Teoría de la mente básica y avanzada Estudios con

The most frequent categorisation of research distinguishes quantitative from qualitative methodologies (Creswell, 2014; David & Sutton, 2011). Data can be categorised as qualitative if they are presented in word form and depict circumstances, people or situations related to a certain phenomenon, and as quantitative when they are presented as precise figures, calculations or measurements with a number of interpretations (Blaxter, Hughes, & Tight, 2010; Huberman & Miles, 2002). The two approaches also have different theoretical and epistemic roots. According to Ray (1994) and Tayie (2005), completely different philosophical assumptions and drives lead to different targets and different research procedures. Broadly, quantitative research tends to be associated with the positivist paradigm, while qualitative research is usually constructivist (Gall et al., 2007; Newman, Newman, & Newman, 2011; Plano Clark & Creswell, 2008). These two paradigms make assumptions concerning the social realm. They also provide insights into how knowledge should be fashioned or experienced and

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what counts as real issues, explanations and evidence. Table 4.1 compares them according to six philosophical criteria.

Table 4.1: Comparison between positivist and constructivist paradigms

Criterion Positivism Constructivism

Methods Quantitative Qualitative

Ontology (nature of reality)

Reality is single, tangible and fragmentable

Realities are multiple, constructed and holistic

Epistemology

(relationship of the knower to the known)

Objective:

Knower and known are independent, a dualism

Subjective:

Knower and known are interactive, inseparable

The possibility of generalisation

Time- and context-free generalisations are possible

Time-free and context- bound working

hypotheses are possible

The possibility of causal linkage

There are real causes, temporally precedent to or simultaneous with effects

Impossible to

distinguish causes from effects

Principally oriented to the role of theory in relation to research

Emphasises the deductive approach, i.e. on a priori hypotheses or theory

Emphasises the

inductive approach, e.g. ‘grounded theory’

Axiology (The role of values)

Inquiry is value-free Inquiry is value-bound Adapted from Lincoln & Guba (1985), Tashakkori & Teddlie (1998)

4.4.1 Quantitative approach

A quantitative study can be defined as “an inquiry into a social or human problem, based on testing a theory composed of variables, measured with numbers, and analysed with statistical procedures, in order to determine whether the predictive generalizations of the theory hold true” (Creswell, 1994, p.2). According to Bryman (2012), quantitative research employs a particular language largely to clarify how scientists go about examining natural variables, controls, measurements and experiments. Gall et al. (2007) describe quantitative methodology as an analysis based on the postulation that aspects of the social environment comprise an unbiased reality that is comparatively persistent across time and contexts. The overriding methodology is to define and elucidate aspects of this reality by gathering and analysing statistical data on performance and conduct.

Bell (2010) indicates that in quantitative research, facts are gathered in order to examine the association of one group of facts to another, using methods which may

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generate quantifiable and sometimes generalisable findings. Thus, the quantitative paradigm was useful in this study to obtain sets of facts in a consistent form about teachers’ demographic profiles and their feelings about job satisfaction and motivation. These could be studied in detail to measure the frequency of specific opinions and of the likelihood of associations between variables, for instance if perceptions varied with a particular demographic variable such as age. Another use for this approach was for the examination of the relationship between motivation and job satisfaction. It also allowed the researcher to investigate a sizable sample; indeed, one of the major benefits of quantitative research is that it enables the possible measurement of the responses of a large number of people to a limited number of questions, which can facilitate data comparison and statistical aggregation (Patton, 2002). Quantitative findings can be subjected to a wide range of statistical approaches (Baker & Charvat, 2008; Rubin & Babbie, 2013). Therefore, quantitative methods can yield a comprehensive, parsimoniously presentable and generalisable set of findings.

As to their weaknesses, Baker and Charvat (2008) argue that quantitative instruments can have low response rates. The design of quantitative research can also be more challenging than qualitative research, as it initially needs a more categorical description of the kinds of data to be gathered. Nevertheless, once collected, quantitative data can be more straightforwardly analysed (Verma & Mallick, 1999).

The advantages of the quantitative approach set out above make it suitable to address the present research questions. The researcher also received advice from the Saudi MoE that in Saudi Arabia the quantitative approach to social science research is generally preferred, as statistical data would make a particularly useful contribution to the Ministry’s future decision-making. He therefore deemed it appropriate to conduct a quantitative survey.

4.4.2 Qualitative approach

The qualitative approach can be defined as an investigative procedure to understand a social or human issue, on the basis of constructing a multifaceted, rounded picture, shaped with words, recording detailed ideas and opinions of subjects, and carried out in a natural location (Creswell, 2014). Qualitative research normally investigates small groups of people, who provide explanations for purposes and meanings, as well as

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activities. According to Rubin and Babbie (2013) and Williams (2003), qualitative methods include unstructured, detailed interviewing, group interviews and observation.

Qualitative methods offer a rich, in-depth examination of chosen social or educational issues, providing valuable insights and understanding of problematic areas. Qualitative researchers seek to understand individuals’ feelings and views of the world around them. In other words, they seek insights instead of statistical information and are concerned with achieving a more detailed understanding of human behaviour and its underlying motives than a ‘scientific’ methodology can offer (Bell, 2010; Solomon & Draine, 2010). Qualitative research highlights how and why people behave in a certain manner; it is flexible, as the researcher has the opportunity to alter questions in the process of data collection; and its findings are easier for general readers to understand, being less formal and statistically focused (Hancock, 1998). Thus, qualitative research can comprise richer meanings and contents than quantified data (Babbie, 2013; Rubin & Babbie, 2013). One of the major aims of the present study was to investigate the key issues underlying factors of teachers’ job satisfaction and motivation; a qualitative approach was considered useful in explaining them in depth. Keats (2000) suggests that qualitative interviews can effectively identify the factors and motivations behind the perceptions and beliefs of individuals.

However, the qualitative approach also has drawbacks and has been critiqued for being able to support only small-scale projects and not being generalisable, for being dependent on the personal explanations of researchers, for not allowing reproduction by other investigators, for requiring time-consuming data collection and for subsequent difficulties with its analysis (De Vaus, 2014; Fellows & Liu, 2008). In order to mitigate these limitations and those of the quantitative approach, while enjoying as many as possible of the advantages of both, the researcher chose to adopt mixed methods. The next section discusses the ways in which qualitative and quantitative methods can be successfully combined and meticulous attention paid to the issue being investigated.

4.4.3 Mixed methods

In mixed-method research, “the researcher mixes both qualitative and quantitative research approaches within one stage of the study or across two of the stages” (Mishra, (2005, p.261). Gary (2009) states that quantitative and qualitative methods may be utilised interdependently and in a variety of sequences. They can also be used

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independently, concentrating either on one main research question or on various questions. Design selection will depend on the types of research question posed and on how the mixing of methods can add features to the study at hand.

While each approach has its limitations and benefits, their combination not only acknowledges the significance of conventional quantitative and qualitative research, but also provides a dominant third model that will frequently offer the most instructive, comprehensive, well-organised and beneficial research findings (Johnson & Christensen, 2007). The mixed-method researcher is less likely to leave out key findings or commit errors while using the combined paradigms. A number of authors consider this kind of research more precise and its outcomes more credible. For instance, utilising mixed methods can be viewed as empowering the research and filling the gaps of single-approach methods (David & Sutton, 2011; Johnson & Christensen, 2011; Creswell & Plano Clark, 2011). Furthermore, mixed methods are employed as part of a development procedure to allow the researcher to construct strong, effective, dependable measurement instruments and to confirm the findings, which can result in greater understanding (Bryman, 2012; David & Sutton, 2011). Williams (2003) suggests that a mixed-method study is more likely than a single method to answer the research questions; it offers stronger interpretations in most cases and facilitates the investigation of a wider variety of conflicting viewpoints (Teddlie and Tashakkori, 2003).

As to its limitations, the mixed-method approach may involve lengthy data collection and analysis, which can be demanding and challenging in terms of both time and money (Creswell & Plano Clark, 2011; Hall, 2008). Nevertheless, it was considered useful to employ mixed methods in the current study, to identify the stronger areas of each data source, thus enhancing the rationality and dependability of the data gathered. With this approach, the researcher was able to explore further aspects and better highlight the research aims.

Creswell (2014) outlines six strategies for combining quantitative and qualitative methods, as follows:

A sequential explanatory strategy entails the gathering and analysis of quantitative data in the first stage, followed by a second stage where qualitative data are collected and analysed to strengthen and validate the findings of the quantitative phase.

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A sequential exploratory strategy includes a first stage of qualitative data collection and analysis, followed by a quantitative stage that depends on the findings of the initial stage.

A sequential transformative strategy involves a two-stage project with a

hypothetical perspective such as gender, race or social science theory covering the processes. There is a first quantitative or qualitative phase, followed by a qualitative or quantitative one relying on the initial stage.

A concurrent triangulation strategy requires the researcher to gather both

quantitative and qualitative data, noting similarities and variations, so as to benefit from the strengths and overcome the limitations of each.

A concurrent nested strategy is where the researcher brings together quantitative and qualitative data so that a wide-ranging analysis of the research question is provided.

A concurrent transformative strategy is determined by the researcher’s reference

to a particular theoretical viewpoint in addition to the simultaneous collection of both quantitative and qualitative information.

Based on this terminology, the sequential explanatory strategy was decided for the current study, on the basis of the aim and research questions. Thus, it began with the collection and analysis of quantitative data, followed by the collection and analysis of qualitative data. While the former were given priority, both methods were combined throughout the interpretation stage of the research. The researcher also took into account the advice of Creswell and Plano Clark (2011) that decisions about the descriptive design should comprise who the respondents are in the second stage and what sample sizes will be utilised for both components (section 4.10).

There are several reasons for choosing the sequential explanatory strategy. According to Creswell (2014), it is considered the most straightforward of the six main mixed-method strategies, being simple to apply because the steps fall into clear and distinct phases. He also affirms that the design aspects of this strategy make it favourable in terms of description and reporting. Besides, analysing the quantitative data and studying the initial findings can contribute to deciding which aspects to pursue qualitatively, such as by addressing quantitatively important findings or statistically significant outcomes and differentiating among demographic features (Creswell & Plano Clark, 2011; Gary, 2009).

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