Department Seminar Series
Title: Social Feedback: Social Learning from Interaction History to Support Information Seeking
Speaker: Scott Bateman, Ph.D. Candidate
Date:
Time: 3:30
Place: Room 159 Thorvaldson
Abstract:
Looking
for information on the Web has become a central part of many daily activities.
Even though information seeking is extremely common, there are many times when
these tasks are unsuccessful, because the information found is less than ideal
or the task could have been completed more efficiently. In unsuccessful
information-seeking tasks there are often other people who have knowledge or
experience that could help improve task success. However, people do not
typically look for help from others when they search the Web, because tasks can
often be completed alone (even if inefficiently). One of the problems is that
web tools provide people with few opportunities to learn from one another’s
experiences in ways that would allow them to improve their success. To
address this problem I will present the idea of social feedback.
Social
feedback is based on the theory of social learning, which describes how people
learn from observing others. In social feedback, observational learning is
enabled through the mechanism of interaction history – the traces of activity
people create as they interact with the Web. Social feedback systems collect
and display interaction history to allow information seekers to learn how to
complete their tasks more successfully by observing how other people have
behaved in similar situations. In this talk I will describe two different
social-feedback systems and describe studies that demonstrate that social
feedback can successfully support information seeking. The first system
supports global learning, by allowing people to learn new search skills
and techniques that improve information seeking success in many different
tasks. The second system supports local learning, in which people learn
how to accomplish specific tasks more effectively and more efficiently.
Finally,
I will discuss potential applications of social feedback outside of information
seeking and briefly cover some of my previous projects, which have focused on
examining techniques and building systems to support and encourage information
sharing. Biography:
Scott
Bateman is a PhD Candidate in Computer Science at the University of
Saskatchewan, Canada, supervised by Carl Gutwin and Gord McCalla. In his
dissertation work he studies social feedback by designing, building, and
studying systems that allow people to learn and receive guidance from the
behavior of other application users. He is broadly interested in the area of
Human-Computer Interaction and has performed research in social software,
information seeking, information visualization, interaction techniques, and
e-learning. During his graduate studies he interned at Microsoft Research
(Redmond, WA), IBM Research (Cambridge, MA), and the National College of
Ireland (Dublin).
