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CHI 2009 Workshop: Best Practices in Longitudinal Research. Jhilmil Jain Hewlett-Packards Labs, Palo Alto CA jhilmil.jain@hp.com. Who are you?. Role: User Experience Research Lead (IIML lab @ HP Labs) PhD in HCI Leading
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CHI 2009 Workshop: Best Practices in Longitudinal Research Jhilmil Jain Hewlett-Packards Labs, Palo Alto CA jhilmil.jain@hp.com
Who are you? • Role: User Experience Research Lead (IIML lab @ HP Labs) • PhD in HCI • Leading • 7 person s/w dev, UI designer, Visual designers team in Brazil and Palo Alto • Research interests • information visualization; multimodal interaction models; PIM; user research and experimental evaluation • Several patents and publications in the above areas • Very active in academic community: • Program committee: CHIMIT, HCII, UPA, CISIS, ACMSE, GHC, MobileHCI • Program Chair: CHIMIT 2009
What is longitudinal research? • Advantages: • helps to prove the feasibility of novel approaches • invaluable in determining probable adoption rates • aids in studying behavior over time • aids in studying the contextual use of the system • avoids oversimplification of “measured” tasks • Combination of active (diary studies, observational) and passive (post interviews and surveys) • Multimodal diary approach caused an increase in captured feedback, thus resulted in richer retrospective interviews
Your experience with longitudinal research (1/2) • How many studies • About 5 • Types of studies • combination of qualitative and quantitative • mostly on innovative interaction modes, disruptive technologies • Successes • able to identify parameters that affect adoption of technology • Challenges • Compare qualitative data over time? • Lack of personnel and tools to analyze qualitative data • Recruited stakeholders: affinity diagrams
Your experience with longitudinal research (2/2) Usability evaluation vs. longitudinal research Scenario 1 Usability evaluation – system is usable but not useful Longitudinal finding – “adoption gap”, “personal eureka moments” Scenario 2 Usability evaluation - system is usable and useful Longitudinal finding – usage declines as “novelty” wears off Opportunity to discover the reasons - how can the system be better designed/integrated?
What questions do you want answered in this workshop? • How to systematically compare qualitative data over time? • How to compare data when the UI evolves over time or changes significantly? • How to adjust for participant variation/drop offs?