**Essay Instructions**: My partner and I have been working on this paper together (To exam the relationship between the frequency of corporal punishement and the students' grade level, gender, and rural versus urban school), however, the instructor requires us to submit a different version of the writing. Hence, I would like your help to write another versin of the same paper. The soft copy of this paper will also be email to you. Thanks for your help.

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Chapter Three

Methodology

The purpose of the study is to examine the relationship between the frequency of corporal punishment and the students? grade level, gender, and rural versus urban schools. There is literature that examines these relationships in other parts of the world, but nothing has been reported for Taiwan. The outcomes of this analysis could become input to policies and advocacy programs that decrease corporal punishment of students by teachers in Taiwan.

Data required for this study has been gathered by different organizations in Taiwan over the years, but very little has been done to further analyze the data in order to lead to a more meaningful understanding on corporal punishment of students. This study is based on secondary data analysis of available data from the Humanistic Education Foundation in Taipei, Taiwan. Similar to other data collection methods, secondary data analysis has certain inherent limitations. Perhaps the most serious **issue** in using secondary data is that the data only approximate the kinds of data that the investigator would like to employ for testing the hypothesis. There is often an inevitable gap between the primary data the investigator would like to personally collect with specific research purposes in mind and the data already collected by others. Differences are likely to appear in sample size and design, questions wording and sequence, the interview schedule and method, and the overall structure of the experiment. Secondary analysis may cause further problems if the researcher has insufficient information about how the data were collected. This information is important for determining potential sources of bias, errors, or other problems with internal or external validity. Based on all these aforementioned reasons, the use of secondary data means having to analyze and scrutinize the available data in ways that are often above and beyond that of directly collected data.

The data used in this study was gathered by the Humanistic Education Foundation in Taipei, Taiwan in 2004. The Humanistic Education Foundation is one of the grass-root advocacy groups in Taiwan. They devote themselves to many kinds of **educational** **issues**, especially school violence and teachers? corporal punishment of students. They have conducted a series of surveys titled ?Current Teachers? Corporal Punishment in Elementary and Junior High School in Taiwan? since 1999. The data for this study is based on the survey conducted in 2004. The reasons not to choose data from 1999 to 2003 are as follows. The questionnaire used in 1999 and 2000 was to pilot the study and that questionnaire has never been validated. The questionnaire conducted in 2001 and 2002 was improved. However, the questionnaire was based on a qualitative research design, and as a result, there was very little quantitative information from the results.

For 2003, the foundation revised several questions in their questionnaire with the intent to create a more reliable and valid questionnaire. However, the 2003 data was collected only in Taipei and consisted of many missing value. In fact, the same **issues** also existed in data conducted from 1999 to 2003.

In an effort to ensure better data quality and broader representation by the data, the Foundation decided to make a significant investment in the 2004 survey. They improved the survey and overall approach to address many of the **issues** from the previous versions. The data for 2004 covered a much broader geography, and specific effort was made to minimize missing values and increase response rate based on a validated and more reliable questionnaire. For all the aforementioned reasons, the data from 2004 was chosen for this research study.

Sampling Method

The study employs a national sample of 1311 elementary and junior high school students in different areas in Taiwan. The sampling for the study is as follows:

(1) students from elementary school

(2) students from junior high school

(3) students from Northern, Central, and Southern regions in Taiwan

(4) schools from both urban and rural areas

(5) grade level from 1 to 9

A stratified random sampling method was used to draw a representative sample of students. First, investigators followed the Taiwan National Development Plan from Taiwan Central Government and divided the country into three regions: North, Central and South. Each region has slightly differences in culture, political and economic status, and natural environment. Secondly, in each region, one rural and one urban area were selected by random. Hence, this results in a three by two stratification with urban areas in North, Central and South, and rural areas in North, Central, and South. Thirdly, a proportionally stratified random sample was employed to represent elementary and junior high schools. As a result, 62 junior high schools and 162 elementary schools were selected to add to the distribution in different strata. In every school, disproportionate stratified sampling was employed, with 6 students selected in each school in the sample frame. Due to 3 elementary schools dropping out of the project, the total number of elementary schools was 159. Finally, 1344 students were selected with a response rate of 97.5%.

Strength and Limitation of Sampling Method

Researchers use stratified sampling primarily to ensure that different groups of a population are represented adequately in the sample so as to increase the level of accuracy. Furthermore, all other factors being equal, stratified sampling considerably reduces the cost of performing the research. The underlying idea in stratified sampling is to use available information on the population to divide it into groups such that the elements within each group are more akin to the elements in the population as a whole. The results in creating a set of homogeneous samples based on the variables of interest. If a series of homogeneous groups can be sampled in such a way that when the samples are combined, they constitute a sample of a larger and more heterogeneous population, the accuracy of population estimates will be increased. The stratification procedure does not violate the principle of random selection because a probability sample is subsequently drawn within each stratum or specific group.

The fundamental principle applied when dividing a sample into homogeneous strata is that the criteria on which the division is based be related to the variable the researcher is studying. Another important consideration is that when using these criteria, the ensuing number of subsamples does not, taken together, increase the total size of the sample beyond what would be required by a simple random sample. However, if all these criteria were in fact used, the value of the stratified sample would diminish because the number of sub samples required would become enormous.

Sampling from the different strata can be either proportional or disproportional. If the number of sampling units taken from each stratum is of the same proportion within the total sample as the proportion of the stratum within the total population--- a uniform sampling fraction (n/N)--- we obtain a proportionate stratified sample. However, if proportion of the sampling units from each stratum included in the total sample is either above or below the proportion of the total numbers ( N ) in each stratum within the population--- that is, if the sampling fraction vary--- the sample is a disproportionate stratified sample. In other words, when the total number of people characterized by each variable (or stratum) fluctuates within the population, we need to choose the size of each sample for each stratum according to our research requirements. This choice is influenced by the likelihood of obtaining a sufficient number of sampling units from each stratum within the final sample. As a rule, disproportionate stratified samples are used either to compare two or more particular strata or to analyze one stratum intensively (Creswell, 1994). When researchers use a disproportionate stratified sample, we have to weight the estimates of the population?s parameters by the number of units belonging to each stratum. In this sample, weighting strategies seems not to have been done in the original data.

Once researchers have defined the population of interest, they draw a sample that represents that population adequately. The actual procedures involved selecting a sample from a sampling frame comprised of a complete listing of sampling units. Ideally, the sampling frame should include all the sampling units in the given population. In practice, such information is rarely available. Hence, researchers usually have to use substitute lists that contain the same information but may not be comprehensive. There is a high degree of correspondence between a sampling frame and sampling population. The accuracy of the sample depends, first and foremost, on the sampling frame, because every aspect of the sample design--- the population covered, the stages of sampling, and the actual selection process--- is influenced by it. Before selecting a sample, the researcher has to evaluate the sampling frame for potential problems. According to Kish, when inspecting the sampling frame, propose, the typical problems found in sampling frames are incomplete frame, clusters of elements, and blank foreign elements.

The problem of incomplete sampling frames arises when sampling units found in the population are missing from the list. When the sampling frame is incomplete, one option that might be available is the use of supplemental list. In this data, schools are sampled from the complete sampling frames, incomplete sampling frames does not exist in this sample. The second potential type of problem with sampling frame is clusters of elements. This problem occurs when the sampling units are listed in group rather individually. In this sample, this problem does not exist. The third potential type of problem is blank foreign, which is quite common in studies. It occurs when some of the sampling units in the sampling frame are not part of the research population, such as the case where the research population is defined as eligible voters whereas the sampling frame includes individuals who are too young to vote. This problem often occurs when outdated lists are used as the sampling frame. In the current survey, this problem of blank foreign elements does not applied in this data.

Compare to a clinical, convenience or purposive sample, this sample in this study is more generalizable by capturing a wide spectrum of data on teachers? corporal punishment of students in schools and students? responses with a range of victimization experience. It also reaches students who have not sought outside assistance for various reasons. Most importantly, it reaches many schools in rural areas, where there are less **educational** resource, compared to urban area. Northern Taiwan is more urbanized and rich in resources. So far, many studies were conducted in the North but much fewer in Central or Southern regions. This data can help us understand the current teachers? corporal punishment **issues** in these areas with more vulnerable **educational** systems.

Overall, this data is more representative nationally based on a stratified sampling method. The sampling strategy also reaches the students from rural or other areas in Taiwan that are often ignored by many researchers. Most importantly, following this sampling method, we can more accurately estimate the prevalence of teacher employing corporal punishment on students. Victimization rate is more representative, and there are no **issues** with sampling frames, which strengthens the confidence of this data. Given that a high response rate (97%) is achieved in this data, as a result, this data can be perceived as very representative of the overall population. However, since only elementary and junior high schools in Taiwan were sampled, the results of this study only can be generalized to the elementary and junior high schools in Taiwan. Senior high schools would not be part of the generalization, and the results may not be generalized to other countries in the world.

Instrument

A self-created version of Teachers? Aggressive Punishment toward Students (Human Education Foundation, 2004) was administered to measure the variables of interested in this study.

This instrument was composed of 42 items. The content of this instrument is followings:

Basic Demographic Information. Four items provided demographic information, such as the location where students were located (North, Central, South; Urban and Rural), students? gender, and students? school and grade level.

Punishment Types in schools. This variable was based on situations or events that students witnessed at their schools. As a first part of the survey, participants were asked, ?What types or ways of teachers? punishment have you seen so far since last semester?? Students will answer 11 questions that focus on different types of punishment. These questions, for example, include ?I saw teachers asking students to strike other students as punishment?, ?I saw teachers directly hitting students?, ?I saw teachers depriving students? basic needs, such as eating, drinking, resting?. These questions were answered by 1=no and 2=yes. The scale had an alpha reliability of .78.

The second part is the variable examining what students had seen as the implements that teachers used when they punish students. The question is ?What tools have you seen since last semester that teachers used when they punish students?? There are 7 items and include, for example, ?Did you see that teachers use their hand to aggressively punish students? ?, ?Did you see teachers using ruler to punish students??, and ?Did you see teachers using rod to punish students?. Response were given 1=no, and 2 = yes. The scale had alpha reliability of .77.

The third part of this scale is the open question. This open question is to discover any out of the ordinary punishment tools or methods employed by teachers in schools. Students are asked, ?What are the most strange or weird implements and ways that teachers employ when they punish students?? Students are asked to describe what they saw in a brief description.

Prevalence of Punishment. This subscale consists of three questions that refer to the students? personal experience on teachers? administration of corporal punishments. First item is ?What proportion do you think among your teachers physically punished students since last semester?? The response is given in a 4-point Likert-type by 1= all of them, 2= over a half, 3= below a half, and 4= none. The second question is ?How many times have you been physically punished by teachers since last semester?? The response were given in a 4-point Likert-type with 1= never, 2= 1 to 5 times, 3= 6 to 10 times, and 4= over 10 times. The third question is ?Have your teachers asked your parents to sign the contract to permit physical punishment?? The response is given 1= yes, 2= no, and 3= don?t know.

The reason of punishment. The fourth subscale consists of 6 items that refers to the reasons why teachers in school punished students. First five items are ? I was punished by teachers due to poor academic performance?, ?I was punished by teachers due to behavior problems?, ? I was punished by teachers due to bad attitude?, ?I was punished by teachers due to fighting with other students?, and ? I was punished by teachers for being associated with other students who have committed an offence?. The sixth question allows an open answer so student could describe other reasons why they were punished. Responses of the first five items were given on 1= no and 2 =yes. These five items had an alpha reliability coefficient of .63.

Impact of Punishment. This subscale aims to examine the impact of teachers? punishment on students. Two dimensions were inspected and the first dimension is to examine the impact of direct punishment. Students were asked what about their thoughts when punished by teachers, and the items included ?I feel scared, shamed, and quilt?, ? I feel angry and want to retaliate?, ? I feel I deserved it?, ? I think it is cruel and unreasonable treatment?, ? I feel I am the target of the teachers? venting their frustration?, and ? I don?t know?. The last question is open to allow students to describe their feeling or thoughts. The six items were given responses of 1=no, and 2= yes. The first six items had an alpha reliability coefficient of .82.

The second dimension is to examine the impact of witnessing teachers? punishment of other students. Students were asked ?When you see other students punished by teachers, what do you think?? Answers included ?I feel sympathy toward those students?, ? I feel lucky that I am not that person?, ?I think the teachers are right to punish these students?, ?I feel injustice and angry at teachers? punishment of those students?, and ? I don?t know my feelings?. The last question is open to allow students to freely describe their feelings and thoughts. The first 5 items are given the response 1= no, and 2= yes. The first 5 items has an alpha reliability coefficient of .79.

Potential Transmission of Teachers? Punishment. This variable is to examine whether there is potential transmission in students? points of view towards teachers? punishment. This question asked students ?Whether you will employ corporal punishment toward students if you become a teacher in the future? The response was given 1= yes, 2= no, 3= it depends, and 4= unsure.

Students? self-report of academic performance. This variable is to examine students? academic performance by students? self-reporting. Students are asked ?What is your academic performance? ?. The response is given 1= good, 2=fair, and 3= bad.

Perception of Teachers? Punishment as Illegal. This variable is to investigate whether the students knew that teachers? punishment was legal or not. Students are asked ?Do you know that it is illegal for teachers to physically punish students?? The responses are 1= yes, I know, and 2= no, I do not know.

Data Analysis

All data cleansing and analysis were conducted using SPSS for windows (Version 13.0). The initial phase of the analysis involved calculating the completion (response) rate and examining various characteristics of the respondents, such as basic socio-demographic characteristics and background. The completion rate was calculated by dividing the number of respondents who participate in the study by those prospective respondents who had been contacted and met the sampling eligibility criteria. The respondents? characteristics were examined using descriptive statistics, such as frequencies, means, standard deviation, mode, and range.

The analytical methods employed in testing the proposed hypotheses consisted primarily of the following procedures: 1) a descriptive analysis of the respondent?s experiences with teachers? punishment; (2) estimating the prevalence of teachers? punishment, as well as a bivariate analysis of the prevalence by demographic and students? background; (3) bivariate analysis of experience of teachers? aggressive punishment.

The descriptive analysis of experience of teachers? punishment:

Characteristics of violence experienced by the respondent were assessed by using descriptive statistics. These analyses included the specific types of punishment employed by teachers, witnessing of punishments, students? academic performance, and students? behavioral and emotional response. Content analysis was conducted on the responses to open-ended questions, such as the respondents? emotional and behavioral reactions to the teachers? punishment and the perceived influence of cultural values on teachers? response to teachers? aggressive punishment.

Estimating the prevalence of teachers? aggressive punishment:

Basic statistical tools will be used to estimate teachers? punishment. Measurements of association were used to examine the association between the rates of teachers? punishment and students? basic demographics.

In order to test whether students? experiences of teachers? punishment vary by gender, the location of the schools, and students? grade levels, Chi-square, Kolmogorov-Smirnov test, and measurement of association was conducted (Creswell, 1994).

Reference

Creswell JW, (1994). Research design: qualitative and quantitative approaches. Thousand Oaks, California, Sage Publications.

Kish, L. (1965). Survey Sampling. New York: John Wiley and Sons, Inc.

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