Teasing Apart with Meta Analysis

I’m presenting Teasing Apart with Meta Analysis (TAMA) at WebSci’11 today: this post is a very brief summary, plus links to further information.

In a nutshell, TAMA is a method for understanding user experiences. It grew from Teasing Apart, Piecing Together (TAPT), a method I built during my EngD. TAPT is about analysis and then redesign of experiences across contexts: for example, moving from traditional to mobile web, or from physical to digital spaces. The evidence showed that the first phase of TAPT — Teasing Apart — is a very strong way to elicit information on people’s subjective experiences, particularly emotional and social aspects. As well as yielding rich data, it also turned out to be rapid to apply.

This led to the question: can we use the Teasing Apart phase of TAPT for analysis in its own right, rather than analysis leading towards redesign?

Some meta analysis materials

Some meta analysis materials

The answer is yes. In my WebSci paper I report on the method and results of a case study conducted last year: we ran two focus groups with users of two geosocial networks (Gowalla and geocaching).

Quick summary: just as with TAPT, using Teasing Apart in TAMA yields rich and relevant data on user experiences, and is quick to apply (lending itself to repeated use — good for corroborating results). It’s a flexible tool: it has been used with focus groups, directly by researchers, and by individual anonymous participants. The meta analysis approach is likewise flexible.

Interested in reading more? Here are a few links:

This post was about the TAMA method and not the results of the case study, which examined experiences with geosocial networks. I’ll be presenting those results at this year’s MobileHCI conference, in the Please Enjoy workshop on playful interactions. I shall blog it at the time of that conference, but if you’re intrigued to know more beforehand, that paper is also online!

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One response to this post.

  1. […] Teasing Apart with Meta Analysis, an approach for understanding user experiences online, is here. This past blog post describes the gist of it, and links to the paper and slides. LikeBe the first to like this […]

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