, 2011; Mirani & Chunawala, 2015). Notably, Sebastian (2016) ob- served that mass enrollment—and the resulting lower teacher–student ratio—is a risk factor in the academic achievement of students with learning difficulties who generally require more personal attention in classroom instruction.

Wapula (2011) observed that opportunities for stu- dents with learning difficulties are almost non-existent in both public and private schools in Botswana. The author of the current paper further noted that children with learning difficulties either perform poorly or drop out of school because they are demotivated and dis- couraged by large class sizes where they cannot have quality contact with teachers. Furthermore, Williamson and Ryan (2012) argued that because of their “between- ness,” students with sheer learning difficulties are not eligible for special education programs. Mwangi (2013) concurs that such students are rarely identified for prop- er placement. These students eventually quit school or just hang on with little hope of good performance. This is a common scenario in most African countries.

Class Size and Academic Achievement Class size is a risk factor in academic achievement

(Mirani & Chunawala, 2015). Generally, overcrowded classes are linked to falling education standards (Owo- eye & Yara, 2011; Sebastian, 2016). It is argued that student achievement decreases as class size increases. Monks and Schmidt (2010) established that class size had a negative and statistically significant impact on student course evaluation. Similarly, Bandiera et al. (2009) found a statistically significant negative (but non-linear) effect of class size on testing results of stu- dents in a northeastern university in the United States of America. The famous STAR program in Tennessee involved classes that ranged in size between 15–17 and 22–25 students. It was observed that students from small classes performed better on standardized tests in mathematics and reading in kindergarten to third grade (Monks & Schmidt, 2010). In a follow-up program in North Carolina, with classes ranging between 15–25 students, it emerged that students in smaller classes achieved test scores of .45 and .56 standard deviations higher than peers in larger classes on mathematics and reading tests respectively (Vandenberg, 2012). These findings were supported by Whitehurst and Chingos (2011) who noted that elementary students assigned to small classes outperformed their classmates in larger regular classes by .22 standard deviations.

In a study carried out in Nigeria, Yara (2010) ob- served that class size influenced academic achievement in mathematics, with those in smaller classes perform- ing better than those in larger classes. Owoeye and Yara (2011) further argued that small class sizes led to less retention, fewer referrals to special education, and few- er dropouts. Notably, Bye (2017) observed that large class sizes hinder the effective working of a teacher as a facilitator who needs to cultivate the learner’s self-mon- itoring and self-regulation skills to achieve learning outcomes. Monks and Schmidt (2010) similarly sup- ported the view, noting that large classes allow students to be more disruptive and give room for disengagement while small classes lend themselves more to pedagogi- cal activities that improve academic achievement.

Arguments in support of smaller class sizes abound. Smaller class sizes not only increase teacher-student contact, but also increase the morale of teachers and reduce stress. Furthermore, teachers are likely to be more creative and less likely to burn out (Yara, 2010). Vandenberg (2012) notes, “Finding engaging, high- ly-qualified teachers is not enough; the number of students assigned to a teacher is important.” (p.12). He

The Journal of the International Association of Special Education21(1) 2021 5

further argues that small class size facilitates individu- alized instruction and lessens indiscipline cases in class. Blatchford et al. (2007) and Cakmak (2009) assert that larger classes make it harder to differentiate instruc- tion and maintain student discipline. The overriding argument is that class size has a direct influence on the eventual academic achievement of students in general and those with learning difficulties in particular.

However, there are conflicting findings on the effect of class size on academic achievement. Studies carried out in Tennessee (USA) by that state’s Department of Education indicated that reducing class size increased student achievement; however, subsequent studies, especially in Asia, contradict the findings (Woessman & West, 2006). Essentially, studies from Asia suggest that reducing class size does not improve academic perfor- mance. Jepsen and Rivkin (2009) argue that studies on the effect of class size have limited clarity, while some revealed mixed findings.

In essence, some studies indicate that reducing class size has a large effect on academic performance, while others depict little or no effect. Moreover, other studies have indicated that class size reduction works in some cases, but not in other similar circumstances (White- hurst & Chingos, 2011; Chingos, 2010). Whitehurst and Chingos (2011) further noted that elementary students assigned to smaller classes performed better than those in regular large classes. However, it emerged that the effect was more visible with boys and economical- ly-disadvantaged children. The study further revealed that class size reduction may have meaningful long- term effect on student achievement only if introduced in lower grades and for children who are less advantaged. Equally, Bandiera et al. (2009) argued that class size had significant impact on student performance but only at the very top and bottom of class-size distribution. Despite many studies on the influence of class size on learners’ academic achievement, the findings are incon- clusive; hence the need for continuous research.

Intuitively, smaller classes make sense for teachers working with struggling students (Korir & Kipkemboi, 2014; Vasudevan, 2017; Whitehurst & Chingos, 2011). However, as outlined, this assumption is supported by some studies and disputed by others. Furthermore, most of the studies have been undertaken in developed coun- tries and involve the general student population. This study, on the other hand, gives a developing country perspective by examining the influence of class size on the academic achievement of students with learning difficulties in Kakamega County.

METHODS The study used descriptive survey and correlational

research design because the intent was to establish and describe the relationship between class size and aca- demic achievement of students with learning difficul- ties. Descriptive survey method allows the collection of both qualitative and quantitative data. The design is fairly economical and allows data collection from a large population at minimal cost (Punch & Oancea, 2014; Mertler, 2019). Correlational research design was used to determine the relationships between class size and academic achievement among slow learners. The target population was 73,985 students, 36,453 of whom were from third form and 37,532 of whom were from fourth form (equivalent to eleventh and twelfth grade); 1,288 classroom teachers from forms three and four; and 12 sub-county Directors of Education from Ka- kamega County.

Stratified random sampling was used to select the schools because they are not homogenous (Kothari, 2004). The strata consisted of schools based on the school type (sub-county, county, extra-county, and national). Saturated sampling was used in selecting the national schools. This study adopted a 10 percent sample size drawn from the target population. A sample of 35 schools was selected, including 129 classroom teachers and two Sub-County Directors of Education. Fisher’s formula was used to determine the sample for slow learners because the exact population was not known. The sample of students with learning difficul- ties was therefore 246. From each selected school, slow learners were selected from the low achievers based on achievement tests. Teacher nomination was key in identifying slow learners to participate in the study. Data were analyzed using percentages, means, standard deviations, Pearson’s (r) correlation, and analysis of variance (ANOVA).

RESULTS

To determine the relationship between class size and academic achievement of students with learning diffi- culties, the researchers first sought to describe the state of class sizes among secondary schools in Kakamega County. The results are provided in Table 1.

Table 1 shows that most class sizes in the study were large, ranging between 31 and above 60. The majority of classes (35%) were 46 students and above. Notably, results from teachers’ questionnaires indicated that 18.0% felt that large class sizes negatively influenced the academic achievement of students with learning difficulties to a very large extent while 54.1% felt that

The Journal of the International Association of Special Education 2021 21(1)6

class size negatively influenced the academic achieve- ment to a large extent. This implies that 72.1% of the teachers felt that large class sizes are a risk to the aca- demic achievement of students with learning difficulties in secondary schools in Kakamega County. Most of the teachers indicated that large class size made them resort to the use of passive teaching methods that are more teacher-centered than learner-centered, such as the lec- ture method. Conversely, the learners interviewed felt that class size does not affect their academic achieve- ment. Indications were that the students with learning difficulties were contented both in large and small class sizes. As one learner put it, “so long as the teacher can be able to offer me assistance when I need” it. This shows that the learners were not aware that a large class size may hinder the teacher from giving them needed assistance.

To test for the null hypothesis—the possibility that there is no significant relationship between class size and academic achievement of students with learning difficulties—the study used the One-Way ANOVA tech- nique. Results are provided in Table 2 and Figure 1.

Results for the ANOVA test, as shown in Table 2, were F(4, 126) = 2.166, p = 0.047 < 0.05. This indi- cated that the class size has a significant influence on the academic performance of students with learning difficulties. For class sizes of 1–15 students, the average or mean score was 45.7813; for class sizes of 16–30 students, the mean score was 42.7857; for class sizes of 31–45 students, the mean score was 39.37; for class siz- es of 46–60 students, the mean score was 40.2; and for class sizes of 60 or more students, the mean score was

20.8125. The mean plot (see Figure 1) also indicates a decrease in academic performance as class size increas- es. The study therefore concludes that having a very large class size is likely to lead to poor performance among students with learning difficulties in secondary schools in Kakamega County.

The correlation analysis indicated a statistically significant relationship between class size and academic achievement of students with learning difficulties. Class size was found to have a negative significant relation- ship, (r = -0.199, p = 0.023 < 0.05). This implies that as class size increases, the academic achievement of students with learning difficulties decreases.

DISCUSSION

The study results indicated large classes, ranging between 31 and above 60 (Table 1). The majority of classes (35%) were 46 students and above. Inciden- tally, Chokera (2014) found a similar scenario in the study carried out in Akithii Division, Meru County. The majority of class sizes (41%) ranged between 41–50, while 29% ranged between 51 and above. Similarly, Waseka and Simatwa (2016) found the average class sizes in Kakamega County as follows: 18–45 (60.8%) and 50–60 (37.5%). This implies that generally speak- ing, class sizes are large in parts of the country and in Kakamega County in particular. Comparatively, studies carried out in developed countries depicted classes that ranged between 15–17 and 22–25, such as the STAR research program (Monks & Schmidt, 2010; White- hurst & Chingos, 2011). It is argued that class size is a key factor in academic achievement (Mirani &

Table 1 Descriptive Findings on Class Sizes.

Statement 1–15 16–30 31–45 46–60 60 and above Class size for the common subjects

5% 15% 45% 25% 10%

Class Size for optional subject 1

13% 34% 25% 17% 11%

Class Size for optional subject 2

13% 29% 29% 19% 10%

Class Size for optional subject 3

10% 34% 30% 18% 8%

Class Size for optional subject 4

10% 30% 35% 14% 11%

Class Size for optional subject 5

12% 27% 39% 17% 6%

The Journal of the International Association of Special Education21(1) 2021 7

Chunawala, 2015). Commonly, overcrowded classes have been linked to falling academic standards (Owo- eye & Yara, 2011; Sebastian, 2016). It is argued that student achievement decreases as class size increases. This study lends credence to that supposition.

Yara (2010) observed that academic achievement in mathematics was influenced by class size in a study carried out in Nigeria: students in smaller classes per- formed better than those in larger classes. Whitehurst and Chingos (2011) also noted that elementary students

Figure 1 Mean Plot for Academic Achievement Across Class Sizes.

Table 2 Results of One-way ANOVA Test.

Academic Achievement (out of 100%) Class Size Count Mean Std. Deviation Std. Error Minimum Maximum

1–15 16 45.7813 19.60439 4.90110 26.00 80.00 16–30 35 42.7857 20.58636 3.47973 15.50 79.50 31–45 50 39.3700 24.32933 3.44069 .00 90.00 46–60 22 40.2045 16.01759 3.41496 15.00 73.50 60 and above 8 20.8125 6.38602 2.25780 15.00 30.00 Total 131 40.0725 21.23550 1.85535 .00 90.00

ANOVA

Sum of Squares Df Mean Square F Sig.

Between Groups 3771.731 4 942.933 2.166 .047 Within Groups 54851.331 126 435.328 Total 58623.061 130

The Journal of the International Association of Special Education 2021 21(1)8

assigned to smaller classes performed better than those in regular large classes. Cakmak (2009) observed that in larger class sizes, teachers spent most of the time meant for academic instruction on class management. In contrast, Smith et al. (2003) noted that while some researches have indicated a negative relationship be- tween class size and academic achievement, their study revealed that reading and mathematics achievement had positive correlation with class size (r = 0.328, p <0.01, r = 0.308, p <0.01, respectively), meaning that as class size increased, reading and mathematics scores also increased. This was contrary to the popular assumption that as class size increases, academic achievement will decrease. The current study findings (r = -0.199, p = 0.023 < 0.05) similarly contradict the findings of Smith et al. (2003) with an indication of a negative correla- tion between class size and academic achievement of students with learning difficulties.

Comparatively, Vandenberg’s (2012) preliminary correlational analysis of results showed a positive rela- tionship between class size and academic achievement. However, this was based on the practice of assigning students with learning difficulties to small classes. Consequently, lower performance in classes with fewer students was primarily based on the fact that they had learning difficulties. Vandenberg’s 2012 study ultimate- ly indicated that many teachers believe that smaller classes have a positive impact on student achievement, indicating that class sizes of 20 students or fewer are ideal. Incidentally, Monks and Schmidt (2010) observed that class size had a statistically significant negative r

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