Thanks for explaining your plan for the data analysis. You characterise later differences between initial conceptions of data analysis and later ones as “go[ing] wrong” (Aman, 2016), and this may be indicative of your analytical technique. When I asked my question originally, I had in mind a number of techniques, and the methodology I expect to be using is grounded theory. This is an iterative system whereby the original data is revisited many times and where the original respondents may be re-contacted (Charmaz, 2006; Hadley, 2015). Grounded theory does not try to predict beforehand how the data will be used, and the iterative process includes many possible reinterpretations. But this is only one method. Postmodernism attempts to understand how a single data item can have multiple truths depending on the person viewing the item, on the situation of how the item is used and on the nature of truth held by the person, among others (Delanty, 2001). Have you settled on your data analysis method? If so, what is it?
By the way, I would challenge Bosmeny’s (2014) claim that “data isn’t inherently scary” and the implication that proper security is all that is needed to allay fears regarding data protection. Bosmeny’s context is that of using app-generated data about children’s responses to mathematics in primary and secondary educational settings. In this limited context, perhaps Bosmeny is making a fair point, but it would be improprietous to generalise this to make claims about data and security in other types of data collection. For example, it may very well be frightening for some participants in an interview to discuss their education histories. For individuals who have had traumatic experiences in education, the action of making this experience into a data point can be “inherently scary”. But that isn’t my biggest worry.
Williams (2009) discusses the ethical nature of respondent data and develops a typology of five aphoria, or “lack[s] of resource… a specific kind of lack or want, a perplexity achieved by an encounter with the previously unthought, an uncertainty about where to go next driven by a desire to progress” (Heidegger 1945/2000, cited in Williams, 2009, p. 214). Textual analysis can lead to the discovery of internal contradictions, which may include potential “inherently scary” (Bosmeny, 2014) items of data; for example, when a participant reveals that a teacher had (racially, sexually, academically) abused them and that that teacher happened to be a member of the same institute as the interviewer (Laureate, 2012).
Aman, J. (2016, October 22). RE: Week 3 – Choosing data collection methods. Message posted to https://elearning.uol.ohecampus.com/webapps/discussionboard/do/message?action=list_messages&forum_id=_1160653_1&group_id=_442972_1&nav=group_forum&conf_id=_539530_1&course_id=_1607246_1&message_id=_19913623_1#msg__19913623_1Id Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. London: Sage.
Bosmeny, T. (2014) Data Can Be Used and Secured. New York Times. Retrieved 24 October 2016 from http://www.nytimes.com/roomfordebate/2014/09/24/protecting-student-privacy-in-online-learning/data-can-be-used-and-secured
Delanty, G. (2001). Challenging knowledge: the university in the knowledge society. Challenging knowledge: the university in the knowledge society. Buckingham: The Society for Research into Higher Education and the Open University Press. http://doi.org/10.1080/1356251022012428
Hadley, G. (2015). English for academic purposes in neoliberal universities: A critical grounded theory. System (Vol. 51). Cham: Springer. http://doi.org/10.1016/j.system.2015.04.010
Laureate Education, Inc. (2012). Ethical Challenges for the Practitioner-Researcher. Baltimore, MD: Laureate.
Williams, K. F. (2009). “Guilty knowledge”: ethical aporia emergent in the research practice of educational development practitioners. London Review of Education, 7(3), 211–221. http://doi.org/10.1080/14748460903290074