Performance of High School vs Middle School Teachers - Essay Example

This chapter outlines the research design which explains what type of research this study is. It also defines the population of the study and the specific sampling technique used. The method of data collection is carefully detailed and the method of data analysis is explained.

Research design is considered a "blueprint" for research, dealing with at least four problems: which questions to study, which data are relevant, what data to collect, and how to analyze the results. The best design depends on the research question as well as the orientation of the researcher. The study will adopt a descriptive survey as a method of collecting information by using a standardized form of the interview schedule and administering a questionnaire to a sample of individuals. This method is most appropriate for collecting information to determine if high school teachers and middle school differ in their attitudes towards education reform. Both the secondary and primary data will be used in the analysis. The design is also suitable because it gives an in-depth description of the phenomena in their existing setting. The descriptive survey is also preferred because it is economical in collecting data from a large sample with high data turnover.

Since it is quantitative research, this proposed study has both dependent and independent variables. The independent variable for the study is the teaching levels (middle and high school teachers) while the dependent variable is the attitude towards school reforms. On the other hand, this proposed study will seek to establish the relationship between the dependent variable (school reforms) and the independent variable (teaching levels).

The purpose of this study is to determine if there is a difference in attitude between high school teachers and middle school teachers towards education reform. The researcher will carry out 30 questions on a questionnaire survey to determine the mood of high school and middle school teachers towards education reform. The target population of the study is high school and middle school teachers across the country. 500 participants will be interviewed during the investigation. For preciseness, the teachers will be divided according to various age and sex. This will give a spread of responses and the opportunity to identify interesting differences.

Sample selection depends on the population size, its homogeneity, the sample media and its cost of use, and the degree of precision required.  The study will use the stratified sampling technique to get the required strata Khan (2011). This is a technique where the population is organized into strata, with each member occupying a specific stratum possessing homogenous characteristics. Each member of a particular stratum then has a probabilistic chance of being chosen for the sample. The population of this study was organized into four strata; male and female teachers, those under 30 and over 30 years old. A simple random sampling technique was then used to select the 500 respondents that were used from the study.

The study will rely mainly on primary data from the questionnaires and secondary data on large-scale variables. The questionnaire will be based on the linked scale and ordinal scale. Besides, non-quantifiable statements within the questionnaire will be developed on a non-ordinal scale which entails personal views Khan (2011). Open and closed-ended questionnaires will be used when asking the respondents about their attitude towards school reforms. Specifically, self-administered questionnaires will be used.  It is considered that a combination of self-administered questionnaires and in-depth personal interviews are, for the research, the most appropriate data collection methods. This is because of the advantages derivable from both approaches which include a high response rate; which is important for reliable data analysis.

A pilot study will be carried out and with subtle discrepancies and challenges, refining of the same made the tool sufficient for data collection. The pilot study will be conducted by randomly selecting a sample of 30; 15 male and 15 female. A pilot study is a very important step in this study because it helps in ascertaining the validity and reliability of the research instruments and making necessary adjustments. The research assistants will administer the questionnaires.

The data collected will be analyzed using both descriptive and inferential statistics. Qualitative data will be analyzed using grounded theory methods as described by Khan (2011). Open coding will be used to name and categorize the data, and selective coding will be used to develop a more general framework. The study will use frequency count, charts, bar graphs and percentages in data analysis. Because the study is quantitative, it will be appropriate to use frequency count, mean, standard deviation, and minimum and maximum values of variables.

Quantitative data analysis will be done to generate frequency percentages. The resulting quantitative data will be then interpreted using a simple statistical method. The questionnaire will be coded and analyzed using Statistical Package for Social Sciences (SPSS) version 21. The data collected through a questionnaire will be classified based on common attributes then tallied to obtain statistical frequencies, tabulated and finally analyzed using descriptive statistics. According to Khan (2011), this helps to collapse large volumes of quantitative data in numerical form for ease of statistical interpretation.  Frequency and distribution tables, graphs and diagrams will be integral during the process of data analysis. Comparative analyses will be used to outline the characteristics of the leading attributes within the variables under discussion.

The hypotheses formulated for this study will be tested using a logistic regression model. This has been used to examine the relationship between dependent and independent variables. According to Khan (2011), logistic regression is multiple regression but with an outcome variable that is a categorical dichotomy and predictor variables that are continuous or categorical.