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doi Using Social Interaction Trace Data and Context to Predict Collaboration Quality and Creative Fluency in Collaborative Design Learning Environments ↗
Lorraine KisselburghClick to read abstract
Engineering design typically occurs as a collaborative process situated in specific context such as computer-supported environments, however there is limited research examining the dynamics of design collaboration in specific contexts. In this study, drawing from situative learning theory, we developed two analytic lenses to broaden theoretical insights into collaborative design practices in computer-supported environments: (a) the role of spatial and material context, and (b) the role of social interactions. We randomly assigned participants to four conditions varying the material context (paper vs. tablet sketching tools) and spatial environment (private room vs commons area) as they worked collaboratively to generate ideas for a toy design task. We used wearable sociometric badges to automatically and unobtrusively collect social interaction data. Using partial least squares regression, we generated two predictive models for collaboration quality and creative fluency. We found that context matters materially to perceptions of collaboration, where those using collaboration-support tools perceived higher quality collaboration. But context matters spatially to creativity, and those situated in private spaces are more fluent in generating ideas than those in commons areas. We also found that interaction dynamics differ: synchronous interaction is important to quality collaboration, but reciprocal interaction is important to creative fluency. These findings provide important insights into the processual factors in collaborative design in computer-supported environments, and the predictive role of context and conversation dynamics. We discuss the theoretical contributions to computer-supported collaborative design, the methodological contributions of wearable sensor tools, and the practical contributions to structuring computer-supported environments for engineering design practice.
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pdf Merging Sketches for Creative Design Exploration: An Evaluation of Physical and Cognitive Operations ↗
Lorraine KisselburghClick to read abstract
Despite its grounding in creativity techniques, merging multiple source sketches to create new ideas has received scant attention in design literature. In this paper, we identify the physical operations that in merging sketch components. We also introduce cognitive operations of reuse, repurpose, refactor, and reinterpret, and explore their relevance to creative design. To examine the relationship of cognitive operations, physical techniques, and creative sketch outcomes, we conducted a qualitative user study where student designers merged existing sketches to generate either an alternative design, or an unrelated new design. We compared two digital selection techniques: freeform selection, and a stroke-cluster-based "object select" technique. The resulting merge sketches were subjected to crowdsourced evaluation of these sketches, and manual coding for the use of cognitive operations. Our findings establish a firm connection between the proposed cognitive operations and the context and outcome of creative tasks. Key findings indicate that reinterpret cognitive operations correlate strongly with creativity in merged sketches, while reuse operations correlate negatively with creativity. Furthermore, freeform selection techniques are preferred significantly by designers. We discuss the empirical contributions of understanding the use of cognitive operations during design exploration, and the practical implications for designing interfaces in digital tools that facilitate creativity in merging sketches.
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pdf Integrating Visual Analytics Support for Grounded Theory Practice in Qualitative Text Analysis ↗
Click to read abstract
We present an argument for using visual analytics to aid Grounded Theory methodologies in qualitative data analysis. Grounded theory methods involve the inductive analysis of data to generate novel insights and theoretical constructs. Making sense of unstructured text data is uniquely suited for visual analytics. Using natural language processing techniques such as parts-of-speech tagging, retrieving information content, and topic modeling, different parts of the data can be structured and semantically associated, and interactively explored, thereby providing conceptual depth to the guided discovery process. We review grounded theory methods and identify processes that can be enhanced through visual analytic techniques. Next, we develop an interface for qualitative text analysis, and evaluate our design with qualitative research practitioners who analyze texts with and without visual analytics support. The results of our study suggest how visual analytics can be incorporated into qualitative data analysis tools, and the analytic and interpretive benefits that can result.
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pdf VizScribe: A Visual Analytics Approach to Understand Designer Behavior ↗
Lorraine KisselburghClick to read abstract
Design protocol analysis is a technique to understand designers’ cognitive processes by analyzing sequences of observations on their behavior. These observations typically use audio, video, and transcript data in order to gain insights into the designer's behavior and the design process. The recent availability of sophisticated sensing technology has made such data highly multimodal, requiring more flexible protocol analysis tools. To address this need, we present VizScribe, a visual analytics framework that employs multiple coordinated multiple views that enable the viewing of such data from different perspectives. VizScribe allows designers to create, customize, and extend interactive visualizations for design protocol data such as video, transcripts, sketches, sensor data, and user logs. User studies where design researchers used VizScribe for protocol analysis indicated that the linked views and interactive navigation offered by VizScribe afforded the researchers multiple, useful ways to approach and interpret such multimodal data.
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pdf skWiki: A Multimedia Sketching System for Collaborative Creativity ↗
Lorraine KisselburghClick to read abstract
We present skWiki, a web application framework for collaborative creativity in digital multimedia projects, including text, hand-drawn sketches, and photographs. skWiki overcomes common drawbacks of existing wiki software by providing a rich viewer/editor architecture for all media types that is integrated into the web browser itself, thus avoiding dependence on client-side editors. Instead of files, skWiki uses the concept of paths as trajectories of persistent state over time. This model has intrinsic support for collaborative editing, including cloning, branching, and merging paths edited by multiple contributors. We demonstrate skWiki's utility using a qualitative, sketching-based user study.