We are facing a serious problem of poor mathematics academic performance in Korea. In particular, students who attend Elementary schools with Diversity are performing poorly in math. These students come from different social backgrounds and the members that make up this group are multicultural students, low-income students, and student-athletes. Each of these schools has implemented its form of teaching methods or procedures to improve students' academic performance but truth be told improving students' academic skills was easier said than done. Under these circumstances, "Did the teachers in elementary school with diversity schools have sufficient student assessment test information which provides data to assess students' educational background of their strengths and weaknesses?"
While researching prior studies, there were studies conducted regarding multicultural students, low-income students, and student-athletes, however, it was difficult to find a study on Elementary school with Diversity. The student assessment information is vital to understand students' educational background, their merits, and demerits to implement solutions to improve their educational ability. Nevertheless, there have been parts that may have been overlooked in the research.
Based on the recognition of these problems, the purpose of this study was to explore the structural relationship between Elementary school with Diversity students' math academic performance and individual differences. Also, to explore the implication to improve math education at these institutions.
The research questions set up to achieve this objective were as follows:
Research Question 1. What are the effects of emotion, personality, cognitive ability, motivation, and learning strategy on the math academic performance in elementary school with diversity students?
Research Question 1-1. What are the direct effects of emotion, personality, cognitive ability, motivation, and learning strategy on the math academic performance in elementary school with diversity students?
Research Question 1-2. What are the indirect effects of emotion, personality, cognitive ability, motivation, and learning strategy on the math academic performance in elementary school with diversity students?
Research Question 2. Depending on the backgrounds of the students in elementary school with diversity, are there differences in emotion, personality, cognitive ability, motivation, learning strategy, and math academic performance?
To solve the research problem, the latent variables to be addressed in this study were selected as emotion, personality, cognitive ability, motivation, learning strategy, and math academic performance through a literature review on the teaching-learning model that reflects the learners' individual differences. The prior studies on the correlation or influence of latent variables were then reviewed, and a hypothetical research model was established based on these results. Then, one elementary school with diversity was conveniently sampled on the basis of whether it had representation as an elementary school with diversity, educational problems objectively existed, and satisfied sufficient data to utilize the structural equation modeling approach. I contacted the aforementioned school principal and the teacher in charge of student assessment. To conduct interviews, discuss the necessity and purpose of the study, and obtained consent from the educational institution and the school parents for the use of personal data for research purposes only. IRB approval (GIRB-G20-X-0022) was obtained for review of ethical issues that may arise in the overall process of data collection. Finally, in order to determine whether the data transferred from the school can be used in the structural equation modeling approach, data screening tasks such as checking missing value, outlier, multivariate normality, and multicollinearity verification were performed and the data was confirmed to be error-free.
The collected data confirmed what the model fit index of the structural equation model was, whether the measurement model was well constructed, and the path of the final structural equation model. As a result, the model fit index of the overall structural equation model was analyzed to be satisfactory. The measurement model was also analyzed that the factor loads of the standardization coefficient were all above 0.5 and were significant at the 5% level, and the construct reliability was all above 0.7, which was analyzed to be well-constructed. The estimates for the five significant paths of the estimated final structural equation model were as follows:
First, the estimate of 'personality→learning strategy' was 0.823 (t=4.983, p<.001), the estimate of 'emotion→competition·avoidance motivation' was 0.703 (t=4.644, p<.001), the estimate of 'personality→learning motivation' was 0.910(t=13.570, p<.001), the estimate of 'emotion→learning motivation' was -0.151 (t=-2.102, p<.05), and the estimate 'cognitive ability→academic achievement in mathematics' was 3.155 (t=9.382, p<.001).
Also, more detailed information about students at elementary school with diversity was sought by trying to analyze the differences in variables according to the subgroups. The results showed that first, there were no subgroup differences in math performance. Second, as a result of analyzing the difference between subgroups on emotion, it was found that there were differences in emotion according to gender, multicultural students, low-income students, and student-athletes. In particular, student-athletes showed relatively high emotion, unlike other subgroups. Third, as a result of analyzing the differences between the lower groups on personality, it was analyzed that there were significant differences in personality between multicultural students and low-income students. Fourth, as a result of the analysis of the differences in cognitive abilities by subgroup, the differences in cognitive abilities by grade were significant. Fifth, as a result of considering motivation as competition and avoidance motivation, it was analyzed that there are significant differences in competition·avoidance motivation according to gender, and there are significant differences in learning motivation according to grade. Sixth, as a result of analyzing the differences between subgroups of learning strategy, it was analyzed that there were significant differences between the multicultural students and low-income students.
Based on the results of the study, the implications for improving mathematics education for students enrolled in elementary school with diversity schools are as follows: First, in order to improve the mathematics academic performance of students who attend elementary school with diversity, it is required to prepare a program that trains their cognitive abilities. In addition, the results of the study highlighted the need to consider inserting personality in the preparation of cognitive improvement programs, which require different activities for each level of difficulty so that participating students can experience more success. Next, if the standard for the program preparation had been based on multicultural students, low-income students, and student-athletes, this needs to be modified to be based on individual differences. Finally, if there is a need for a program based on an environmental background, it seems more appropriate to prepare a program that can develop emotion, personality, and learning strategy.
This study was conducted on students that attend elementary school with diversity, which prominently shows poor math academic performance. The results of the study revealed the different characteristics of multicultural students, low-income students, and student-athletes at elementary schools with diversity. The results are expected to serve as an opportunity for education officials to shed new light on elementary school with diversity schools. Furthermore, the result of this research confirmed that student assessment test data provides education officials insights into the problem of poor math academic performance at elementary schools with diversity schools. It may be meaningful that these results go beyond the fragmentary relationship between math academic performance and latent variables that have been carried out in the field of mathematics education.