Notes for seminar 1

The content revolves around data gathering, data analysis and establishing requirements. This is  a process where establishing clear and concise requirements of a potential product design is the goal. The three different data gathering techniques presented were interviews, questionnaires and observation. Each being ideal under different circumstances. The idea of triangulation, collecting and comparing data by changing variables such as data collector, date, data provider, data gathering technique etc., was encouraged to avoid any inherent bias of the variables. The data gathering population, a predefined template representing a relevant group of people, was to be directly derived from the goal of the data gathering. Different goals equals different populations. Clarity and simplicity in communication with the participants is important when doing any type of data gathering. The ideal type of data recording depends on the situation. Generally though, it is important to be well prepared before performing a data gathering. This could be achieved by doing a pilot study beforehand.

Data analysis is the idea of identifying patterns in the collected data. It is initially done by separating quantitive and qualitiative data. The first being representable by numbers and the second by descriptions, pictures or parts of interviews. Already existing theories or a grounded theory, derived from patters and obvious correlations in the data, can be used to explain certain occurences in the data. A grounded theory can be particularly useful when encountering patterns which are not covered by any preexisting theories. However, it often requires an added amount of data gathering for confirmation purposes. One extremely important factor in data analyzing lies with the interpreter of the data. S/He should try to maintain an impartial mindset in which conclusions are drawn strictly from the data.
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Data gathering and analysis should provide a good foundation in designing a product. When these two parts are completed, one should be able to create a set of clear and concise requirements which pin down what the users need. Such requirements can be purely functional, what the product should be able to do, or non-functional, how the product should perform. If it is seemingly impossible to create straight forward formulations of requirements, more data gathering and analysis is surely required. My question for discussion is, how can we make use of a pilot study to ensure that our methods of data gathering are ideal?