project[3]

lim jia sheng,
0344034.

BDCM
.Design Research & Methodology
::project[3]

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project[3]: Primary Data

todo:

• Select & justify the use of either qualitative, quantitative, or mixed method for data collection.
• Collect the data.
• Analyse the data.

process:

I started out figuring out what research methods I wanted to use. These three were my main contenders:

1. Questionnaire (duh)
2. Focus group
3. Interview

I felt like they were all going to give different enough results so I could do them parallelly. However, understandably that was not really a choice given the timeline. Thus, I chose the first two.

The reason I got rid of "interview" as an option is because I would probably not get as valuable or as objective of a test set if I went with it. "Dark patterns" itself already sounds intimidating & bad, thus there will be some inherent taboo surrounding it. The ones who may be willing to talk about it, should more often than not, be against it, whilst the ones not may be the ones implementing it. Plus, I didn't have large enough of a network to be able to screen the possible people I would contact.

For the rest two however, it was fair game.

I then came up with the questions & explanations for each question. However, to avoid large walls of duplicated text, I won't be including them here, as the differences between them draft & them in production are minute.

Distributing it was another game of pain, as just finding 80 people to talk to in the wild is hard, finding 80 people willing to do surveys, to do your survey, is even harder. I eventually hit the goal just barely by pushing it a lot & doing exchanges with people.

It was around this time I executed the focus group with 5 participants as well.

After all that, I distilled every finding down into a digestible deck & corresponding document, which you may find down there.

feedback:

• 28/10/2021
  • My questions were generally unbiased other than one (the one asking for the user’s action/inaction regarding dark patterns)
• 11/11/2021
  • Definitely not enough respondents
  • I should come up with a strategy to target groups of people more well versed in the topic
  • I should personalize a little more the survey header & title

final:

reflection:

This was an interesting ride. The main thing that still stands out to me is that getting respondents is hard; it's understandable why there are whole industries & careers built from that. Data in general, when having to do with humans, is challenging to get for free, at least that was in my experience. That said, besides that aspect, it was surprisingly fun crafting what was to be asked & actually seeing results from it. The cherry on top was whatever results I got, got to be productive in completing this task.

Which brings me to what I learnt from this project. I found that question asking is definitely a skill & questions can be biased even if on the surface they don't seem obviously so. Honestly I'm surprised I myself never put the two & two together with questions & nudging, especially since I was literally doing research on nudging in used, but hey better late than never. Another hard skill I picked up was definitely data processing & mapping. What I mean by that is merging duplicate entries, resolving vague answers, & even scripting over them to conform them to formats more suitable for visualization/understanding. If all that doesn't say "hardcore researcher" I don't know what does xd.

All in all, this was a great experience. I would've never had the chance to execute something like this. Bearing the badge of the school in the research definitely has made it somewhat easier too. I know I'll be able to use all the random tidbits of skills & data to improve my future execution of research.