TweetBubble: A Twitter Extension Stimulates Exploratory Browsing

We extend the Twitter interface to stimulate exploratory browsing of social media and develop a method to establish its efficacy. In exploratory browsing, users seek and traverse diverse and novel information as they investigate a conceptual space. Social media has become a predominant source of information. Social media is characterized by rapidly evolving content and relationships. We need interface mechanisms to effectively and iteratively browse, search, and filter, i.e., explore vast social media networks. We develop the TweetBubble browser extension, extending Twitter to enable expansion of social media associations @usernames and #hashtags in-context, with-out overwriting initial content. We build on a prior metadata type system, developing new presentation semantics, which enable a look and feel consistent with Twitter. We identify exploratory browsing as a creative ideation process. We use prior ideation metrics as a basis for new ideation metrics of exploratory browsing. We conducted a 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. This research impacts the design and evaluation of interfaces that stimulate intrapersonal creativity, and thereby mutual understanding, by supporting exploratory browsing of connected perspectives in a shared, structured, conceptual space

SPORT SPARKS: Supporting Creative Thinking by Professional Coaches

This short paper reports a new digital tool that supports creative idea generation about possible solutions to these challenges. Exploratory design research resulted in a new digital tool that was designed for use by the coaches of elite athletes, to discover creative ideas with which to remove, overcome and mitigate the effects of concrete athlete under-performance. Furthermore, initial feedback from 22 professional sports practitioners revealed that use of the tool led to most of them understanding the challenge from new perspectives, exploring alternative options to solve the challenge, and influenced their decision-making about the challenge

Grounded Visual Analytics: A New Approach to Discovering Phenomena in Data at Scale

We introduce Grounded Visual Analytics, a new method that integrates qualitative and quantitative approaches in order to help investigators discover patterns about human activity. Investigators who develop or study systems often use log data, which keeps track of interactions their participants perform. Discovering and characterizing patterns in this data is important because it can help guide interactive computing system design. This new approach integrates Visual Analytics, a field that investigates Information Visualization and interactive machine learning, and Grounded Theory, a rigorous qualitative research method for discovering nuanced understanding of qualitative data. This dissertation defines and motivates this new approach, reviews relevant existing tools, builds the Log Timelines system. We present and analyze six case studies that use Log Timelines, a probe that we created in order explore Grounded Visual Analytics. In a series of case studies, we collaborate with a participant-investigator on their own project and data. Their use of Grounded Visual Analytics generates ideas about how future research can bridge the gap between qualitative and quantitative methods

QueryTogether: Enabling entity-centric exploration in multi-device collaborative search

Collaborative and co-located information access is becoming increasingly common. However, fairly little attention has been devoted to the design of ubiquitous computing approaches for spontaneous exploration of large information spaces enabling co-located collaboration. We investigate whether an entity-based user interface provides a solution to support co-located search on heterogeneous devices. We present the design and implementation of QueryTogether, a multi-device collaborative search tool through which entities such as people, documents, and keywords can be used to compose queries that can be shared to a public screen or specific users with easy touch enabled interaction. We conducted mixed-methods user experiments with twenty seven participants (nine groups of three people), to compare the collaborative search with QueryTogether to a baseline adopting established search and collaboration interfaces. Results show that QueryTogether led to more balanced contribution and search engagement. While the overall s-recall in search was similar, in the QueryTogether condition participants found most of the relevant results earlier in the tasks, and for more than half of the queries avoided text entry by manipulating recommended entities. The video analysis demonstrated a more consistent common ground through increased attention to the common screen, and more transitions between collaboration styles. Therefore, this provided a better fit for the spontaneity of ubiquitous scenarios. QueryTogether and the corresponding study demonstrate the importance of entity based interfaces to improve collaboration by facilitating balanced participation, flexibility of collaboration styles and social processing of search entities across conversation and devices. The findings promote a vision of collaborative search support in spontaneous and ubiquitous multi-device settings, and better linking of conversation objects to searchable entities

Evaluating An Information System To Provide Creative Guidance About Health-and-Safety In Manufacturing

Creativity’s importance to organizations and businesses is now recognized to be a precondition for both design and innovation. One strategy is to introduce new forms of information system that support human creative thinking by their employees. Most successful uses have been in professional disciplines in the creative industries such as design and theatre. This paper reports the design and evaluation of a new information system that was researched and developed to support human creativity in a non-creative industry – health-and-safety in a manufacturing plant. An established risk detection and resolution process in one plant was extended with the new system to support plant employees to think creatively about resolutions to health-and-safety risks. The new system was used in a manufacturing plant for over 3 months. Results revealed that a subset of the risk resolutions generated with the new system were more creative and more complete than risk resolutions generated without the system in a corresponding period. However, the employees needed more time than was available to generate more complete risk resolutions. The evaluation results led to coordinated changes to both the information system and work practices associated with it

Supporting Scholarly Research Ideation through Web Semantics

We develop new methods and technologies for supporting scholarly research ideation, the tasks in which researchers develop new ideas for their work, through web semantics, computational representations of information found on the web, capturing meaning involving people’s experiences of things of interest. To do so, we first conducted a qualitative study with established researchers on their practices, using sensitizing concepts from information science, creative cognition, and art as a basis for framing and deriving findings. We found that participants engage in and combine a wide range of activities, including citation chaining, exploratory browsing, and curation, to achieve their goals of creative ideation. We derived a new, interdisciplinary model to depict their practices. Our study and findings address a gap in existing research: the creative nature of what researchers do has been insufficiently investigated. The model is expected to guide future investigations. We then use in-context presentations of dynamically extracted semantic information to (1) address the issues of digression and disorientation, which arise in citation chaining and exploratory browsing, and (2) provide contextual information in researchers’ prior work curation. The implemented interface, Metadata In-Context Explorer (MICE), maintains context while allowing new information to be brought into and integrated with the current context, reducing the needs for switching between documents and webpages. Study shows that MICE supports participants in their citation chaining processes, thus supports scholarly research ideation. MICE is implemented with BigSemantics, a metadata type system and runtime integrating data models, extraction rules, and presentation hints into types. BigSemantics operationalizes type-specific, dynamic extraction and rich presentation of semantic information (a.k.a. metadata) found on the web. The metadata type system, runtime, and MICE are expected to help build interfaces supporting dynamic exploratory search, browsing, and other creative tasks involving complex and interlinked semantics

Association, Reflection, Stimulation: Problem Exploration in Early Design through AI-Augmented Mind-Mapping

The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks real advances in science. - Albert Einstein This dissertation aims at developing a computational framework to support the process of problem exploration in early design. To do so, we investigate digital mind-mapping as a tool for problem exploration and develop new algorithms and interaction workflows by leveraging large knowledge databases. The central premise of this work is that channeling the designer's thinking process through intelligent stimulation using such databases can augment designers' ability to reason about the problem at hand and creatively synthesize new ideas to address the problem. Design problems are typically ambiguous, ill-defined, unstructured, and open-ended. Therefore, learning about the problem and exploration of the problem domain is critical in early design to build a well-developed understanding of the context toward fruitful solution exploration in design. Despite the importance of problem understanding in design, little research has been devoted to investigating problem exploration activities in-depth and drawing a clear connection on the effects of such activities on the resulting design outcomes. Most current efforts focus exclusively on implementing methods for ideation, conceptualization, and concept evaluation wherein the solution space takes prominence. In this regard, this dissertation aims to complement this with a study of problem exploration techniques (mind-mapping and free writing) and evaluation in early design. We highlight the importance of problem-based exploration and learning, and share insights on how the structure and associative capability afforded by mind-maps affect ideation on the problem statement, product opportunity gap, and the needs around a given design context. It is common for designers to tend to commit to solutions too early and limit the potential of discovering creative and novel ideas in early design. This tendency is further pronounced with the advent of several digital design tools that are feature-rich and focus on design conceptualization and solution formulation, rather than design problem exploration. Additionally, much of the research in design theory and methodology has also mostly focused on conceptualization techniques such as C-Sketch and morphological matrix, that aim to support the formation of new solution concepts through modification and re-interpretation of rough initial ones. To complement these, in this dissertation, we emphasize the importance of problem exploration and brainstorming tasks towards design opportunity identification during early design. This is studied with the use of mind-maps, a technique that helps designers express their thoughts by making connections or associations between ideas around a given context. Further, we propose novel human-computer collaborative mind-mapping workflows for enhancing design experiences through novel textual, verbal and visual computer supports. Specifically, we designed and implemented two cognitive support mechanisms to help designers in inspecting design problems and generating ideas. Human-subject studies were conducted to examine how these systems perform and user perception. Based on the extensive investigation, this dissertation further shares insights on how to promote reflection in problem exploration by stimulating association across ideas, and develops design implications for intelligent AI-augmented workflows during early design exploratory tasks