Filtering by
- All Subjects: human-computer interaction
- All Subjects: scenario planning
- Creators: Byrd, Andrew
- Creators: Maciejewski, Ross
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task is created that aims
to determine ground-truth by collecting information in
two different ways: rankings and numerical estimates.
Results indicate that accurate collective decisions can
be achieved with less people when ordinal and cardinal
information is collected and aggregated together
using consensus-based, multimodal models. We also
show that presenting users with larger problems produces
more valuable ordinal information, and is a more
efficient way to collect an aggregate ranking. As a result,
we suggest input-elicitation to be more widely considered
for future work in crowdsourcing and incorporated
into future platforms to improve accuracy and efficiency.
In this dissertation, I seek to advance both the knowledge of limitations in current technologies used in practice as well as the mechanisms that can be used for large-scale support. The overall research question I explore is: “How can we support large-scale creative collaboration in distributed online communities?” I first advance existing support techniques by evaluating the impact of active support in brainstorming performance. Furthermore, I leverage existing theoretical models of individual idea generation as well as recommender system techniques to design CrowdMuse, a novel adaptive large-scale idea generation system. CrowdMuse models users in order to adapt itself to each individual. I evaluate the system’s efficacy through two large-scale studies. I also advance knowledge of current large-scale practices by examining common communication channels under the lens of Creativity Support Tools, yielding a list of creativity bottlenecks brought about by the affordances of these channels. Finally, I connect both ends of this dissertation by deploying CrowdMuse in an Open Source online community for two weeks. I evaluate their usage of the system as well as its perceived benefits and issues compared to traditional communication tools.
This dissertation makes the following contributions to the field of large-scale creativity: 1) the design and evaluation of a first-of-its-kind adaptive brainstorming system; 2) the evaluation of the effects of active inspirations compared to simple idea exposure; 3) the development and application of a set of creativity support design heuristics to uncover creativity bottlenecks; and 4) an exploration of large-scale brainstorming systems’ usefulness to online communities.
There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.
Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.