Research Philosophy
The present research study uses a positivist research philosophy to investigate the effectiveness of alternative teacher certification programs in education.
This philosophy views research in social science as a form of scientific explanation, or as an organised method for combining deductive logic with accurate empirical observations of individual behaviour with the view to discovering and confirming a set of probabilistic causal laws that can then be used by the researcher to predict or envisage general patterns of human behaviour (Neumann, 2003).
Bryman (2008) posits that the knowledge that develops through a positivist research orientation is embedded in thorough observation and measurement of the objective reality that exists “out there” in the world, and that can only be possible through the development of valid measures of observations for use in studying or evaluating the main issues of concern to the researcher.
In the context of the present study, it is more appropriate to use a positivist research philosophy than an interpretivist research philosophy as the former allows the researcher to:
- collect specific empirical data on the effectiveness of alternative teacher certification programs in the district,
- develop specific sets of hypotheses and operationalise them based on the main issues of interest to the study,
- empirically test the hypotheses with the intention to corroborating existing relationships between the main issues of interest to the study.
However, unlike interpretivism or social constructivism, positivism as a research philosophy lacks the rigour to describe a phenomenon, construct propositions, as well as identify structures and interactions between complex mechanisms (Mesel, 2013; Zachariadis, Scott, & Barett, 2013).
Research Approach
The present study uses a quantitative research approach, which is usually associated with an empiricist/positivist research paradigm and a survey method of data collection (Weaver & Olson, 2006).
Available research methodology scholarship defines the quantitative research approach “as a type of empirical research into a social phenomena or human problem, testing a theory consisting of variables which are measured with numbers and analysed with statistics in order to determine if the theory explains or predicts phenomena of interest” (Yilmaz, 2013, p. 312).
On their part, Lee and Hubona (2009) argue that quantitative research is basically an approach for testing objective theories by investigating the relationships between issues and variables considered to be of critical concern to the study using rigid rules of logic and measurement, truth, absolute principles and prediction as allowed in a positivist research philosophy.
In the context of the present study, a quantitative research approach is more appropriate than qualitative or mixed methods research approaches, as it allows the researcher to not only effectively test the stated hypotheses through empirical or statistical means, but also respond to the underlying research questions by using numbers (statistics) to investigate the relationship between variables of interest to the study (Creswell, 2009).
Another advantage of the quantitative research approach lies in its capacity to provide the researcher with a broad analysis of the main issues under investigation; however, the approach is unable to focus on the operation of social processes in a greater depth than a qualitative research approach (Griffin, n.d.).
Research Strategy
This particular study uses a cross-sectional (survey) research design because the sampled study participants are contacted at a fixed point in time to collect data using two sets of standardised survey questionnaires (Balnaves & Caputi, 2001).
Available research methodology scholarship demonstrates that a survey research is appropriate in the present study as it avails “a quantitative or numeric description of trends, attitudes, or opinions of a population by studying a sample of that population” (Creswell, 2014, p. 13).
Consequently, the survey research design is appropriate than other designs (e.g., case studies, longitudinal designs and experimental designs) as it enables the researcher to not only investigate the effectiveness of alternative teacher certification programs in the district at a particular point of time, but also to use less financial resources and time in studying a sample rather than the whole population.
Additionally, a cross-sectional research strategy is easy to apply, demonstrates adequate capacity to be descriptive, and enables the researcher to collect data that is broader in scope.
However, unlike other research designs such as case studies and experimental designs, the cross-sectional research design is unable to make inferences about processes that occur over time, implying that it cannot demonstrate causality (Balnaves & Caputi, 2001).
Population and Sampling
Creswell (2014) defines “population” as a group of individuals or things of interest that a researcher intends to examine or explore with the view to meeting the study objectives and providing answers to the key research questions. Following this definition, the target population in the present study includes education officials as well as teachers residing in the school district.
The researcher employs nonprobability sampling techniques, in large part due to the nature of information required to investigate the effectiveness of alternative teacher certification programs in the school district.
Specifically, purposive sampling technique is used to select a sample of 50 education officials within the school district who are well versed with the alternative teacher certification programs, while convenience sampling technique is used to select a sample of 150 teachers from the school district.
In the context of this study, purposive sampling technique is appropriate than other probability sampling techniques such as simple random sampling due to its capacity to allow the researcher to gain an in-depth and holistic understanding of alternative teacher certification programs, as a purposive sample is selected or “handpicked” based on the participants expansive knowledge of issues that are of primary concern to the researcher (Sekaran, 2006; Vogt, 2007).
Consequently, the purposive sample of education officials is essential in facilitating the researcher to gain an in-depth and holistic understanding of the effectiveness of alternative teacher certification programs in education.
However, unlike some probability sampling techniques such as simple random sampling and stratified random sampling, purposive sampling is costly to administer in terms of finances and time, not mentioning that a purposive sample is not always representative of the population (Teddlie, 2007).
Convenience sampling technique is used in the sampling of teachers as it is not only easier to administer, but is less expensive than other sampling procedures and helps the researcher in the gathering of important data that would not have been possible using probability sampling techniques (Vogt, 2007).
However, unlike some probability sampling techniques such as sample random sampling, convenience sampling may not result in a representative sample and suffers from several biases including underrepresentation or overrepresentation of particular groups within the sample (Teddlie, 2007).
Methods of Data Collection
The present study draws on quantitative data collected by means of standardised questionnaire schedules administered to the sampled education officials and teachers within the school district. Available methodology literature defines questionnaires as “fixed sets of questions that can be administered by paper and pencil, as a Web form, or by an interviewer who follows a strict script” (Harrell & Bradley, 2009, p. 6).
The present study uses online means to send the questionnaires to participants for completion and onward submission through the same protocols, hence the need to provide participants with sufficient time to respond to the self-administered, web-based questionnaires without the assistance of the researcher (Potter, 2003).
Of the two questionnaire sets prepared for the purpose of collecting data, one set containing a combination of numerical questions, Yes and No questions, closed-ended questions and a few open-ended items is administered to the education officers, while the other set containing similar items is administered to the sampled teachers.
It is important to note that both questionnaires are divided into two sections: the first section is concerned with collecting the demographic information of participants, while the second section mostly contains questions asking participants to identify their level of agreement with a number of statements presented in the questionnaires using a five-point Lickert-type scale (“1=strongly disagree”; “2=disagree”; “3=neither agree nor disagree”; “4=agree”; “5=strongly agree”) with the view to investigating the effectiveness of alternative teacher certification programs in the school district.
The use of the Lickert-type scale in the two questionnaires is consistent with the quantitative research approach which, according to Gelo, Braakmann, & Benetka (2008), “requires the reduction of phenomena to numerical values in order to carry out statistical analysis.”
Drawing from this elaboration, it is evident that the use of a Lickert-type scale in the data collection process is justifiable as it allows survey participants to quantify their preferences, thoughts, and attitudes on the effectiveness of alternative teacher certification programs within the school district (Fowler, 2008).
Overall, the web-based self-administered questionnaires used in this study are appropriate than other data collection techniques such as interviews and focus groups due to a number of reasons, namely low administration costs, wider geographical reach, capacity to provide greater anonymity for participants due to absence of the interviewer, low training requirement for the person administering the schedules, and capacity to reduce bias that is often caused by interviewer characteristics or variability in interviewer skills.
However, unlike qualitative data collection methods such as interviews and focus groups, questionnaires are unable to achieve a high participant response rate, are unable to capture complex and ambiguous questions due to the absence of the researcher, and are also unable to probe participants further as most items are closed-ended (Harrell & Bradley, 2009; Marsden & Wright, 2010; Nicholas & Childs, 2009; Potter, 2003).
Validity and Reliability
Available literature demonstrates that validity implies the degree to which a particular measure is effective in measuring what it is supposed to, while reliability implies the degree or level to which a test or procedure is able to generate similar results under constant conditions on all occasions (Bryman & Bell, 2008; Punch, 2009).
Following these definitions, reliability of the study findings (e.g., consistency of results among participants, consistency of the study results across uses) has be guaranteed through:
- standardising the questionnaire schedules,
- documenting shifts or progress regularly,
- ensuring the stability of the Lickert-type scale and other scales used in the questionnaires.
On the other hand, the validity of the study results (e.g., establishing relationships between different study variables and generalising the results to other contexts) has been guaranteed by:
- using available literature on alternative teacher certification to structure the questions in the standardised questionnaire sets with the view to ensuring their relevance and representativeness,
- comparing the questionnaire instruments to other similar validated measures used in measuring the effectiveness of alternative teacher certification programs,
- establishing the correct operational measures for the theoretical concepts under investigation through successfully linking the items contained in the questionnaire sets to the study’s objectives, research questions, and hypotheses (Bryman & Bell, 2008; Punch, 2009).
Ethical Considerations
Ethical considerations form an important component of any research process, with available methodology scholarship demonstrating that ethical issues arise in any research study using human subjects as the investigator is expected to “ ensure that no harm occurs to the voluntary participants and that all participants have made the decision to assist after receiving full information as to what is required and what, if any, potential consequences may arise from such participation” (Polonsky & Waller, 2010, p. 69).
In this particular study, the researcher has:
- sought for written permission from the district education department and relevant schools to be allowed to engage the participants in data collection,
- ensured that any participation in the research study is voluntary, and that the sampled teachers and education officials taking part in the study have been provided with adequate information to make informed choices,
- ensured the teachers and education officials fully understand what they are being asked to do and are abundantly informed of any potentially negative consequences arising from such participation,
- guaranteed individual confidentiality and anonymity of participating teachers and education officials,
- facilitated the debriefing of participating teachers and education officials, including using online means to share with them the study findings (Gregory, 2003; Polonsky & Waller, 2010).
Data Analysis
In the present study, completed questionnaires returned from the participants are cleaned, coded, and entered into the Statistical Package for Social Sciences (SPSS) for analysis and interpretation of the results. The two major techniques used to analyse data in this study include descriptive statistics (univariate analysis) as well as inferential statistics with a focus on analysis of variance (ANOVA) and correlation analysis (p).
The study findings are synthesised, harmonised, and presented using various formats, including normal text, descriptive tables of means and standard deviations, frequency distribution tables, bar graphs, pie charts, as well as correlation tables.
It is important to note that the advantages of using descriptive statistics include:
- capacity to gather, organise, and compare huge amounts of discreet categorical and continuous non-discreet (numerically infinite) data in a more manageable form for easier interpretation of results,
- capacity to be employed in systematic observations of central tendency in order to describe subject data information in a manner that is less subjectively assessed by others,
- capacity to identify with ease discreet or finite categorical variables, including participants’ gender, age in completed years, educational level, and certification status (Connolly, 2007; Treiman, 2008).
Lastly, the justification for using ANOVA and correlation statistics lies in the capacity of the two data analysis techniques to:
- avail more comprehensive information than is the case with descriptive statistics,
- yield significant insights into relationships between issues of interest,
- make predictions between causes and effects,
- generate convincing support for a given theory or the main issues being investigated in the research study (Runyon, 2010).
References
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