Mathematics Learning Performance and MathematicsLearning Difficulties in China

1a. Statistical tool used in the study:

A multi-stage stratification sampling is constructed by taking a series of simple random samples in stages. This type of sampling is often more practical than simple random sampling for studies requiring "on location" analysis, such as door-to-door surveys. In a multistage random sample, a large area, such as a country, is first divided into smaller regions (such as states), and a random sample of these regions is collected. In the second stage, a random sample of smaller areas (such as counties) is taken from within each of the regions chosen in the first stage.

1b. What it measures in the study?

The researcher used multi-stage stratification sampling to identify the total number of samples to be used in the study. In this study, mathematics performance data were obtained from 10, 959 students enrolled in Grade 1 to Grade 6.

2a. Statistical tool used in the study:

Cronbach's alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A "high" value for alpha does not imply that the measure is unidimensional. If, in addition to measuring internal consistency, you wish to provide evidence that the scale in question is unidimensional, additional analyses can be performed. Technically speaking, Cronbach's alpha is not a statistical test - it is a coefficient of reliability (or consistency).

2b. What it measures in the study?

The researcher used Cronbach's alpha to test the consistency and reliability of the Mathematics performance test, covering the mathematics curriculum from Grades 1 to 6. Thus, the researcher found out that the reliability of the scales was reported to be high.

3a. Statistical tool used in the study:

Exploratory factor analysis (EFA) is a statistical technique that is used to reduce data to a smaller set of summary variables and to explore the underlining theoretical structure of the

phenomena. It is used to identify the structure of the relationship between the variable and the respondent. Confirmatory factor analysis (CFA) is a tool that is used to confirm or reject the measurement theory. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) are similar techniques, but in exploratory factor analysis (EFA), data is simply explored and provides information about the numbers of factors required to represent the data.

3b. What it measures in the study?

The researcher used EFA and CFA to identify the relationship between the following SES variables; father and mother’s educational level. In an exploratory factor analysis (EFA) the results suggest a two-factor structure in the SES variable. But, weak factor loadings were observed for both father and mother’s educational level; moreover these SES items loaded on both factors. They were therefore excluded from the further analysis. In a second step, a confirmatory factor analysis was carried out building on the two-factor solution.

4a. Statistical tool used in the study:

Kendall's Tau assesses statistical associations based on the ranks of the data. Ranking data is carried out on the variables that are separately put in order and are numbered. Correlation analysis measures the strength of the relationship between two variables. Correlation analyses can be used to test for associations in hypothesis testing. The null hypothesis is that there is no association between the variables under study. Thus, the purpose is to investigate the possible association in the underlying variables. It would be incorrect to write the null hypothesis as having no rank correlation between the variables.

4b. What it measures in the study?

The researcher used Kendall’s tau to correlate between mathematics performance and parent’s occupational level and family’s wealth underscore the decision to include these variables in relation to the SES index. The researcher found a strong correlation between other variables in the study.

Significance of this research in the Philippine setting.

With this research we can also identify some factors that affect the academic performance of our students especially in Mathematics. These factors are predictors on how we can improve our teaching strategies for us to become effective and efficient teachers to our students. Through this, we can design an appropriate curriculum to those who are facing hardships with their studies due to some factors identified as significant. In the long run, this is very beneficial to all of the educators, like us, to address the needs of our students in Education and other matters.