This is the first part of my fourth lecture at the HITLab, Canterbury University in New Zealand. As a design practitioner I am frequently getting a question from other practitioners, why would they do user research in the first place. Once I manage to convince them why it makes sense, the follow up question typically regards the issue of choosing the right people for that research. In this presentation I am trying to highlight two different approaches to user research, which I will describe in more detail in the next presentation.
<ul><li> user research: trying to answer the why and how questions aga szstek(at)gmail.com </li> <li> why doing user research in the rst place? </li> <li> -users have dierent goals than designers -users do not care for design success -there is more than one user per solution -there is more than one solution per problem </li> <li> traditional user research - formal - informative - answers - precision - understanding - raw data generative methods - informal - inspirational - questions - ambiguity - empathy - interpretation </li> <li> user research: an example PhD project: Sebas1an Denef Promoters: David V. Keyson i Reinhard Oppermann </li> <li> How do remen deal with dangerous situations in the midst of the action? How could their actions be supported through interactive technologies? </li> <li> OBSERVATIONS </li> <li> TOOL ANALYSIS </li> <li> ROLE PLAYING </li> <li> BUILDING EMPATHY </li> <li> using generative methods: an example Welcome Experience at a telecom provider Aga Szstek, Marcin Piotrowski, Joanna Kwiatkowska </li> <li> rst month with a telecom provider provider rst impressions user trial period uncertainty building relationship gaining trust adjusting oer explaining payment upselling </li> <li> partcipants - 20 persons (50% M, 50% F) - recruited at the door of the providers shop - committed to buy a postpaid plan - signing an agreement to participate </li> <li> diary / blog study </li> <li> love / hate letters </li> <li> creative workshop </li> <li> why and when traditional user research? </li> <li> - works great for the dened design space - helps to objectify discovered phenomena - supports task oriented design - resolves interaction problems - focuses in iterative measurement of progress - enables comparison </li> <li> why and when generative methods? </li> <li> - high complexity of the design issues (so called: wicked problems) - uncertainty what truly is the design challenge - need for exibility to approach the solution - building empathy </li> <li> who should participate? </li> <li> snowball sampling: when you want to nd users who have similar interests, jobs or lifestyle </li> <li> extreme case sampling: when you want to nd users who are extreme representatives of certain behaviours (e.g. remen for a decision-taking study </li> <li> homogenous sampling: when you want to nd users who are very much alike in a certain aspect </li> <li> maximum variation sampling: when you want to nd users who are very dierent with respect to a certain aspect </li> <li> convenience sampling: when you just want to nd users who are together for some reason (eg. a workshop) and agree to participate in the study </li> <li> opportunistic sampling: when you just want to nd truly random users </li> <li> references Denef, S.; Keyson, D.; Oppermann, R. Rigid Structures, Independent Units, Monitoring: Organizing Patterns in Frontline Fireghting. In Proceedings of the 2011 SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, USA, 510 May 2011; pp. 1949 1958. Pallot, Marc, et al. "Living lab research landscape: From user centred design and user experience towards user cocreation." First European Summer School'Living Labs'. 2010. </li> </ul>