Coming into this project, we understand that people have different needs, and not everyone may belong to our target group. So just like a throng of people walking on the streets, how do we sieve out the users who have the need?
Fortunately for us, we have the users in mind right at the beginning of designing process, and has very earlier on know that meeting the needs of students - specifically NUS students - is what we want to do.
Personas...
We come up with personas of anti, novice and advanced users to understand them better. While we acknowledged that there are people who accept this technology fast, there are still people who will be as stubborn as mules in their adoption...
Users specifications and requirements
While some requirement of users can be obtained from the preliminary study, we want to futher narrow down the scope by conducting another survey based on the Kano Model.
We came up with an exhaustive list of items to be included in the system before posting the questions to 26 respondents.
Personally, I find this test very interesting as for every positive question posted, you have to post a counter-question in understanding how much people can live without it. Rating of the scale is also unconventional - instead of a symmetrical scale of very unsatisfied, unsatisified, neutral, satisfied and vey satisifed - the scale ranges from i like it this way, i expect it this way, i m neutral, i can tolerate it this way and i dislike it this way.
Hence, while a person can answer I like it if the system has photosharing, and states that I expect that the system usually do not have photosharing. This feature can be classified as an excitement attribute to the website.
Going along this line... we are able to obtain a lot of interesting information as to what will need to be inside the system and taking out what is not necessary.
REFLECTION
Interesting to conduct
This process proves enjoyable for the team as it seems to gear us a step closer to the design of the end product. Also, the final product becomes less abstract here with studies conducted in understanding users' specifications.
Results are subjective, but so what?
Guess the results cannot be objective in that sense that we have already generated a set of features. Also, testing on 26 respondents will not be what you call as "scientific" from a statistical sense. Still, we believe that the results are meaningful in steering us to a correct direction.
Of course, the article by Christopher Fahey helps too in addressing this issue of make-believe objectivity.
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