Evaluating creativity support environments is challenging. Some approaches address people's experiences of creativity. The present method measures creativity, across conditions, in the products that people make.This research introduces information-based ideation (IBI), a paradigm for investigating open-ended tasks and activities in which users develop new ideas. IBI tasks span imagining, planning, and reflecting on a weekend, vacation, outfit, makeover, paper, internship, thesis, design, campaign, crisis response, career, or invention. What products do people create through engagement in IBI? Curation of digital media incorporates conceptualization, finding and choosing information objects, annotation, and synthesis. Through engagement in IBI tasks, people create curation products. This article formulates a quantitative methodology for evaluating IBI support tools, building on prior creative cognition research in engineering design to derive a battery of ideation metrics of curation. Elemental ideation metrics evaluate creativity within curated found objects. Holistic ideation metrics evaluate how a curation puts elements together.IBI support environments are characterized by their underlying medium of curation. Curation media include lists, such as listicles, and grids, such as the boards of Pinterest.An in-depth case study investigates information composition, an art-based medium representing a curation as a freeform visual semantic connected whole. We raise two creative cognition challenges for IBI. One challenge is overcoming fixation-for instance, when a person gets stuck in a counterproductive mental set. The other challenge is to bridge information visualization's synthesis gap, by providing support for connecting findings. To address the challenges, we develop mixed-initiative information composition (MI 2 C), integrating human curation of information composition with automated agents of information retrieval and visualization.We hypothesize that MI 2 C generates provocative stimuli that help users overcome fixation to become more creative on IBI tasks. We hypothesize that MI 2 C's integration of curation and visualization bridges the synthesis gap to help users become more creative. To investigate these hypotheses, we apply ideation metrics of curation to interpret results from experiments with 44 and 49 participants.

We extend the Twitter interface to stimulate exploratory browsing of social media and develop a creative cognition method to establish its efficacy. Exploratory browsing is a creative process in which users seek and traverse diverse and novel information as they investigate a conceptual space. The TweetBubble browser extension extends Twitter to enable expansion of social media associations-@usernames and #hashtags-in-context, without overwriting initial content. We build on a prior metadata type system, developing new presentation semantics, which enable an integrated look and feel consistent with Twitter.We show how exploratory browsing constitutes a mini-c creative process. We use prior ideation metrics as a basis for new ideation metrics of exploratory browsing. We conducted a mixed methods crowdsourced study, with data from 54 participants, amidst the 2014 Academy Awards. Quantitative and qualitative findings validate the technique of in-context exploratory browsing interfaces for social media. Their consistency supports the validity of ideation metrics of exploratory browsing as an evaluation methodology for interactive systems designed to promote creative engagement.

Combating fake news and misinformation propagation is a challenging task in the post-truth era. News feed and search algorithms could potentially lead to unintentional large-scale propagation of false and fabricated information with users being exposed to algorithmically selected false content. Our research investigates the effects of an Explainable AI assistant embedded in news review platforms for combating the propagation of fake news. We design a news reviewing and sharing interface, create a dataset of news stories, and train four interpretable fake news detection algorithms to study the effects of algorithmic transparency on end-users. We present evaluation results and analysis from multiple controlled crowdsourced studies. For a deeper understanding of Explainable AI systems, we discuss interactions between user engagement, mental model, trust, and performance measures in the process of explaining. The study results indicate that explanations helped participants to build appropriate mental models of the intelligent assistants in different conditions and adjust their trust according to their perceptions of model limitations.

Reflection, interpretation, and curation play key roles in learning, creativity, and problem solving. Reflection means looking back and forward among building blocks constituting a space of ideas, contextualizing with processes including tasks, activities, and one's internal thinking and meditating, and deriving new understandings, known as interpretations. Curation, in the digital age, means searching, gathering, collecting, organizing, designing, reflecting on, and interpreting information.We introduce rich bookmarks, representations of key ideas from documents as navigable links that integrate visual clippings and rich semantic metadata. We support curating rich bookmarks as information composition. In this holistic visual form, curators express relationships among curated elements through implicit visual features, such as spatial position, color, and translucence.We investigated the situated context of a university course, engaging educators in iterative co-design. Rich bookmarks emerged in the process, motivating changes in pedagogy and software. Changes provoked students to collect more novel and varied ideas. They reported that curating rich bookmarks as information composition helped them reflect, transforming prior ideas into new ones. The visual component of rich bookmarks was found to support multiple interpretations; the semantic to support associational exploration of related ideas.