3.0 Methodology Chapter
This chapter will outline the research design employed by this study to achieve its research aims. The aims of this research are as follows:
- To explore the role of the SNA in mainstream post-primary PE from the perspective of SNAs and PE teachers.
- To determine whether SNAs can act as facilitators for the inclusion of students with SEN in PE
- To examine the views of SNA’s and PE teachers about the factors that may promote or hinder the inclusion of students with SEN in PE
- To evaluate the need and desire for training for SNAs and PE teachers in developing inclusive practices in PE.
To achieve these aims the study will attempt to answer the following research questions:
- What is the profile of PE Teachers and SNAs teaching in mainstream post primary schools?
- What is the inclusion profile of post primary schools in relation to inclusion of students with SEN?
- What are the current roles and responsibilities of the SNA in mainstream post primary schools, from the perspective of the SNA?
- What factors affect the role played by the SNA in mainstream post primary schools?
- What is the current and desired role of the SNA in enabling the inclusion of students with SEN in post primary mainstream PE from the perspective of the SNA?
- What is the current and desired role of the SNA in enabling the inclusion of students with SEN in post primary mainstream PE from the perspective of the PE teacher?
- Is there a difference between the views of SNAS and Pe teachers in this regard?
- What are the key factors which promote or hinder SNAs having a role in inclusion in PE?
- What are the key factors in enabling the inclusion of students with SEN in PE?
- Is there a demand for the provision of training amongst SNA’s on including children with SEN in PE?
A mixed methods research design was employed, for this research, to answer these questions and included the use of questionnaires, focus groups and interviews. Justification for the use of a mixed methods research design, along with details of the research instruments used and data collection methods followed, will be outlined in depth in this chapter.
This chapter will begin by outlining the theoretical perspective which frames this research.
3.2 Theoretical Research Perspective
3.2.1 Research Paradigm
It is imperative to consider one’s own set of beliefs before commencing any research and deciding on a methodology and related methods, as the researchers world view will undoubtedly effect how the research is undertaken and interpreted (Morgan, 2007). The popularity of paradigms as a way to summarize researchers’ beliefs about their efforts to create knowledge has been directly attributed to Thomas Kuhn’s landmark book titled “The Structure of Scientific Revolutions” (Kuhn, 1962). However within this book the term “research paradigm” was described as many different things and as such was criticized as lacking in clarity by fellow scholar Masterman in 1970. Kuhn went on to discuss the various application of the term “research paradigm” at length in a further “postscript” (Kuhn, 1974) and suggested that depending on the field of study the meaning and applications of the this term can vary, from paradigms as worldviews, as epistemological stances, as shared beliefs among members of a specialty area or as model examples of research (Morgan, 2007), see appendices 3.1 for a detailed description of these four versions of paradigms.
Kuhn defines a paradigm as: “an integrated cluster of substantive concepts, variables and problems attached with corresponding methodological approaches and tools…”. According to him, the term paradigm refers to a research culture with a set of beliefs, values, and assumptions that a community of researchers has in common regarding the nature and conduct of research (Kuhn, 1977).
The most commonly used definition still stems from Kuhn’s original works, with paradigms being described as the set of common beliefs and agreements shared between scientists about how problems should be understood and addressed (Kuhn,1962). It is within this definition however, that a great significance lies on the chosen application of its concept to one’s own research, which is crucial in framing the theoretical underpinning of one’s chosen methodologies. It is also noteworthy to add that the assumptions associated with one paradigm over the other are neither correct or incorrect, but that it is the duty of a researcher to argue the value of their chosen paradigm in relation to the methodologies they employ (Shanks, 2002).
The centrality of a research paradigm includes clarity between “what is to be studied and how the research process is to be carried out” (Denzin & Lincoln, 2005a, p. 183). This section of the methodology chapter will seek to map out this research projects’ process while underpinning it with the philosophical components that make up research paradigms.
220.127.116.11 Key considerations of a research paradigm
The value of the researcher taking the time to reflect upon their own philosophical assumptions of knowledge and placing themselves somewhere within the spectrum of paradigms is vital, because as Denzin and Lincoln (2005) have reminded us, paradigms “are human constructions” that “define the worldview of the researcher” (p.183). In attempting to understand one’s own research paradigm, there are four key considerations to explore:
- Ontology: What is my perception of the nature of reality?
- Epistomology: What is my belief about how knowledge is created and presented?
- Methodology: What is the best means for acquiring knowledge?
- Axiology: What ethics, values and morals are important in acquiring and presenting knowledge?
Ontology concerns the nature of reality, for example, is there a “real” objective world out there, or is reality constructed through human relationships? In research there are two key ontological assumptions, Realism and Nominalism, although perceptions of reality can exist along a continuum between the two. Realists feel that we can ‘gain access to that world by thinking, observing and recording our experiences carefully’ (Moses and Knutsen 2007, p.8) and that reality exists independently of our thinking about it. This type of ontological assumption is more typically aligned with traditional hypotheses testing research. Nominalism conversely, believes that ‘reality is socially constructed, that individuals develop subjective meanings of their own personal experience, and that this gives way to multiple meanings’ (Bloomberg and Volpe 2008, p.9). According to a nominalist assumption it is the researcher’s role to make sense of the reality which has been socially constructed through a process of interpretation of experiences and perceptions of individuals and phenomenon’s. This research aligns itself with that of a nominalist ontological view and attempts to understand the SNAs and PE teachers experiences of inclusion from their own perspectives, rather than believe that there is one singular truth and correct model of inclusion. It seeks, therefore, to use research to give voice to the individuals who make sense of and construct their own realities.
Epistemology is “the study of the nature of knowledge and justification” (Schwandt, 2001, p. 71). Epistomological positions are characterized by a set of assumptions about knowledge and knowing, which provide answers to the question “What and how can we know?” (Willig, 2012). It attempts to answer the basic question of what distinguishes true knowledge from false knowledge and how can we come to find out.
In research “Epistemology is inescapable” (Carter and Little, 2007 pp 1319). It is impossible to engage in the process of knowledge creation without already having some assumptions about what knowledge is and how it is constructed, therefore epistemology theoretically shapes the research either by a researcher actively adopting a theory of knowledge to underpin their studies or by a less reflexive researcher implicitly adopting a theory of knowledge (Carter and Little, 2007). Furthermore epistemology is normative, in that it is the basis for explaining the rightness or wrongness, the admissibility or inadmissibility, of types of knowledge and sources of justification of that knowledge. It is for these reasons that every aspect of a research project contains epistemic content, from the methodology chosen to the methods and to the axiology or ethical decisions made within the research process and interpretation of the research data, see figure 3 for a summary of this interconnected relationship.
There are two basic pillars on the continuum of epistemological assumptions (see figure 4.) although many different terms have been used to label each pillar, for the purpose of this research the terms constructivism and that of empiricism will be used. It must also be noted that as with all philosophical viewpoints on a continuum there are many assumptions which fall between both constructivism and empiricism.
Empiricism views reality as universal, objective, and quantifiable. It assumes that reality is the same for you as it is for me and through the application of science we can identify and ‘see’ what is?shared reality. Within this assumption the individual is reduced to the status of a passive receptacle, as knowledge is seen as static with the role of the researcher being one of objectivity to access the reality and knowledge (Ashworth, 2003).
The basic assertion of the constructionist argument is that reality is socially constructed by and between individuals who experience it (Gergen, 1999) and that reality can be different for each of us based on our unique understandings of the world and our experience of it (Berger & Luckman, 1966). The subjectivity of reality within this epistemological stance is key and the belief that knowledge is adaptive and active – with the role of the researcher being to unveil knowledge as it happens.
An additional empirical stance exists which is positioned slightly between both empiricism and constructivism, called Social constructionism (Berger & Luckman, 1966; Gergen, 1999, 2001a, 2001b). Within this assumption the individual is a sense maker whom seeks to understand or make sense of their world as they see and experience it. Social constructionism allows the unique differences of individuals to come into focus while at the same time permitting the essential sameness that unites human beings to be identified (Ashworth, 2003). In this manner each individual reality is true for the person because he or she experiences it but it is independent of that person due to his or her inability to alter it (Gergen, 1999).
This latter understanding of knowledge as being socially constructed, flexible to the individuals experiences and subject to individual reality is one which this research aligns with. The role of the researcher therefore within this research is to unveil knowledge as it happens with no pre-conceived notions of what form of experiences are expected or unexpected. The constructed knowledge surrounding inclusion in PE will come mainly from reviewing available literature within this field while the constructed insights will come from the perceptions of inclusion experiences collected from those at the center of the research, SNAs and PE teachers, through questionnaires and focus groups and interviews.
As previously stated a researchers epistemology modifies methodology and justifies the knowledge produced through data collection (see Figure 3) (Carter and Little, 2007). A methodology is defined as “a theory and analysis of how research should proceed” (Harding, 1987, p. 2), and it justifies the methods used for data collection within a research project. Methods are “procedures, tools and techniques” of research (Schwandt, 2001, p. 158) which produces data and analyses from which knowledge is created. This research used a mixed methods approach and based on the ontological and epistemological assumptions aligned with this research as outlined above, the focus was on using interpretative qualitative and quantitative methods to explore a broad spectrum of perceived realities surrounding the topic of inclusion in PE and the role of the SNA. It is in this way that this study lends itself nicely to that of a mixed methods study, with an associated paradigm to provide a theoretical framework. This is discussed in more detail in the following section.
Figure 3. The Simple Relationship Between Epistemology, Methodology, and Method (Carter and Little 2007)
As stated briefly above, epistemology also has ethical and values weight. Axiology relates to the values which underlie the way in which research is carried out and interpreted, because undeniably, knowledge that is generated by a project will be discussed and justified in relation to the broader cultural values of the researcher but also of the research context. With an epistemological viewpoint of social constructivism this becomes even more valid, because a researcher who believes that individuals experiences and knowledge are created from social interactions must be very aware of the potential impact of themselves as the researcher within this environment and how their interpretations of the research data could become a “truth” for the participants who are part of the research. The epistemological values which underlie this belief will have consequences on the role the researcher will play in the research and also on the way the data is presented and interpreted. Within this research for example caution had to be taken when conducting the focus groups and interviews not to use leading questions which may guide the participants to provide certain views about inclusion which may be similar to the researchers.
3.2.2 Research paradigm categories
Now that the epistemological and ontological assumptions for the research have been examined, detail will be given in relation to the chosen paradigms which are most aligned with this particular research project.
Flick (2009) attempted to bring some order to the ambivalence which exists in relation to what constitutes a paradigm by describing four categories of paradigms, although he declares that his categorization is by no means definitive. Table 1. displays four of the major paradigms.
Table 1. Four main paradigms and associated methodologies
The next section briefly describes the four main paradigms and assesses their influence on this research.
In early educational and psychological research the main paradigms that dominated studies were positivism and following on from this, post positivism.
The underlying assumption of positivism is that of realism. The perspective of positivism is that knowledge is viewed as being tangible and objective with positivist researchers examining evidence available and making firm and objective conclusions based on that evidence, whilst being mindful that “great precision is necessary on the part of the scientist to verify conclusions” (Emden and Sandelowski, 1999, p.2). Post-positivists rejected the narrow perspective, limiting what could be studied to what was directly observable and whilst they still held beliefs about the importance of objectivity, they believed that researchers should “modify their claims to understandings of truth based on probability, rather than certainty’ (Flick 2009, p.12). As a result of this new paradigm, research methods allowing measurement of phenomenon which were previously considered as being too subjective by positivists emerged. Within this current research the influence of the post positivist paradigm can be seen in the use of questionnaires to measure the perspectives of SNAs and PE teachers in schools across Ireland towards inclusion in PE. For example, the questionnaire data is analysed statistically to provide objective conclusions for the research questions being asked, however the data collected from the questionnaires is very much subjective as it drawn from the perceptions of the SNAs and PE teachers themselves.
Conversely to positivism and post positivism, constructivism, which is rooted in the nominalist philosophy, makes the assumption that knowledge is socially constructed by those active in the research process. The belief is that social reality is subjective and that people organize experiences in order to make them understandable, independently of any foundational reality (Egon, Guba and Lincoln, 2001). Within this paradigm it has been suggested that researchers should attempt to understand the complex world of lived experience from the viewpoint of those who live it (Schwandt, 2000) and seek to comprehend how “the individual created, modifies and interprets the world” (Cohen, Manion and Morrison, 2004, p.7). Within this research project the constructivism approach can be seen in the focus groups and semi structured interviews which were conducted in an attempt to gain further understanding of the research participants lived experiences of inclusion in PE and the role of the SNA.
18.104.22.168 The Transformative Paradigm
Whilst the influences of both the post-positivist and more so the constructivist paradigm have been shown to be evident within this research project, within both of these paradigms the researcher remains external to the research setting and attempts to avoid having any influence over the research setting. Within this research project, although the former attempt to remain uninfluential over the research phenomenon being explored was adhered to for the initial stages of the research (Study 1 phase 1), the advancement from this study was to collaboratively plan and implement a training intervention on inclusion, in an attempt to affect the inclusion practices within PE. This results in the need to branch into an alternative paradigm which has recently emerged to allow the research process to attempt to transform the lives of research participants in some way.
Due to the inadequacy of positivism and constructivism to address social justice issues, the transformative paradigm was founded. A range of transformative paradigms exist with the most relevant to the intervention phase to this research being the critical theory transformative paradigm.
Critical theory progresses to go beyond explain social phenomenon, as with positivism, and past seeking to understand them, such as with constructivism, but rather is sets out to actually change the situation (Cohen, Manion and Morrison, 2010)
In attempting to apply critical transformative theory to this research a number of key features were needed, firstly to understand the lived experiences of people within the context being studied, to examine the social conditions in order to uncover the hidden limiting structures and finally to fuse theory and action to attempt to make a positive change in the observed phenomenon. All of these features can be seen to be evident through the variety of methods applied within this research project.
As exemplified in the above descriptions of paradigms, some assumptions and applications were taken from various paradigms in order to best answer the research questions of this project. It has been suggested that once a researcher does not ignore their own worldview it is not necessary to operate within one single paradigm or conduct paradigm driven research (Cohen, Manion and Morrision, 2004) but rather to focus on the research questions at hand and how to answer them most productively while staying true to your own epistemology.
The mixing of paradigms in this way have been referred to as pragmatism, and it would be most accurate to state therefore that this research project operates primarily within a pragmatic paradigm. Morgan (2007) supports this type of approach to research arguing that a pragmatic approach allows the positive aspects of all paradigms to work together and focuses on the research problem, using whatever methods are necessary to understand and solve the problem. Additional scholars have also advocated for this pragmatic approach stating that it ‘sidesteps the contentious issues of truth and reality and orients itself towards solving practical problems in the real world’ (Feilzer, 2009 p.8).
This research project was undertaken with the stance that both paradigms and methods can be combined in order to ensure that the phenomenon under investigation can be reported in a manner that places the findings of the research and the possible theories that can be generated to the fore. As qualitative and quantitative methods both have positive and negative components it was envisaged that combining both allows for the positive aspects to be maximised and the negative aspect to be minimised.
The following sections will examine theuse of qualitative, quantitative and mixed methods research as well as discussing the data collection methods employed for this research. The current research employed a mixed methods approach.
3.3.1 Qualitative research
Researchers assuming qualitative perspectives are interested in understanding individuals’ perceptions of the world. Qualitative researchers are interested in perceptions of reality and are open to the possibility that people may observe the same thing differently.
Campbell (1997, p.122) defines qualitative research as: “An inquiry process based on building a holistic, complex understanding of a social problem. It is characterized by data collection in a natural setting where the researcher acts as a key instrument. Furthermore, the research contains deep, rich description and is more concerned with process than specifying outcomes or products.”
Qualitative researchers view events through the prism of the people being studied; this is normally achieved through person-to-person interaction. Additionally, Punch draws our attention to another important distinction, which is that ‘qualitative research not only uses non-numerical and unstructured data but also, typically, has research questions and methods which are more general at the start, and become more focused as the study progresses’ (Punch 2005, p28).
3.3.2 Quantitative Research
Creswell (2009) describes quantitative research as ‘a means of testing objective theories by examining the relationship among variables. These variables, in turn, can be measured, typically on instruments, so that numbered data can be analysed using statistical procedures’ (p.4). Quantitative researchers gather facts or data and examine the association of these sets to another (Bell and Waters, 2014). Through the use of structured and predetermined research questions and conceptual frameworks (Punch 2005), they therefore use techniques that are likely to produce quantified and, if possible, generalizable conclusions (Bell and Waters, 2014).
Quantitative approaches are based on a number of assumptions. Firstly, they assume that regularities or patterns in nature exist and that these patterns can be observed and described. Secondly, dividing them into parts and studying those parts using empirical methods can test statements based on these regularities. Thirdly, they assume that it is possible to distinguish between value-laden statements and factual ones (Moses and Knutsen, 2007).
Critics of this approach strenuously challenge most or all of these assumptions. They believe that there are very few absolute ‘facts’ in social science and contend that, even if the world exists independently of the observer, our knowledge of it does not. Cohen, Manion and Morrison (2004) argue that life cannot be defined solely in measurable terms and that the quest for objectivity alienates us from ourselves and from nature. These critics advocate a more qualitative approach to research in social science.
3.3.3 Mixed Methods research
Mixed methods research attempts to respect the multiple beliefs, perspectives and usefulness of both qualitative and quantitative approaches, incorporating the best of both worldviews (Guba and Lincoln, 2005). Creswell (2008) advances a number of strengths of mixed methods research, strengths which render the approach appropriate for this study. Firstly, quantitative and qualitative data together provide a better understanding of the research problem than either type by itself; secondly, one type of research is not enough to answer the research question; and thirdly, from a practical perspective, multiple viewpoints are needed. Another aspect of mixed methods that is appealing, is that one method can develop, inform and complement the other, and thereby mitigate the limitations associated with the primary method. Mixed methods provide greater breadth and depth, which facilitate enhanced description and deeper understanding of the research phenomena (Johnson, Onwuegbuzie and Turner, 2007). Mason (2006) asserts that the fusion of quantitative and qualitative ideas can create data and arguments that can form the basis for well-founded social theory. Greene (2007, p118) contends that “the greatest potential of mixed methods inquiry is the generative possibilities that accompany the mixing of different ways of knowing, perceiving and understanding”.
Having now justified and validated the reasons for employing a mixed methods research methodology,what remains is to make careful consideration around three other factors:
- the timing of the use of collected data
- the relative weight of the quantitative and qualitative approaches
- the approach to mixing the two datasets
These issues will be discussed below in relation to decisions made for this research project.
Timing can also be referred to as sequencing and it refers to the temporal relationship between the quantitative and qualitative components within a research project (Green et al., 1989). Timing is often discussed in relation to the time the datasets are collected but it is more important to consider the order in which the data will be used by the researcher within a study (Morgan 1998). Timing in mixed methods design is classified in one of two ways: concurrent or sequential (Morse, 1991). Within this research project data was collected sequentially with quantitative data being collected first through questionnaires, followed by qualitative data through focus groups and semi-structured interviews. The rationale for doing this sequentially was so the questionnaire data could inform the interview questions asked.
Weighting refers to the relative importance or priority of the quantitative and qualitative methods to answering the research questions, referred to as the “priority decision” (Morgan, 1998). Again there are two options with regard to weighting of data collection measures, equal weighting or priority weighting given to one data collection method. It has been suggested the theoretical worldview used to guide the research project will determine whether the qualitative or quantitative data will get more weighting in the project. In the case of this research it is the quantitative data which is given more weighting with the qualitative data being used in a supporting and explanatory role. See figure 4 to illustrate choice in timing and weighting for mixed methods research design.
Figure 4. Timing and Weighting decisions for mixed methods research design
In relation to mixing of the data, Creswell et al., (2011) identified six separate mixed method research approaches. These include the convergence parallel design, the explanatory sequential design, the exploratory sequential design, the embedded design, the transformative design and the multiphase design.
Sequential mixed methods designs comprise of multiple phases of data collection with the particular sequence being determined by the research purpose (Andrew & Halcomb, 2009). Sequential designs may be either explanatory, in which the quantitative data is collected first followed by the qualitative data, or exploratory, in which the qualitative data is collected first and followed by the quantitative element of the study (Creswell & Plano-Clark, 2007). Andrew and Halcomb (2009) suggest that in explanatory designs the weight is usually, but not always, afforded to the quantitative element of the study, while exploratory designs usually, but not always, affords the weight to the qualitative element of the study.
This research study chose to employ an explanatory sequential design whereby the quantitative data was collected first, in the form of the questionnaires, followed by the qualitative data collection through follow up focus groups and interviews. Within this design, the purpose of the qualitative data is to further explain and interpret the findings from the quantitative data and thus the priority focus is on the quantitative data. For example, the questionnaires in this study were used to collect quantitative data from a large number of SNAs and PE teachers, which would be representative of the general perceptions amongst this population in Ireland. Following on from this, participants who completed the questionnaires were invited for interviews where they could further explain and offer insights into their questionnaire answers.
The rationale that quantitative data would offer a general understanding of a research problem, followed by the qualitative data refining and explaining the statistical results through an exploration of participants’ views, is well documented in the literature (Rossman and Wilson 1985; Tashakkori and Teddlie 1998; Creswell 2003). The strengths of this design include its straightforwardness and the provision of opportunities for the exploration of quantitative results in more detail, while the limitations of the design are that is it is time and resource consuming to collect and analyze both types of data, particularly at different time points (Creswell, Goodchild, and Turner 1996; Green and Caracelli 1997; Creswell 2003, 2005; Moghaddam, Walker, and Harre 2003; Ivankova, Creswell and Stick, 2006). See Appendices 3.3 for the model of data collection and analysis using the Mixed Methods sequential explanatory design.
The rationale for mixing both kinds of data within one study is based on the perception that neither quantitative nor qualitative methods alone would be enough to encapsulate the trends and details of a phenomenon. Using quantitative and qualitative methods together in one study takes advantage of the strengths of each type of data and complements each other to allow for a more thorough analysis. (Ivankoca, Creswell and Stick year; Green, Caracelli, and Graham 1989; Miles and Huberman 1994; Green and Caracelli 1997; Tashakkori and Teddlie 1998).
While the main research question under investigation in this research relates to human experience and thus would seem to most naturally lend itself to qualitative methods such as focus groups and interviews, in order to try to establish an overview of the broader trends in the national population of SNAs and PE teachers working in mainstream post-primary schools, it was necessary to firstly use quantitative methods in the form of questionnaires followed by qualitative methods to provide more in depth insights.
The next section will detail the qualitative and quantitative methods employed during this research.
3.4 Research Methods
It is important for any research study that the methods selected are both adequate to answer the research questions and appropriate for the research methodology being employed. Having reviewed previous and related research studies a combination of questionnaires and follow up focus groups and interviews were deemed the most appropriate methods for use during this research study. Barton and Thomlinson (1981) and Haug (1998) support the use of interviews in order to tackle critically the inherent assumptions and contradictions of research with questionnaires. Therefore, the combination of questionnaires followed by interviews (focus group and semi-structured) allowed the opportunity to answer the research questions and identify themes and issues surrounding the role of SNA’s in PE.
3.4.1 Data Collection Methods
The two data collection methods used for this research were questionnaires and focus groups/interviews.
“A Questionnaire is a method for collecting primary data in which a sample of respondents are asked a list of carefully structured questions chosen after considerable testing with a view to eliciting reliable responses.” (Collis and Hussey, 2014, p.205). Questionnaires can be used in a number of different settings including interviews, by telephone, online and postal. For this research a combination of online and postal questionnaires were used. The questionnaire used in this research was developed by the researcher based on a version of a questionnaire used in Davis et al. (2007) with adaptations made to make the questionnaire more applicable to this particular research environment and context. Other sources which guided the choice of questions on the questionnaire included a review of the literature in the area of inclusion in PE (Sweeney and Coulter, 2008; Chandler & Green, 1995; La Msater, Gall, Kinchin & Siedentop, 1998, Block 2003; Meegan and MacPhail, 2006) along with Department of Education published documents on the role of the SNA in post primary education (DES, 2011)
Two different questionnaires were designed for SNAs and PE teachers with many similar questions on both, using multiple-choice, likert scale and dichotomous (yes/no) questions. Survey Monkey was used for the development of the online version of the questionnaire.
Content validity of the questionnaire was determined by a two-step process consisting of written comments from higher education professionals (n=3) and the completion of a 6-item modified validity rating form (See appendices 3.1 ) by a sample (n=11) of SNAs (Thomas and Nelson 1996).
Focus groups and semi-structured interviews
Focus Groups and Interviews sought to gain further insight into the role of the SNA using the topics from the questionnaire as a guide.
Focus Groups are “used to gather data relating to the feelings and opinions of a group of people who are involved in a common situation or discussing the same phenomenon” (Collis and Hussey, 2014, p.141). Using interview style techniques groups of participants are encouraged by a group leader or researcher to discuss their opinions on selected topics. The advantage of focus groups as opposed to interviews is the addition of the effect that the group interaction can have on topics being discussed, for example through listening to others views being expressed participants can be stimulated to voice their own opinions, which they may not have done without this group interaction (Morgan, 1997). The purpose of a focus group is not to obtain data which can be generalized about a whole population but rather to obtain as full a range of perceptions about a specific phenomenon. Within this research the focus groups aimed to provide additional insights and depth to the findings of the questionnaires and so the questions and topic chosen were based on findings that were considered important and pertinent to the study from the questionnaire data.
Interviews are a method of collecting information from selected participants through asking questions to find out what they do, think or feel. Under an interpretivist paradigm interviews seek to explore “data on understandings, opinions, what people remember doing, attitudes, feelings and the like, that people have in common” (Arksey and Knight, 1999, p.2) and will be unstructured or semi structured (Collis and Hussey (2014). During interviews open questions which require longer and more developed answers, rather than yes/no answers, can be used, or closed questions which require very brief factual answers. Within this research semi structured interviews were conducted, whereby participants were encouraged to talk about specific topics of interest through the use of open ended questions but allowed for other questions to emerge during the course of the interview depending on the responses given by the participants. Probing questions also formed an important part of the interview to ensure the participants elaborate on statements which they make that may be of particular interest to the research question.
As with all data collection methods, interview and focus groups have some potential problems which the researcher must be aware of. One such problem which can occur is social desirability bias, whereby participants will answer in the way they feel the researcher would like them too, (Collis and Hussey, 2014). Another common problem with focus groups is having one participant who is overly dominant, making it difficult for others to express their opinions. The role of the researcher here is vital in firstly explaining the way in which the focus group will be conducted to all participants prior to its commencement and secondly by maintaining control of the group and encouraging all participants to contribute throughout. Being aware of these potential problems prior to data collection is vital for the researcher in order to conduct the focus groups and interviews to the highest standard.
3.4.2 Research Participants and research protocol
Questionnaires were posted to all mainstream post-primary schools in Ireland who employed SNAs according to the NCSE School Allocations List from 2012/13 (See Appendices 3.2) (n=732 Schools, n=2019 SNA’, n=1100 PE Teachers). These questionnaires were addressed to SEN Co-ordinators in each school. Links to an online version of the questionnaire were also emailed to the schools and to SNA union groups. Follow up phone calls were made to SEN Co-ordinators in the schools two weeks after initially sending the questionnaires in an attempt to increase response rate.
It has been suggested in the literature (Fincham, 2008) that taking this multi-mode approach to questionnaire data collection may yield greater response rates, with a study carried out by Yun and Trumbo (2000) receiving a response rate of 72% with such an approach. Response rate is “defined as the number of respondents divided by the number of eligible subjects in the sample” (Draugalis, Coons, & Plaza, 2008, p11). Despite taking this multi-mode approach and using follow up procedures, the response rate for this research remained relatively low, with just 16% of the SNA population responding (n=330 SNAs) and 18% of the sampled PE Teachers (n= 193 PE Teachers). A low response rate to questionnaires by potential respondents in a population can result in nonresponse bias which can have a negative effect on the reliability and validity of questionnaire study findings (Fincham, 2008).
Whilst the literature available does not seem to set a minimum acceptable response rate, Draugalis, Coons and Plaza (2008) reviewed articles from 2005 and 2006 and reported that 35% of survey research papers had response rates less than 30%, 30% had response rates between 31%-60%, and 35% had response rates of 61% or greater.Cook et al have noted that: “Response representativeness is more important than response rate in survey research. However, response rate is important if it bears on representativeness.”(Cook et al, 2000, p.821).
Representativeness refers to how well the sample drawn for the questionnaire research compares with the population of interest (Fincham, 2008). Within this study it can be stated that the population of interest is well represented based on comparisons of the demographics of the participants which were reported (Location, Age, Gender) in this study, with that of other research on this population. The results section will outline these comparisons in more detail. Based on this, whilst non response bias must be considered in the interpretation of the questionnaire data collected, it would seem accurate to suggest that the data will provide a reliable representation of the greater population of SNA’s and PE teachers? with whom this study is interested.
Follow up Focus Groups (n=4) and Semi structured interviews (n=6) were conducted with a total of 29 SNAs who had completed the questionnaires. All SNAs who participated in the questionnaire research were contacted by email and invited to take part in the follow up focus groups and interviews. These focus groups and interviews added depth to the questionnaire results and allowed for themes and topics arising from the questionnaire data to be further explored.
3.4.3 Data Analysis
This research employed a mixed methods design using quantitative approaches to analyse the questionnaire data and qualitative approaches to explore the themes from the focus groups and interviews. As stated previously the quantitative analysis took place initially followed by the qualitative data analysis. The questionnaire data was inputted into Statistical Package for the Social Sciences (SPSS) and was screend and cleaned before being analysed using descriptive statistics, including frequency and percentage response distributions and measures of central tendency, and inferential statistics, including T-tests, Regression Analysis and Pearsons correlations. Using the initial descriptive statistics analysis of the questionnaire data, interview topics were chosen for the qualitative stage of the data collection. The interviews and focus groups were audiotaped and transcribed verbatim before being entered into Nvivo software, where the data was coded and analysed using thematic analysis with an emphatic interpretation orientation. Verification procedures as per Ivankova, Creswell and Stick, (2005) were followed including; member checking, intercoder agreement, rich and thick descriptions of the cases, reviewing and resolving disconfirming evidence, and academic adviser’s auditing.
The methods of data analysis used and the procedures followed will be outlined in greater detail below.
22.214.171.124. Quantitative Data Analysis
The questionnaire data was analysed quantitatively using Statistical Package for the Social Sciences (SPSS). Statistics is a branch of science that deals with the collection, organisation, analysis of data and drawing of inferences from the samples to the whole population (Winters, Winters and Amedee, 2010) Descriptive statistics try to describe the relationship between variables in a sample or population. Descriptive statistics provide a summary of data in the form of mean, median and mode. Inferential statistics use a random sample of data taken from a population to describe and make inferences about the whole population. It is valuable when it is not possible to examine each member of an entire population (Satake , 2015).
Data from the questionnaires were tested using both parametric and non-parametric tests depending on the variables being analyzed. Parametric tests were used to analyse numerical data that are normally distributed. The two most basic prerequisites for parametric statistical analysis are:
- The assumption of normality which specifies that the means of the sample group are normally distributed
- The assumption of equal variance which specifies that the variances of the samples and of their corresponding population are equal. (Altman 2009).
However, when the assumptions of normality are not met, and the sample means are not normally distributed, parametric tests are used. Non-parametric tests are also used to analyse ordinal and categorical data. Non-parametric tests may fail to detect a significant difference when compared with a parametric test (Nahm, 2016).
Statistical tests were conducted to measure for relationships, differences, and inferred causality between the variables.
To test the data for relationships between selected variables, Pearsons Correlations and Multiple Regression Analysis was conducted.
The independent paired t-test was used to measure for significant differences between independent samples. The formula for unpaired t-test is:
where X1 − X2 is the difference between the means of the two groups and SE denotes the standard error of the difference.
Chi-square test was used to analyse the categorical or nominal variables, comparing the frequencies to see whether the observed data differed significantly from that of the expected data. It is calculated by the sum of the squared difference between observed (O) and the expected (E) data (or the deviation, d) divided by the expected data by the following formula:
Logistics Regression was also used to test the odds of an event occurring based on one or more predictor variables.
126.96.36.199 Qualitative Data Analysis – Thematic analysis
Qualitative data analysis has been described as the “central step” in qualitative research, and in many ways forms the outcomes of the research (Flick, 2013). Defined as “the classification and interpretation of linguistic (or visual) material to make statements about implicit and explicit dimensions and structures of meaning-making in the material” (Flick, 2013), qualitative data analysis aims to describe, compare and explain selected phenomenon’s and potentially develop theories based on these acquired analysis.
Interpretation is a key component of qualitative research and without it we cannot make sense of or derive any true meaning from the data (Willig, 2013). Different interpretations of the same data can be generated as a result of asking different questions of it, which highlights the impact that a researchers ontological and epistemological positions have on the data analysis due to the effect they have on the interpretation orientation selected. The two different interpretation orientations are stated as being suspicious interpretation and emphatic interpretation.
Suspicious’ interpretation aims to reveal hidden truths and to unmask that which presents itself, to bring out latent meaning which is contained within but not immediately obvious in the data. It is necessary to have theoretical concepts to interrogate the data using this approach.
Emphatic interpretation seeks to elaborate and illuminate the meaning which is contained within the material by paying special attention to its features and qualities and making connections, noticing patterns and identifying relationships. ‘Empathic’ interpretations are very much grounded in the data and do not set out to explain why something occurs or to identify a causal mechanism underpinning the phenomenon but rather to amplify what the data is saying (Willig, 2013).
The interpretive orientation taking place? with the data analysis in this research was an emphatic one, with the purpose of the qualitative data being to give voice to the data and provide further insight into the perceptions of the research participants surrounding the phenomenon being explored.
As stated previously the data analysis method used for the qualitative data was thematic analysis. Thematic analysis refers to the process of identifying themes in the data which capture meaning that are relevant to the research question and identify patterns in the data (Braun and Clarke, 2006). Through its theoretical freedom, it has been stated that thematic analysis provides a flexible research tool, which can provide a rich account of data. (Braun and Clarke, 2006).
Themes or patterns within data can be identified in one of two primary ways : in an inductive or “bottom up‟ way, or in a theoretical or deductive or “top down‟ way. Inductive analysis is a method of coding the data without trying to fit it into a pre-existing coding or research question driven framework. In this sense, this form of thematic analysis is data driven. In contrast, a “theoretical‟ thematic analysis would tend to be driven by the researcher’s theoretical or analytic interest in the area, and is thus more explicitly analyst-driven. This form of thematic analysis tends to provide a less rich description of the data overall, and more a detailed analysis of some aspect of the data. The choice between inductive and theoretical approaches also affects whether the researchers codes for a quite specific research question (which maps onto the more theoretical approach) or the specific research question evolves through the coding process (which maps onto the inductive approach) (Braun and Clarke, 2006). For the purposes of this research a theoretical approach was used to develop themes from the data, using the research questions, existing literature and the quantitative data results as the analytical guide.
The six phases of conducting thematic analysis as outlined by Braun and Clarke (2006) were followed as the procedure for analyzing the data in this research, see table below for an outline of these phases.
- Altman, D.G. (2009). Bland JM. Parametric v non-parametric methods for data analysis. BMJ.;338:a3167
- Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60(9), 662–669. http://doi.org/10.4103/0019-5049.190623
- Ashworth, P. (2003). The origins of qualitative psychology. In J. Smith (Ed.), Qualitative psychology: A practical guide to research methods. Thousand Oaks, CA: Sage.
- Berger, P., & Luckman, T. (1966). The Social Construction of Reality. Middlesex: Penguin Books Ltd.
- Bell, J. and Waters, S. (2014) Doing Your Research Project: A Guide For First-Time Researchers. Sixth edition . Great Britain; Open University Press.
- Carter, S.M. and Little, M. 2007. Justifying knowledge, justifying method, taking action: Epistemologies, methodologies, and methods in qualitative research. Qualitative Health Research, 17(10),
- Campbell, T. (1997). Technology, Multimedia, and Qualitative Research in Education. Journal of Research on Computing in Education. 30(2) pp 122-132.
- Cohen, L., Mannion, L and Morrison, K. (2007), 7th ed. Research Methods in Education. New York: Routledge
- Cohen, L., Manion, L. and Morrison, K. (2004). Research Methods in Education (sixth edition).London: Routledge Falmer.
- Cook C, Heath F, Thompson RL (2000). A meta-analysis of response rates in web- or internet-based surveys. Educ and Psychol Meas. 60(6):821–36.
- Creswell, J.W. and Plano Clark, V.L. (2007). Designing and conducting mixed methods research. Thousand Oaks, Calif: SAGE Publications.
- Collis, J. and Hussey, R. (2014). Business Research. A Practical Guide for undergraduate and postgraduate students. Cornwall: Palgrave Macmillen.
- Department of Education and Skills 2011. The special needs assistant scheme a value for money review of expenditure on the special needs assistant scheme.
- Draugalis, J. R., Coons, S. J., & Plaza, C. M. (2008). Best Practices for Survey Research Reports: A Synopsis for Authors and Reviewers. American Journal of Pharmaceutical Education, 72(1), 11.
- Emden, C. & Sandelowski, M. (1999). The good, the bad, and the relative, part 2:
- Feilzer, M. (2009). Doing mixed methods research pragmatically: implications for the rediscovery of pragmatism as a research paradigm. Journal of Mixed Methods Research. 4 (1), pp 6-16.
- Flick, U. (2013). Mapping the field. In U. Flick, The Sage handbook of qualitative data analysis. London, UK: Sage UK.
- Fincham, J. E. (2008). Response Rates and Responsiveness for Surveys, Standards, and the Journal . American Journal of Pharmaceutical Education, 72(2), 43.
- Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11, 255–274.
- Gergen, K. (1999). An invitation to social construction. London: Sage.
- Gergen, K. (2001a). Construction in contention: Toward consequential resolutions. Theory and Psychology, 11 (3), 419-432.
- Gergen, K. (2001b). Psychological science in a postmodern context. American Psychologist, 56(10), 803-813.
- Ivankova, N.V., Creswell, J.W., and Stick, S.L. (2006) Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice. Field Methods; 18; 3
- Kuhn, T. (1996). The structure of scientific revolutions (3rd ed). Chicago: University of Chicago Press. (Original work published 1962)
- Linda Dale Bloomberg & Marie F. Volpe (2008). Completing Your Qualitative Dissertation: A Roadmap From Beginning to End. Los Angeles, London: Sage Publications
- Morgan, D. L. (1998). Practical strategies for combining qualitative and quantitative methods: Applications to health research. Qualitative Health Research, 8, 362–376.
- Morgan, D.L. (1997) Focus Groups as Qualitative Research, 2nd Edn. Thousand Oaks, CA: Sage.
- Morgan, D.L. (2007). Paradigms lost and pragmatism regained: methodological implications of combining qualitative and quantitative methods. Journal of Mixed
- Methods Research. 1 (1), pp 48-76.
- Moses, J. and Knutsen, T. (2007). Ways of knowing: competing methodologies in social and political research. New York, NY: Palgrave Macmillan.
- Nahm, F.S. (2016). Nonparametric statistical tests for the continuous data: The basic concept and the practical use. Korean J Anesthesiol. 69:8–14
- Satake, E.B. (2015). Statistical Methods and Reasoning for the Clinical Sciences Evidence-Based Practice. Ist ed. San Diego: Plural Publishing, Inc; pp. 1–19.
- Schwandt, T. (2003). “Back to the rough ground!” Beyond theory to practice in evaluation. Evaluation. 9 (3), pp 353-364.
- Schwartz, C. and Struhkamp, G. (2004)’ ‘Does Evaluation Build or Destroy Trust?’ Paper given at the 6th Conference of the European Evaluation Society. Berlin, 30 September-2 October
- Schwandt, T. (2000) Further diagnostic thoughts on what ails evaluation practice. The American Journal of Evaluation. Volume 21, Issue 2, Spring–Summer, Pages 225–229
- Shank, G. D. (2002). Qualitative research: a personal skills approach. Prentice Hall, Columbus, Ohio, USA.
- Willig, C. (2012). Perspectives on the epistemological bases for qualitative research. IN: Cooper, H (eds.) American Psychologist Association Handbook of Research Methods in Psychology: Vol 1. Foundations, Planning, Measures and Psychometrics.
- Winters, R., Winters, A., Amedee, R.G and Ochsner, J. (2010). Statistics: A brief overview.10:213–6
- Yun GW, Trumbo CW. Comparative response to a survey executed by post, e-mail, & web form. J Compu-Mediated Com. 2000:6. Available online at: http://jcmc.indiana.edu/vol6/issue1/yun.html Accessed April 1, 2008.
3.1 Four versions of Paradigms (Morgan 2007)
3.2 6-item modified validity rating form
3.3 NCSE SNA Allocation 2012/13
3.4 Mixed Methods Sequential Explanatory Design
3.1. 6-item modified validity rating form
3.2 NCSE SNA Allocation 2012/13
3.3 Mixed Methods Sequential Explanatory Data Collection and Analysis Design.
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