Processes of assigning qualitative or quantitative values to chunks of data or categorizing data into groups based on commonality or along thematic lines for the purposes of describing, analyzing, and organizing data. A simple version typically involves marking the transcript margin with a color, number, letter, description, or symbol code to represent key themes or categories 

 
Other notes: Coding is about data reduction. It is a multiple stage process that allows the researcher to understand, organize, and extract themes or trends from their data sets. Review the lecture slides and recorded lecture from week 9 for more information on coding.   

A person’s social, locational, and ideological placement relative to the research project or to other participants in it. May be influenced by biological characteristics such as class, race, gender, as well as various formative experiences   

Positionality statement (definition from Hay & Cope, 2021 p. 430): 

Record of how a researcher is situated in the production of knowledge over time. This requires careful reflection on the researcher’s points of connection and disconnection with a project. Positionality statements are not stand-alone testimonials. Instead, they document the co-constitution of researcher and project 

Other notes: It is important for researchers to be aware of their positionalities as they could potentially influence how the researcher understands and analyzes the data they collect. Reflecting upon your positionalities as a researcher allows one to identify if biases exist within their thinking towards their research project. Review pages 27 and 49 in Hay & Cope for more details regarding positionality and why it is important.  

Your purpose statement should be formatted in full sentences, facts from the literature etc. It should describe the purpose of your research (I.e. what will your research do or produce? What is the purpose of this study? Why do you want to do it? What do you hope to accomplish?).  Review Cresswell chapter 5 and the lecture slides from week 2 for more information about writing purpose statements. 

The purpose is the intent, the problem is the need or issue, the research question is about the data collection to address the need in a way consistent with the intent. 

Ontology: beliefs about the world. Understanding about the kinds of things that exist in the universe and the relations between them. Multiples ontologies: the appreciation that different societies (or groups and individuals in society) might have different views of the world, or have diverse ways of being in the world 

Epistemology: ways of knowing the world and justifying belief. A critical assessment of how knowledge is produced, by whom, and for what purposes. Summed up by the question: how do we know what we know?  Many of the “isms” (constructivism, positivism, post-structuralism etc.) that were discussed in week 8 are epistemologies. 

Methodology: philosophical and theoretical basis for conducting research that is much broader and sometimes more politically charged than method alone (e.g., feminist methodology). Broadly, there are three categories of methodology; quantitative, qualitative, and mixed. However, many types/categories of methodologies can exist under the larger umbrellas of qualitative or quantitative methodology. 

Methods: Means by which data are collected and analyzed. These are your tools for data collection; think about all of the methods we have discussed this semester and their advantages and disadvantages. 

Foucauldian discourse analysis seeks to uncover the social and cultural mechanisms that maintain or rupture the structures and rules of validity embedded in statements about the world,” (Hay & Cope p. 334). It is fundamentally social constructionist (J&P: the whole package from philosphical premise to methodology to techniques for data collection and analysis) 

Document analysis: A general, qualitative method to systematically analyse documents to answer your research questions. Can be stand-alone, but more often in conjunction with other data sources (interviews, PO etc.) to triangulate findings. In this sense it is useful to refute, elucidate or expand on your other material, to minimize bias.