Analysis Of Tool Use Research Articles

Interaction Aesthetics In and Beyond the Flow

Although almost two decades have passed since the term aesthetics of interaction made its appearance in design-oriented Human-Computer Interaction (HCI), the actual understanding of the concept remains fuzzy and focused on the description of qualities of what constitutes an aesthetic experience. However, by trying to describe specific aesthetic qualities emerging from technology encounters, we risk offering endless definitions of potential aesthetic traits, mostly fixated on pleasurable interactions. This approach may discard other interactive expressions that could potentially lead us to meaningful insights. Drawing on the similarities between John Dewey's aesthetic experiences, Eugene Gendlin's process model, and Martin Heidegger’s analysis of tool use, this article offers a theoretical framework towards a broader, systematized view of aesthetics of interaction. To do so, the discussion exemplifies a series of phenomenological experiences ranging from transparency to breakdown: two opposites in the understanding of how technologies reveal themselves.

The search for the ejecting chair: a mixed-methods analysis of tool use in a sedentary behavior intervention.

Research is needed on interventions targeting sedentary behavior with appropriate behavior-change tools. The current study used convergent sequential mixed methods (QUAN + qual) to explore tool use during a edentary behavior intervention. Data came from a two-arm randomized sedentary behavior pilot intervention. Participants used a number of intervention tools (e.g., prompts and standing desks). Separate mixed-effects regression models explored associations between change in number of tools and frequency of tool use with two intervention targets: change in sitting time and number of sit-to-stand transitions overtime. Qualitative data explored participants' attitudes towards intervention tools. There was a significant relationship between change in total tool use and sitting time after adjusting for number of tools (β = -12.86, p = .02), demonstrating that a one-unit increase in tool use was associated with an almost 13 min reduction in sitting time. In contrast, there was a significant positive association between change in number of tools and sitting time after adjusting for frequency of tool use (β = 63.70, p = .001), indicating that increasing the number of tools without increasing frequency of tool use was associated with more sitting time. Twenty-four semistructured interviews were coded and a thematic analysis revealed four themes related to tool use: (a) prompts to disrupt behavior; (b) tools matching the goal; (c) tools for sit-to-stand were ineffective; and (d) tool use evolved over time. Participants who honed in on effective tools were more successful in reducing sitting time. Tools for participants to increase sit-to-stand transitions were largely ineffective. This study is registered at clincialtrials.gov. Identifier: NCT02544867.