Seguimiento del Panel de Indicadores de Sostenibilidad de Arantzazu

Transferability refers to the degree to which the results of quantitative research can be generalised or transferred to other contexts or settings. According to Schwandt (2007), it deals with issues of generalisation from case to case. As noted before, the objective of this study is to determine how anxiety and lack of motivation has led to poor performances among Pre-degree students considering also the poor teaching methods, by investigating the participants in their unique contexts. The aim is not to

Traditional Criteria for Judging

Quantitative Research Alternative Criteria for Judging Qualitative Research

Reliability Reliability

Internal Validity Credibility External Validity _{Transferability}

Confirmability Objectivity

106 generalise but rather to obtain meaningful information that can have a positive effect on further research in this area of study.

The person who wishes to “transfer” the results to a different context is then responsible for making the judgment of how sensible the transfer is.

3.9.2 CREDIBILITY

The credibility criterion involves establishing that the results of the quantitative research are truthful or believable from the perspective of the participant in the research. It addresses the issue whether the reconstruction and representation of the participant’s view fits with the participant’s interpretation of his/her experiences. In other words, it could be the degree to which the interpretation of data has the same meanings for the participant and the researcher so that they both agree on the description or composition of events, especially the meanings of events (McMillan and Schumacher, 2009). Since from this perspective, the purpose of qualitative research is to describe or understand the phenomena of interest from the participant’s viewpoint (anxiety, lack of motivation and teaching strategies affecting mathematics achievement), the participants are the only ones who can legitimately judge the credibility of the results.

In this study credibility will be achieved and enhanced by making use of triangulation and crystallisation in order to verify the data.

3.9.2.1 Triangulation

Triangulation as mentioned earlier in this study is a strategy that helps enhance the validity and reliability of the research as well as to evaluate the findings of a study. It involves various methods of data collection from a variety of sources (Golafshani, 2003; Stake, 2005). A number of triangulation types exist, four were identified by Knafl and Breitmayer (1989), namely:

 Triangulation of data methods (data are collected by various means and compared.)

 Triangulation of data sources (maximises the range of data that might contribute to complete understanding of the concept.

 Theoretical Triangulation (meaning that the ideas from diverse or competing theories can be tested.)

107  Investigators’ triangulation (occurs in a study in which a research team

rather than a single researcher is used).

Other forms of triangulation methods as put forward by Cohen (2000) and his colleagues include:

 Space Triangulation (concerned with collection of data in various situations)

 Methodological triangulation (using the same method on different occasions or different methods on the same participant).

For this study, the triangulation of data methods have been adopted and used, as data are collected by various means and thereafter compared.

It is generally believed and accepted that the reliability and validity of any study would improve if the researcher uses several different types of sources that provide more insight into the same event and then cross-check the results against that of another procedure (De Vos et. al, 2005).

To this end, this proposed study will make use of methodological and investigator triangulation. The researcher will thus implement various techniques (observations, interviews, co-constructive conversations, surveys, focus groups, field notes and journals) to collect and verify the data. The researcher will engage an external coder if need be to code data collected from these sources and will discuss all the results throughout the process of data collection and analysis with his supervisor.

3.9.2.2 Crystallisation

This is the process of temporarily suspending the examining or reading of the collected data (Immersion) in order to reflect on the analysis experience and attempt to identify and articulate patterns or themes noticed during the immersion process. Sociologist Richardson (1994), and St. Pierre, (2005) broadly introduced the concept of crystallisation to qualitative methodologists in Richardson (1994) classic essay, “Writing as a Method of Inquiry.” Richardson (1994) articulated crystallisation in qualitative research as the capacity for writers/researchers to break free of traditional generic constraints. Nieuwenhuis (2007) explains that because the constructivist perspective views the world as reality that is changing and maintains that there are

108 multiple realities depending on the person interpreting it, and posits that qualitative researchers have their own interpretation of data.

This means by making use of various methods of data collection and analysis, the researcher finds emerging patterns that represents a crystallised reality and thereby adds to the quality of the study. Therefore, the proposed study will engage the triangulation and crystallisation processes in order to have a deeper understanding of the phenomenon under study in a more trustworthy and dependable manner.

3.9.3 DEPENDABILITY

The third criterion for dependability, according to the quantitative view of reliability is based on the assumption of replicability or repeatability. What this refers to is whether we would obtain the same results if we could observe the same thing twice. Although, we cannot actually measure the same thing twice, by definition if we are measuring twice, we are measuring two different things. In order to measure reliability, quantitative researchers construct various hypothetical notions (for example the True Score Theory) to get around this fact. According to Trochim (2002:1), “The true score theory is thus a simple model of how the world operates, it maintains that every measurement is an additive composite of two components: true ability or level of the respondent on that measure; and the random error involved”.

According to Schwandt (2007:11), “Dependability requires the researcher to take responsibility for ensuring that the process followed during the study is logical, traceable and documented. The idea of dependability on the other hand, emphasises that the researcher should account for the ever-changing context within which research occur. The researcher is responsible for describing the changes that occur in the setting and how these changes affected the way they approached the study”. The simple equation of: X= T + ex, where X= True score, T= True ability or level and

ex= random error. This equation also has a parallel one at the level of the variance

or variability of a measure that is across a set of scores, we assume that:

var (X) = var (T) + var (ex)

This can be interpreted in a more practical term that the variability of one’s measure is the sum of the variability due to true score and the variability due to random error.

109 It tells us that most measurements have an error component, which needs allowance to be made for.

3.9.4 CONFIRMABILITY

Confirmability refers to the degree to which the results of a research could be confirmed or corroborated by others. In other words, it means the degree to which the interpretation of data has the same meaning for the participant and the researcher so that they both agree on the description or composition of events and especially on the meanings of the events (McMillan and Schumacher, 2009).

There are a number of strategies for enhancing confirmability. The researcher can document the procedures for checking and rechecking the data throughout the study. Another researcher can play the “devil’s advocate” with respect to the results by actively searching for and describe any negative instances that contradict prior observations. After this study, one can conduct a data audit that examines the data collection, analyses procedures and make judgments about the potential for bias or distortion.

In this proposed study making use of triangulation and crystallisation in order to verify the data will enhance confirmability.