2 Overview Qualitative and quantitative Simple quantitative analysis Simple qualitative analysisTools to support data analysisTheoretical frameworks: grounded theory, distributed cognition, activity theoryPresenting the findings: rigorous notations, stories, summaries
3 Quantitative and qualitative Quantitative data – expressed as numbersQualitative data – difficult to measure sensibly as numbers, e.g. count number of words to measure dissatisfactionQuantitative analysis – numerical methods to ascertain size, magnitude, amountQualitative analysis – expresses the nature of elements and is represented as themes, patterns, storiesBe careful how you manipulate data and numbers!
4 Simple quantitative analysis AveragesMean: add up values and divide by number of data pointsMedian: middle value of data when rankedMode: figure that appears most often in the dataPercentagesGraphical representations give overview of data
5 Simple qualitative analysis Unstructured - are not directed by a script. Rich but not replicable.Structured - are tightly scripted, often like a questionnaire. Replicable but may lack richness.Semi-structured - guided by a script but interesting issues can be explored in more depth. Can provide a good balance between richness and replicability.
6 Visualizing log data Interaction profiles of players in online game Log of web page activity
7 Simple qualitative analysis Recurring patterns or themesEmergent from data, dependent on observation framework if usedCategorizing dataCategorization scheme may be emergent or pre-specifiedLooking for critical incidentsHelps to focus in on key events
8 Tools to support data analysis Spreadsheet – simple to use, basic graphsStatistical packages, e.g. SPSSQualitative data analysis toolsCategorization and theme-based analysis, e.g. N6Quantitative analysis of text-based dataCAQDAS Networking Project, based at the University of Surrey (
9 Theoretical frameworks for qualitative analysis Basing data analysis around theoretical frameworks provides further insightThree such frameworks are:Grounded TheoryDistributed CognitionActivity Theory
10 Grounded Theory Aims to derive theory from systematic analysis of data Based on categorization approach (called here ‘coding’)Three levels of ‘coding’Open: identify categoriesAxial: flesh out and link to subcategoriesSelective: form theoretical schemeResearchers are encouraged to draw on own theoretical backgrounds to inform analysis
11 Distributed Cognition The people, environment & artefacts are regarded as one cognitive systemUsed for analyzing collaborative workFocuses on information propagation & transformation
12 Activity TheoryExplains human behavior in terms of our practical activity with the worldProvides a framework that focuses analysis around the concept of an ‘activity’ and helps to identify tensions between the different elements of the systemTwo key models: one outlines what constitutes an ‘activity’; one models the mediating role of artifacts
15 Presenting the findings Only make claims that your data can supportThe best way to present your findings depends on the audience, the purpose, and the data gathering and analysis undertakenGraphical representations (as discussed above) may be appropriate for presentationOther techniques are:Rigorous notations, e.g. UMLUsing stories, e.g. to create scenariosSummarizing the findings
16 SummaryThe data analysis that can be done depends on the data gathering that was doneQualitative and quantitative data may be gathered from any of the three main data gathering approachesPercentages and averages are commonly used in Interaction DesignMean, median and mode are different kinds of ‘average’ and can have very different answers for the same set of dataGrounded Theory, Distributed Cognition and Activity Theory are theoretical frameworks to support data analysisPresentation of the findings should not overstate the evidence