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The effect of prototyping material on verbal and non-verbal behaviours in collaborative design tasks
This paper reports a study of 23 controlled experiments, with a total of 99 individual tasks, between pairs of designers collaborating to solve a simple design task using four different types of prototyping media. The aim of the study was to correlate verbal and non-verbal behaviours across different types of media with a range of measurement indicators. Using innovative movement trail images we show how collaborative sketching activity results in attenuated use of interpersonal collaborative space when compared with cardboard, clay, and Lego, which provoked intensive collaboration. Furthermore, the sketching (control) condition resulted in pre-conceived ideas being executed when compared with the three-dimensional media, where ideas emerged through collaboration. This finding suggests that increased creativity in design can result through the careful choice of prototyping media at the beginning of the design process
A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space
We are developing a system for human-robot communication that enables people
to communicate with robots in a natural way and is focused on solving problems
in a shared space. Our strategy for developing this system is fundamentally
data-driven: we use data from multiple input sources and train key components
with various machine learning techniques. We developed a web application that
is collecting data on how two humans communicate to accomplish a task, as well
as a mobile laboratory that is instrumented to collect data on how two humans
communicate to accomplish a task in a physically shared space. The data from
these systems will be used to train and fine-tune the second stage of our
system, in which the robot will be simulated through software. A physical robot
will be used in the final stage of our project. We describe these instruments,
a test-suite and performance metrics designed to evaluate and automate the data
gathering process as well as evaluate an initial data set.Comment: 2017 AAAI Fall Symposium on Natural Communication for Human-Robot
Collaboratio
Gesture analysis for physics education researchers
Systematic observations of student gestures can not only fill in gaps in
students' verbal expressions, but can also offer valuable information about
student ideas, including their source, their novelty to the speaker, and their
construction in real time. This paper provides a review of the research in
gesture analysis that is most relevant to physics education researchers and
illustrates gesture analysis for the purpose of better understanding student
thinking about physics.Comment: 14 page
An environment for studying the impact of spatialising sonified graphs on data comprehension
We describe AudioCave, an environment for exploring the impact of spatialising sonified graphs on a set of numerical data comprehension tasks. Its design builds on findings regarding the effectiveness of sonified graphs for numerical data overview and discovery by visually impaired and blind students. We demonstrate its use as a test bed for comparing the approach of accessing a single sonified numerical datum at a time to one where multiple sonified numerical data can be accessed concurrently. Results from this experiment show that concurrent access facilitates the tackling of our set multivariate data comprehension tasks. AudioCave also demonstrates how the spatialisation of the sonified graphs provides opportunities for sharing the representation. We present two experiments investigating users solving set data comprehension tasks collaboratively by sharing the data representation
Attendee-Sourcing: Exploring The Design Space of Community-Informed Conference Scheduling
Constructing a good conference schedule for a large multi-track conference
needs to take into account the preferences and constraints of organizers,
authors, and attendees. Creating a schedule which has fewer conflicts for
authors and attendees, and thematically coherent sessions is a challenging
task.
Cobi introduced an alternative approach to conference scheduling by engaging
the community to play an active role in the planning process. The current Cobi
pipeline consists of committee-sourcing and author-sourcing to plan a
conference schedule. We further explore the design space of community-sourcing
by introducing attendee-sourcing -- a process that collects input from
conference attendees and encodes them as preferences and constraints for
creating sessions and schedule. For CHI 2014, a large multi-track conference in
human-computer interaction with more than 3,000 attendees and 1,000 authors, we
collected attendees' preferences by making available all the accepted papers at
the conference on a paper recommendation tool we built called Confer, for a
period of 45 days before announcing the conference program (sessions and
schedule). We compare the preferences marked on Confer with the preferences
collected from Cobi's author-sourcing approach. We show that attendee-sourcing
can provide insights beyond what can be discovered by author-sourcing. For CHI
2014, the results show value in the method and attendees' participation. It
produces data that provides more alternatives in scheduling and complements
data collected from other methods for creating coherent sessions and reducing
conflicts.Comment: HCOMP 201
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