CHAPTER 7 data analysis

Question 1

Wat betekend criticality in Data Analyse?

Answer 1

Op zoek naar interpretaties die zo gecompliceerd en accuraat mogelijk zijn.

Question 2

Wat is de definitie van data-analyse ?

Answer 2

= processen om hun data te begrijpen (“to make sense of”).

• in dataset analytische thema’s te identificeren (construeren) en om, uiteindelijk, deze thema’s om te zetten in resultaten die de RQ’s beantwoorden.
• het intentionele, systematische onderzoeken van data, en gebeurt voortdurend doorheen het onderzoeksproces.
• Een cruciale stap in QR: Data spreken nooit voor zichzelf.

Typisch verloop: Corpus -> Patronen -> Analytisch kader

Gestructureerd, maar ook steeds flexibel

Doel: getrouw (“fidelity”) zijn en blijven aan participanten als experten van hun eigen ervaringen

Question 3

Wanneer in in het onderzoek wordt analyse uitgevoerd?

Answer 3

Data analysis relates to all aspects of qualitative research and should not be thought of as isolated at one summative moment.

We consider this ongoing analysis part of the iterative and recursive nature of qualitative research and as a central aspect of validity.

Qualitative data analysis begins as soon as the first piece of data is collected and continues throughout the entire research process

Question 4

Hoe kan je data analyse kritisch benaderen?

Answer 4

> Erkennen dat DA iteratief, recursief & ‘ongoing’ is (en dus: formatief X summatief)

> Holistische aandacht voor taal, context(en), perspectieven

> Belang van formatieve analyse (o.m. m.b.t. DVinstrumenten en m.b.t. emergente thema’s)

> Aandacht voor relatie tussen databronnen & DVprocessen

> Trianguleren (van o.m. data en theorie)

> Op zoek naar disconfirming evidence

> Dialogic engagement

> Aandacht voor issues van interpretatieve autoriteit

Question 5

Wat is interpretive authority?

Answer 5

refers to the power of the researcher to be the interpreter and translator of people’s lived experiences and perspectives.

problematic when researchers believe that they have the “true” or “correct” version of someone’s story.

resist this: through their own
individualized reflexive engagement and through creating the conditions and processes of dialogic engagement in which assumptions, biases, and interpretations are rigorously challenged

consider how the data were collected, whose voices were left out, and the specific methods used and their relationship to the extant data.

• data are co-constructed and not simply “collected,” and therefore researchers must account for their role in
  the creation of data, including its limitations

Question 6

Wat is het verschil tussen data analyse en interpretatie?

Answer 6

INTERPRETATIE in kwalitatief onderzoek = Hoe de onderzoeker participanten en hun leven begrijpt, duiding geeft, representeert. Natuurlijk, gebeurd constant. Is breder.

ANALYSE= Specifieker, nl. het intentionele, gestructureerde en systematische proces van data interpreteren.
> vooral het intentionele maakt ruimte voor reflexie op interpretatie

het is van belang ervan bewust te zijn dat subjectiviteit in elk proces van onderzoek voorkomt - je moet hier bewust mee omgaan tijdens data analyse

Question 7

Wat zijn de stappen in het data analyse proces?

Answer 7

1. data reductie
2. reorganisatie data
3. representatie van data

Question 8

Wat is het proces van data reductie?

Answer 8

• Data reduction may involve carefully reviewing your data to determine what is of interest to your specific research questions and topic > the key phenomena you want to explore
• beginning with an open-coding process that
  narrows the data from your corpus
• specific research questions and research
  approach will influence the way researchers approach this phase

Question 9

Wat is het proces van data reorganisatie?

Answer 9

• data are grouped and categorized (or coded) according to specific features, commonalities, differences, or
  other aspects of the data.
• axial coding
• includes comparing codes and categories to determine themes and preliminary findings.
• emergent - determine emerging themes, you recheck these themes with your data and search for alternative explanations.

Question 10

Wat is het proces van representatie van data?

Answer 10

• researchers develop arguments based on the data and previous research
• represent their data in various ways: using quotes from transcripts to support themes, diagrams and other visual representations, and narratives of participants’ experiences

Question 11

what is phenomenology data analysis?

Answer 11

analysis remains as close to data as possible

Question 12

what is grounded theory data analysis?

Answer 12

• an inductive process that stays close to the data

- constant comparison method

Question 13

what is ethnography data analysis?

Answer 13

• goal is contextualized cultural meaning
• gain insider perspective of phenomenon
• inductive analysis process
• not theoretically driven

Question 14

action research data analysis is..?

Answer 14

• data analysis in real time
• engage group (the participants)in process of data analysis
• primacy on participants perspective

Question 15

narrative research DA is ?

Answer 15

focus of analysis is on content or structure of the story as narrative

Question 16

Wat is thematisch data analyse?

Answer 16

• involves noting relationships, similarities, and differences in the data.
• theme reflects important concepts in the data and is often understood as “a generalized feature of a data set”
• context and fidelity to participants are paramount in
  qualitative research > particularity of individualized experience can get lost >
• Themes do not necessarily need to reflect patterns and commonalities.
• Many factors influence what ultimately become themes,
  and central to these are your research questions

Question 17

Wat is een integratieve aanpak van data analyse?

Answer 17

an approach that iteratively integrates within and across the various stages and activities of your research project.

This requires engaging a specific kind of criticality in your approach to the entire data analysis

Question 18

Wat betekend iteratief en recursief werken in data analyse?

Answer 18

RECURSIEF: each subsequent analytic process informs and builds on the other in

your research methods— are directly related to the findings since the data constitute the material on which your findings are based.

hoe je analyse aanpakt, hangt rechtstreeks af van vorige keuzes) : The analytical approaches
you use depend on the research questions, instrument questions, and what you seek to learn with/from individuals.

ITERATIEF:
it means that you see their (of the data sources and processes ) refinement as emergent and
responsive to what you are learning in real time. It is only through ongoing data analysis that such insights and design improvements can be cultivated.

Question 19

wat is fedaliteit in data analyse - getrouw?

Answer 19

• being authentic to what study participants actually say, how they say it, and from within which contexts they share particular thoughts or experiences.
• transparent about the ways questions are worded and how the researcher and situation shapes
  responses (data).
• The fidelity must be to participants and the information
  they share;
• researchers should try to resist the urge to
  assume meaning, make inferences, or overassert what can be learned from partial engagements.

Question 20

What is summative and formatief data analyse?

Answer 20

SUMMATIEF: data analyse als een welafgelijnde en aparte stap, na het verzamelen van de data (h.8)

FORMATIEF : Verfijnen van instrumenten en (R)Qs(“reality check”) & Beginnen begrijpen van de data > doorheen gehele data analyse process!

Formative analysis (also referred to as preliminary or early analysis) begins with the refinement of your methods (and sometimes the research
questions) and continues throughout the entire research process as data are
collected.

• formative data analysis also means that you are starting to get a sense of what you are learning from the data

Question 21

What are methods for formative analysis?

Answer 21

reflexive pocesses such as writing memos
piloting
vetting

see chapter 3

Question 22

wat is analytische data triangualtie?

Answer 22

Analytische datatriangulatie: Verschillende databronnen met elkaar vergelijken voor spanningen en manieren waarop verschillende databronnen de zich ontwikkelende inzichten uitdagen en/of ondersteunen

collected at different times, places, and/or about/with different people

• data uit verschillende analytische hoeken bekijken; verschillende manieren van naar de data kijken uitproberen

Question 23

wat is analytisch - theoretische triangulatie?

Answer 23

Analytisch-theoretische triangulatie: Het gebruiken van meerdere theoretische perspectieven; meer dan 1 theorie > steeds heen en weer bewegen tussen theorie en data

Theorie kan 1/ de studie drijven/gronden, 2/ opduikende inzichten ondersteunen, 3/ je bevindingen kaderen en/of uitdagen

“Een” theorie vs. specifieke theoretische componenten

Question 24

Waarom is dialogic engagement belangrijk?

Answer 24

Binnenbrengen van bijkomende & alternatieve perspectieven > Uitdagen van eigen blik = via bijv. dialogic engagement

• Actief binnenbrengen in het DA proces
• Gesprek onder collega-studenten, met je promotor, …, experten
• Reflexiviteit & analytische skills verhogen

Binnenbrengen van bijkomende & alternatieve perspectieven

Uitdagen van eigen blik

Accountability

!! Niet uit het oog verliezen: Ethische aspecten (bijv. informed consent)