The "Active Search" Hypothesis: How Search Strategies Relate to Creative Learning

While research shows that web search plays a role throughout the creative process, less is known about about how people use web search to learn and frame their thinking about an open problem. People need web search to gather information about a problem area, but this can also influence the rest of the creative process. To understand how web search affects early-stage design, we collected and analyzed search log and self-report data from 34 students in a project-based design class. Participants reported struggling with scoping broad, ill-defined information goals into queries, learning domain-specific language, and assessing the usefulness of information. Analysis found that more active and diverse search behavior (i.e. issuing more frequent and diverse queries, and opening more webpages) related to more progress in early-stage design (i.e. gathering more facts, articulating more insights, and developing better problem frames). Based on these findings, we discuss implications for designing search tools to support peoples' creative processes.

[1]  Vinod Goel,et al.  The Structure of Design Problem Spaces , 1992, Cogn. Sci..

[2]  Aniket Kittur,et al.  SearchLens: composing and capturing complex user interests for exploratory search , 2019, IUI.

[3]  R. J. Bogumil,et al.  The reflective practitioner: How professionals think in action , 1985, Proceedings of the IEEE.

[4]  Robert G. Capra,et al.  An In-situ Study of Information Needs in Design-related Creative Projects , 2020, CHIIR.

[5]  M. J. Wilkenfeld,et al.  Similarity and emergence in conceptual combination , 2001 .

[6]  Kees Dorst,et al.  The core of ‘design thinking’ and its application , 2011 .

[7]  Jon Kolko,et al.  Exposing the Magic of Design: A Practitioner's Guide to the Methods and Theory of Synthesis , 2011 .

[8]  Jon Kolko,et al.  Exposing the Magic of Design , 2010 .

[9]  Sharon L Thompson-Schill,et al.  Functional Fixedness in Creative Thinking Tasks Depends on Stimulus Modality. , 2016, Psychology of aesthetics, creativity, and the arts.

[10]  William Hemmig.  The information-seeking behavior of visual artists: a literature review , 2008, J. Documentation.

[11]  Kazjon Grace,et al.  Surprise-Triggered Reformulation of Design Goals , 2016, AAAI.

[12]  D. Campbell.  Blind variation and selective retention in creative thought as in other knowledge processes. , 1960, Psychological review.

[13]  Robert G. Capra,et al.  Understanding How People use Search to Support their Everyday Creative Tasks , 2019, CHIIR.

[14]  B. Cramond,et al.  The Creative Problem Finding Hierarchy: A Suggested Model for Understanding Problem Finding , 2018, Creativity. Theories – Research - Applications.

[15]  Aniket Kittur,et al.  Mesh: Scaffolding Comparison Tables for Online Decision Making , 2020, UIST.

[16]  Pernilla Qvarfordt,et al.  Leading people to longer queries , 2013, CHI.

[17]  D. Gentner,et al.  The analogical mind : perspectives from cognitive science , 2001 .

[18]  Jaime Arguello,et al.  Grannies, tanning beds, tattoos and NASCAR: evaluation of search tasks with varying levels of cognitive complexity , 2012, IIiX.

[19]  J. W. Getzels.  Problem Finding: a Theoretical Note , 1979, Cogn. Sci..

[20]  Kevyn Collins-Thompson,et al.  Towards searching as a learning process: A review of current perspectives and future directions , 2016, J. Inf. Sci..

[21]  Benjamin S. Bloom,et al.  A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives , 2000 .

[22]  Kees Dorst,et al.  Briefing and reframing: A situated practice , 2011 .

[23]  Chirag Shah,et al.  Searching as Learning: Exploring Search Behavior and Learning Outcomes in Learning-related Tasks , 2018, CHIIR.

[24]  Scott R. Klemmer,et al.  RePlay: Contextually Presenting Learning Videos Across Software Applications , 2019, CHI.

[25]  Ujwal Gadiraju,et al.  Understanding User Search Behavior Across Varying Cognitive Levels , 2019, HT.

[26]  Dafna Shahaf,et al.  Analogy Mining for Specific Design Needs , 2017, CHI.

[27]  Lisl Zach,et al.  When is enough enough? Modeling the information-seeking and stopping behavior of senior arts administrators , 2005, J. Assoc. Inf. Sci. Technol..

[28]  Bernard J. Jansen,et al.  Using the taxonomy of cognitive learning to model online searching , 2009, Inf. Process. Manag..

[29]  Max L. Wilson,et al.  A comparison of techniques for measuring sensemaking and learning within participant-generated summaries , 2013, J. Assoc. Inf. Sci. Technol..

[30]  Pertti Vakkari,et al.  Evaluation Methodologies in Information Retrieval (Dagstuhl Seminar 13441) , 2013, Dagstuhl Reports.

[31]  Gary Marchionini,et al.  Synthesis Lectures on Information Concepts, Retrieval, and Services , 2009 .

[32]  C. H. Dorst,et al.  Frame Innovation: Create New Thinking by Design , 2015 .

[33]  Lyn Robinson,et al.  The information-related behaviour of emerging artists and designers: Inspiration and guidance for new practitioners , 2011, J. Documentation.

[34]  A. Ortony,et al.  Similarity and Analogical Reasoning , 1991 .

[35]  M. Scheerer,et al.  Problem Solving , 1967, Nature.

[36]  Susan T. Dumais,et al.  Discovery is never by chance: designing for (un)serendipity , 2009, C&C '09.

[37]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.