A Teacher Perspective: Bullying and Participation in Classes

The main purpose of this study is to gain some understanding from teachers about their perceptions and practices surrounding bullying behaviors in class. While the purpose of every school is to impart knowledge to students and ensure better academic performances, the literature reviewed revealed that bullying has become a behavioral problem that is likely to frustrate such efforts. It is, therefore, necessary to examine the relationship between bullying and class participation using the teacher’s perspective. This chapter, thus, presents the intended methodology for this study. The chapter provides a description of the research method and design for this study including their rationale and appropriateness in the study. This chapter also discusses the intended sampling procedures, data collection procedures, and techniques of data analysis. Validity of the research method, both internal and external, is also included in this chapter.

Research Method and Design Appropriateness

The researcher will use the descriptive quantitative method in this study to test the stated hypotheses and provide answers to the guiding research questions. This will involve the utilization of both primary and secondary data to provide the information needed to make the final judgment. Secondary data will include a critical review of literature on the subject as well as a review of students’ academic performance records to be able to establish the link between bullying and academic performance. Primary data on the other hand will involve field surveys to collect information about teachers’ perception of the subject matter. This is congruent with a number of social scientists who emphasize the need to incorporate both secondary and primary data in a social science research study (Neuman, 2011; Bulmer, Sturgis & Allum, 2009). In this regard, Smith and Albaum (2010) stated that it is a mandatory rule for every researcher to conduct a thorough literature review on the subject matter before the collection of primary data.

Besides, the research topic falls in the category of social science guided by the “who”, “what”, “when”, “where” and “how” type of questions that often yield quantifiable answers hence can only be studied and analyzed in a quantitative manner. Further, the topic under study is quantitative in nature with well-defined variables hence the rationale for quantitative approach. The study has both dependent and independent variables as well as control variables. Dependent variables in this study will be “student’s performance outcome” and “teacher’s mode of intervention.” As had been mentioned earlier, bullying affects both individual student’s class participation as well as the teacher’s ability to utilize instruction time to the maximum hence the choice for these variables. Independent variables, on the other hand, will include “school policy,” “perceived seriousness,” and “support.” Control variables will include such factors as “gender,” “ethnicity,” “age,” and “teacher type.” According to Smith and Albaum (2010), a qualitative survey is more appropriate if the researcher has very little information about the problem, including study variables hence not appropriate in this study.

A quantitative descriptive survey methodology is appropriate in this study because such a design explores the association between variables in a descriptive format that allows the researcher to analyze other behavioral elements associated with the subject. According to Arinlade and Raheem (2008), a descriptive survey takes a careful examination of the phenomenon and describes it based on the researcher’s observations. The methodology used will enable the researcher to understand how bullying is affecting class participation from a teacher perspective, and provide data that will provide guidance on the best approach to handle problem behaviors in public schools. Survey method is highly congruent with a number of social researchers that emphasize the significance of survey design in studying a large population (Neuman, 2011; Wiersma & Jurs, 2009). A survey design allows for the study of a large population from a sample point of view (Wiersma & Jurs, 2009) hence the most appropriate in this study.

The researcher intends to use cross-sectional survey design to assess the relationship between bullying and class participation. Unlike longitudinal studies that focus on a group over a period, cross-sectional studies only examine a group at a particular point in time (Neuman, 2011). Given time limitations, undertaking a longitudinal study will be impossible hence; cross-sectional survey remains the most appropriate design in this study. Besides, this is an initial inquiry into the subject thus does not require a longitudinal study in order to get a synopsis picture of the situation. Further, the researcher is only interested in the teachers’ current perceptions on the subject matter hence the appropriateness of cross-sectional survey in this study. The researcher will use online survey to increase response speed and minimize on the cost of conducting the study. As Mabry-Hubbard (2008) observed, online surveys are increasingly becoming popular since they are cheaper to conduct.

Population, Sampling, and Data Collection Procedures and Rationale

  • Population: This study will be conducted in Florida State. The population of this study will consist of teachers whether regular full-time or part-time teachers in Jacksonville, FL Schools. This study will confine itself to surveying a sample population of teachers located in the sampled schools as will be discussed in the succeeding section of this topic. Since the researcher intends to assess the relationship between bullying and class participation, teachers remain the most appropriate respondent to provide the much-needed information.
  • Sampling: The researcher intends to collect data across Florida State. Since it will not be possible to collect data from all the schools in this area, the researcher will employ stratified sampling by first grouping schools into school districts then sampling one school from every district resulting into approximately 500 schools. The researcher believes this sample will be representative enough and the information gathered will have a national outlook. The researcher intends to sample randomly 20 teachers from every school resulting into a sample frame of 10,000 teachers, a sample that is big enough for a quantitative survey. The teachers will be sampled randomly as they access the school website. The survey will appear in a pop-up window in the school website enabling the teachers to either take the survey or opt out hence random sampling. The researcher will design the survey in such a way that it stops showing the moment twenty teachers submit their respondents. Likert-scale survey technique will be used to collect data from a sample population of 10, 000 participants. The researcher will adopt a Likert-scale type of questionnaire developed by Rensis Likert, which has been tested for reliability, practicability and validity in psychosocial research (Dawes, 2008). Stratified random sampling will ensure that the sampling process is free from any bias and that the sampled population is a true representation of the whole population. To access the sampled population, the researcher will contact the school principals to explain the intent of the study and request for support in using teachers in the study as well as the permission to reference such important school documents as student discipline and performance records throughout the study.
  • Data Collection: Both primary and secondary data will be collected for purposes of this study. Data collection procedures will therefore consist of;
    • a literature review that will be accomplished through a search of relevant literature in both public and private libraries as well as credible online libraries. The information gathered from these sources will provide the theoretical framework that will guide this study. Apart from a review of previous work on the subject, the researcher will also gather secondary information about students’ performance records from individual schools sampled for the survey.
    • and a cross-sectional survey to collect primary information about teachers’ perception of the subject. Online surveys will be used to gather information from teachers using graphical user interface (GUI) technology via the internet. This technique is most appropriate in this study since the study design has a wide geographical coverage and it will be time-consuming for the researcher to administer the questionnaires in person. Besides, the target population is literate hence is able to read and comprehend the questions on their own thus the rationale for self-administered questionnaire. Another advantage of online survey is that data will be automatically entered into the database hence minimizes the cost of data entry (Mabry-Hubbard, 2008). A survey with a backend SQL database accessible through a Web interface will be used to collect data for this study. The survey will appear in a pop-up window while accessing the school home page. A teacher who opts not to take the survey can close the window when it appears. The survey will be a single-page questionnaire design so that the respondents do not tire up clicking through multiple pages. A single-page survey will also allow the respondents to review previous questions and correct mistakes if any. Although the survey will be conducted using web interface, the researcher will have to conduct project monitoring to track responses and to ensure that the survey is accessible to all participants.
  • Instrument: A self-administered questionnaire comprising of model questions will be used to collect data in this study. The survey design will include a total of 35 model questions featuring a 5 to 7-point question value scale, to pinpoint question-level respondent results. Likert scales will incorporate agreement, frequency, importance, and likelihood scales. For instance, agreement scale will be a 5-point scale that provide a rating of 1= Strongly Disagree to 5= Strongly Agree for the model questions. The researcher adopts Likert survey scale as the most appropriate instrument for data collection in this study. Likert survey uses a pre-determined scale to gauge responses for various questions (Dawes, 2008). The survey will be accessible on the web to make certain that the collections of questionnaires are representative sample of the target population. The survey will be designed to allow only one answer per question and a maximum of twenty respondents per school. The researcher believes the topic under study is of great concern to the participants hence is likely to generate a high response rate.

Informed consent, confidentiality, and geographic location information

The researcher will send a prior letter of introduction to the school principals in the sampled schools informing them of the study and at the same time requesting them for the permission to include their teachers in the online survey. As a show of legality of the study, a copy of the Permission to Conduct a Survey Application form signed by the concerned state office will be sent together with the introduction letter via school official Email address to individual school principals. Details of the study explaining the conditions of the survey will be distributed to teachers through Email to alert them of the ongoing survey.

As a measure of confidentiality, the respondents will not have to disclose their identity in the survey. The information collected will remain private and will only be used for purposes of this study.

This study will be carried out in the State of Florida. The specific geographic location of this study will depend on the geographic locations of the sampled Jacksonville schools.

Validity and Reliability

Reliability as a measure emphasizes the ability of an instrument used in one study to obtain similar results when used in similar situations over time (Wiersma & Jurs, 2009). In other words, reliability refers to consistency of the measurement tool. Validity on the other hand emphasizes the ability of the measurement tool to yield the intended results. An online survey methodology combined with an advanced data analysis technique provides the highest level of precision and power necessary in this study. The focus of the survey will be to ensure valid measurement of the data, which requires reliability, validity and sensitivity. There are different forms of validity; however, the most important forms of validity in this study are internal and external validity.

Internal and External validity

Internal validity focus on how well the study was run and how confidently the researcher can conclude that changes in dependent variables resulted from changes in independent variables and not extraneous variables (Wiersma & Jurs, 2009). In the case of this study, internal validity will focus on the researcher’s ability to conclude confidently that bullying affects participation in class based on the findings of the survey. There are many threats to internal validity that every researcher has to look out for during the study. These include history, maturation of events, testing procedures, changes in instrumentation accuracy or precision, improvement in statistical scores, selection of participants, attrition, and selection method maturation (Wiersma & Jurs, 2009).

In contrast, external validity focuses on the ability to apply the findings of a study in a different environment under a similar situation (Wiersma & Jurs, 2009). External validity is more concerned about how applicable the results of a sample survey will be to the population. The main threat to external validity lies in sampling procedures. If the sampling process is marred with partiality, which does not allow for random selection of participants, then the study result may not be applicable to the population.

To achieve both internal and external validity, the researcher intends to employ stratified random sampling and use sophisticated data collection and analysis tool that will allow for reliability, validity and precision.

Data analysis

Data analysis will involve statistical data analysis, graphical representations and written reports. Both descriptive statistics and other forms of quantitative tests will be used to analyze data collected in this study.

  • Descriptive Statistics: Descriptive statistics typically include statistical measures such as mean, mode, median, variance and standard deviation (Miethe, 2007). Descriptive statistics will be used to analyze data pertaining to dependent and control variables in this study.
  • Bivariate Correlation: The researcher will use Bivariate correlation to analyze the strength of correlation between independent variables and to examine multicollinearity within correlated variables. Since conceptually most variables as used in social science research are related, a high correlation of independent variables may result into problems during data analysis. Bivariate coefficients are interpreted as follows within a range of -1 to 1; a positive value signifies a direct relationship, i.e., an increase in x leads to an increase in y, while a negative value signifies the reverse (Bush, 2009). Zero value signifies a lack of correlation between two independent variables. According to Cohen, West & Aiken (2003), a range of.10 to.30 represents small correlation,.31 to.50 represents medium correlation and.51 to 1.0 represents large correlation coefficient (Bush, 2009).
  • Latent Variable-Partial Least Squared (LV-PLS) regression: LV-PLS is a recently developed statistical technique that shares a common conceptual bond between multiple regression, canonical analysis, and principle component analysis to develop a path analytic method for analysis to develop the relationship between multiple indicator and response variables (Abdi, 2007). Besides, LV-PLS makes it possible to analyze data that is not normally distributed, which may be impossible using traditional data analysis methods (Abdi, 2007). LV-PLS is a sophisticated methodology that examines the relationship between dependent and independent variables that may not normally exist (Abdi, 2007). Using this tool with a big sample of 10000 respondents ensures that the scores are valid and reliable. The researcher finds this technique appropriate in this study since it can account for influences that traditionally confound experimental approaches and where physically impossible to administer randomized controlled conditions to elicit causality in many environments.

Chapter Summary

This chapter discussed the proposed research methodology for the study. A discussion of the research method and design appropriateness, the study population, sampling and data collection procedures, and data analysis procedures together with the rationale for their choice is clearly presented in this chapter. A descriptive quantitative research methodology was identified as the most appropriate research methodology basing its rationale on the nature of the topic under study and the type of data to be collected. A cross-sectional survey design was the most appropriate design based on the wide geographical coverage of the study and the need to collect data in real time emphasized by Neuman (2011) and Wiersma & Jurs (2009). The researcher settled for online survey due to its time and cost effective nature in collecting data over a wide geographical coverage. Sampling procedure involved stratified random sampling to ensure that all the school districts in Florida are included in the study. Using this procedure, the researcher estimated a sample frame of 500 schools translating to 10, 000 respondents. The researcher believed that such a big sample frame would be representative enough. The researcher also settled for Likert survey type of questionnaire as the most appropriate instrument of data collection that will be presented in an online survey. The researcher also identified various techniques of data analysis including Latent Variable-Partial Least Squared, bivariate correlation, and descriptive statistics. The succeeding chapter will involve a comprehensive analysis and presentation of survey data.


Abdi, H. (2007). PLS-Regression. In Neil, S. (Ed.), Encyclopedia of measurement and statistics (pp. 1-13). Thousand Oaks (CA): Sage.

Arnlade, J. A. & Raheem, Y. A. (2008). Teacher’s opinion in the incorporation of environmental education in the Nigerian primary school curriculum. Educational Research and Review Vol. 3(11), pp. 334-338.

Bulmer, M. I. A., Sturgis, P. & Allum, N. (2009). The secondary analysis of survey data. Sage benchmarks in social research methods series. Thousand Oaks (CA).: Sage.

Bush, M. D. (2009). A quantitative investigation of teachers’ responses to bullying. (Unpublished doctoral dissertation). Indiana University of Pennsylvania, Indiana.

Dawes, J. (2008). Do Data Characteristics Change According to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International Journal of Market Research 50 (1): 61–77. justice. LA: Roxbury Publishing Co.

Mabry-Hubbard, R.Y. (2008). Comparing Internet research design methods (IRDM) for American rural populations with telephone survey method. Paper presented at the annual meeting of the Rural Sociological Society, Radisson Hotel- Manchester, Manchester, New Hampshire.

Miethe, T. D. (2007). Simple statistics: Applications in criminology and criminal.

Neuman, W. L. (2011). Social research methods: Qualitative and quantitative approaches (7th ed.). New Jersey: Pearson.

Smith, S. M. & Albaum, G. S. (2010). An introduction to marketing research. Thousand Oaks (CA): Sage.

Wiersma, W. & Jurs, S. G. (2009). Research methods in education: An introduction (9th ed.). Boston: Allyn & Bacon, Incorporated.