Hi,
I am currently writing a research protocol for my final year dissertation within which I am looking at current podiatry students and their levels of emotional intelligence and resilience as an insight into the future podiatry workforce. Also looking to see if there is any relationship between the two variables.
I am using two already existing pre-validated self-reporting questionnaires for both and will analyze them via crosstabulation. I am so confused by so many aspects of what I am doing so any help would be appreciated! Am I correct in saying that the study is quantitative, cross-sectional and observational in nature? would this then have to fall within the positivism paradigm? I have to mention which paradigm I am using but I feel it is more Constructionist but this can't be the case if I am using quantitative data?
Novice to research in 2nd year of Undergraduate degree and struggling,
Thanks, Melissa.
It sounds like you are conducting a quantitative, cross-sectional, and observational study using two pre-validated self-reporting questionnaires to assess emotional intelligence and resilience in podiatry students. Your study aims to determine if there is a relationship between these two variables, and you plan to analyze the data using crosstabulation.
In terms of the research paradigm, it is important to consider the ontological and epistemological assumptions that underlie your study. Ontology refers to the nature of reality and how it is studied, while epistemology refers to how knowledge is acquired and validated.
Based on your description, it seems that your study falls within the positivist paradigm, which assumes that there is an objective reality that can be studied using empirical methods. Positivism emphasizes the use of quantitative methods to test hypotheses and identify causal relationships between variables.
However, this does not necessarily mean that your study cannot incorporate constructionist elements. Constructionism emphasizes the subjective nature of reality and how it is constructed through social processes. In a quantitative study, you can still incorporate constructionist elements by considering the social context and meaning behind the quantitative data.
- Your study is indeed quantitative, as you will be analyzing numerical data using statistical methods. It's also cross-sectional, as you are measuring both emotional intelligence and resilience at a single point in time. Finally, it's observational in nature, as you are not manipulating any variables or conducting experiments.
- Regarding paradigms, it's not necessarily true that quantitative research must fall within the positivist paradigm. Positivism is a philosophical approach that emphasizes the use of empirical evidence to verify or falsify hypotheses, and it's often associated with quantitative research. However, there are other paradigms that can be used in quantitative research, such as post-positivism, critical realism, or pragmatism. These paradigms recognize that there are multiple ways of knowing and that scientific inquiry is influenced by social and cultural contexts. So if you feel that a constructionist paradigm is more appropriate for your study, you can certainly argue for that.
- It's important to note that the choice of paradigm should not depend solely on the type of data you collect (quantitative vs. qualitative), but rather on the research questions, theoretical framework, and epistemological assumptions of your study. You may find that some paradigms align better with certain aspects of your research than others.
- Crosstabulation is a useful method for analyzing associations between two categorical variables, such as emotional intelligence and resilience. However, you may want to consider using additional statistical tests to confirm or explore the relationships between these variables. For example, you could use correlation analysis, regression analysis, or structural equation modeling (SEM) to examine the strength and direction of the associations, control for potential confounding factors, or test mediation or moderation hypotheses.
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