Qualitative research methods

Qualitative Research Methods

Tijmen van Gurp Ard Jacobs

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Introduction In the module Qualitative Research Methods for Interaction Design, we’ve explored methods for analysing, interpreting and acquiring qualitative data, which may strategically serve as input for the design of innovative products, services and systems. The module has mainly focussed on the process of investigating new perspectives to a given design domain, but has also delivered insights in how to identify design opportunities upon these insights.

It’s the unusual perspective that may lead to radical innovation.

Jacobs G. J., s050518, g.j.jacobs@student.tue.nl

Gurp, T. M., van, s081936 t.m.v.gurp@student.tue.nl

Table of Contents INTRODUCTION 4

Domain ITERATION #1 Highlights, Affinity Diagram, Chunks Categories Closed coding Conclusion & Discussion ITERATION #2 Annotations, Affinity Diagram, Chunks Interpretation Hypothesis Categories Closed Coding Interview Interview Guide Interviewees nnotations Opportunities for Design Conclusion Discussion

Domain Sleep. Sleep is considered a necessity for both body and brain. It is crucial that we rest in order to recharge for our daily activities. However, sleep is experienced quite differently among different people. And the causes for this are surely divers.

In this report, we present our research process and our findings on the investigation of cause and effect of the sleep experience. We followed closely the methods provided by the lecturer, that delivered insights in the domain.

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ITERATION #1 6

Highlights, Affinity Diagram, Chunks After we’ve been provided with the results of a questionnaire (mostly sentence-completion method) on the quality of sleep, we started with highlighting the important comments and remarks. Upon that, we collected the highlights in an affinity diagram.

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Highlights, Affinity Diagram, Chunks After identifying one of the chunks (“stress�) as the biggest and most interesting, we continued with creating a short but vivid description (memos) of the two categories we defined:

OTHER STRESS:

fears, lack of love, physical discomforts, energy fluctuations

JOB/STUDY RELATED STRESS: workload, tasks, activities, responsibilities

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Job/study related stress: workload, tasks, activities, responsibilities • I love it when my sleep comes quickly.

• I have trouble sleeping-in.

• I have a busy work schedule.

• Sleeping could empty my mind.

• Before I sleep, I worry about all the things I still need to do.

• I tend to wake up at night because of noises/sounds from inside or outside the house.

• I wish for my family to be happy.

• Sometimes I feel lonely.

Other stress: fears, lack of love, physical discomforts, energy fluctuations • Temperature is important to the quality of my sleep.

• I wake up a few times every night for a visit to the bathroom or because of pain/discomfort • I am depressed.

• I worry about myself and others.

• I’d love to have a good night sleep and feel fit the next day.

Closed coding 10

Conclusion & Discussion From the closed coding, we figured that the category descriptions were not yet reliable enough, and should therefore be refined. Particular causes for this were that some of the participants fitted both categories equally, and were therefore subject to the coder’s judgement. Also, it was sometimes difficult to identify cause and effect within the answers of a sin-

gle participant. For example, one of the participants stated that she worried about her family situation, but she also said she experienced stress at work; leaving no reference to what inclined the other. Therefore, we decided to review our data up to this point, in order to concretize and make more specific the two categories.

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CLOSED CODING #1 Cat 1 Cat 1 Cat 2 Total Agreements Exp. Agreements K Intercoder Reliability

3 2 5

Cat 2 1 7 8

Total 4 9 13

10 7,08 0,49 77%

Sometimes a participant fitted both categories.

Differences between categories seemed too small.

Described symptoms affect each other, therefore difficult to define origin.

ITERATION #2 12

Annotations, Affinity Diagram, Chunks

Since the chosen categories were both descriptively including, we figured that the distinctness of each of the categories would increase by defining one category (instead of two-) with including as well as excluding criteria.

In order to achieve this, we reviewed the data and recreated the affinity diagram out of post-its. This method resulted in a richer image of the domain and an increased understanding of the weight of the different topics discussed around quality of sleep, due to e.g. commonality of particular annotations.

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Interpretation By redoing the affinity diagram, we found that many of the annotations gave superficial insight in the actual causes for decreased quality of sleep.

Implying that additional qualitative data should be gathered on specific chunks to generate more vivid descriptions.

As the scope of this module covers only a week, we found ourselves compelled to choosing one of the chunks to do further investigation on.

We chose temperature. Temperature appeared to be commonly discussed with regard to quality of sleep, however little qualitative data on temperature (mostly subjective data like “not too hot, not too cold�) emerged from the questionnaire.

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Hypothesis By elaborating on the annotations relating to temperature and quality of sleep, we defined an early hypothesis regarding temperature related conditions for increased quality of sleep. “A warm bed and a cold(er), well ventilated room will allow the body to relieve its heat through the head (which is supposed to be uncovered, while the rest of the body is covered), amplifying the experience of emptying the mind and processing the events of the day, allowing the body to move into a state of rest.�

Categories Based on the annotations and early hypothesis, we divided one chunk into two categories; 1) people how appear to be saying that the criteria said forth below positively influence the quality of their sleep, and 2)

Temperature conditions: A • warm-up body before sleep (shower, heating, etc.)

• bed should feel warm • wrap with blanket while in bed • window open • heating turned low/off

those who’ve put forth contrasting criteria, and 3) those who don’t mention the influence of temperature to be relevant to the quality of their sleep.

Temperature conditions: Temperature condiB tions: N • window closed/none • heating high / warm room • using socks / gloves

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Closed Coding 20

The returned numbers show a significant increase in reliability over the formerly chosen categories, implying clear descriptions of criteria. The categories at this point form a reliable basis for further qualitative research on temperature with respect to quality of sleep. So far, design opportunities have not yet emerged. Richer

data should be gathered to uncover nuances within the defined categories, which could lead to opportunities for design. So far, the opportunities found relate to the design of a ‘responsive environment’, but we believe a more subtle approach can potentially be taken.

CLOSED CODING #2 Cat 1 Cat 1 Cat 2 Total Agreements Exp. Agreements K Intercoder Reliability

11 1 12 15 9,5 0,85 94%

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Cat 2 1 4 4

Total 11 5 16

Interview 22

Interviewees

6 x mind-map: Jochem 6 people, both men and Joost women, generally good sleep- Marwien ers Marie Jose Laurie Brigitta

Interview Guide The interview guide is phrased around the topic of temperature in relation to quality of sleep. It is loosely structured according to the provided framework. The adjective “loosely” describes the level of anticipated divergence throughout the interview, allowing the interviewee to explain further his/her response. The interview guide includes introductory and general questions to ease-in the subject, questions aiming at enriching and concretizing the already found criteria, and questions elaborating on particular contexts in which temperature and sleep are more heavily connected (such as ‘camping outdoors’).

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Annotations 24

With the data collected from the interviews we did another iteration of annotating to see if there were commonalities within the data. As it was not that much data this analysis was done by printing out all the data and laying it out on the table. While discussing our findings we highlighted the most important data on our insights.

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Although the research process was short, we already saw some design opportunities for in the sleeping environment. We can think of a situation whereby the skin temperature is measured to adapt the room temperature towards the perfect temperature. Regulating the temperature by central heating or classic air-conditioning was not preferred by our interviewees. Therefore we think there

is an opportunity to look for different ways of regulating the environmental temperatures. As it is known that the body temperature has its own cycles in sleeping, and it effects the sleep we see an opportunity in measuring this cycles and adapting the environment to support the cycles also in the faces before sleeping and while waking up.

Opportunities for Design

?

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