| CSCL 2002 in Boulder, Colorado |
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| Documenting Collaborative Interactions Workshop |
| Colourful Hints for Collaborative Climbing |
| Jonathan Cohen, James Dai, Michael Wu, Sarah Yang |
| UBC EGEMS Research |
| A team of four EGEMS members (Jonathan Cohen, James Dai, Michael Wu, Sarah Yang)
was dispatched Monday morning to the Computer Support for Collaborative Learning
2002 conference to present their current research in a workshop and receive insights
and feedback. The conference was held in Boulder, Colorado between January
7th to 11th. Though this team would only participate in half the conference,
they set high goals and had the vision to meet the challenges they faced. This
web page is a journal that tracks what happened at the conference - it is incomplete as there
are still pictures that need to be developed, scanned, and added here. Click here for our brief proposal paper to the conference (PDF format). Many thanks to Dr. Maria Klawe, Dr. Bob Woodham, and the UBC Computer Science Department for helping to sponsor our trip! |
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About EGEMS |
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| EGEMS, Electronic Games for Education
in Mathematics and Science, is an interdisciplinary group from the
University of British Columbia. Directed by
Dr. Maria Klawe,
EGEMS is interested in researching the role of educational computer games in the
classroom environment in supporting and reinforcing mathematical concepts learned
in class. A parallel focus is on the gender issues involved. EGEMS works with a
multitude of people ranging from elementary school teachers, professors, and
industrial companies. |
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What is PrimeClimb? |
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| Screenshot of PrimeClimb game |
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| PrimeClimb, created by EGEMS, is an educational computer game that
supports introductory classroom teachings of prime factorization for grade six
and seven students. The game is played in partners, and success can be
achieved through collaborative play. Pairs of students climb a treacherous
mountain together with only their tools and wits. The climbers
are limited in the distance they may travel because a safety rope constrains
their movement. This mountain is made up of numbers which climbers may climb on.
When a climber climbs onto a number that has a shared common factor with his
partner's number, that climber falls. The safety rope helps the fallen climber
recover. This rope acts as a constraint at times and encourages climbers
to work together. A pick tool is provided to reduce any mountain number by one. This
can be particularly helpful in difficult situations. |
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Our Current Research |
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| PrimeClimb is currently being used in two separate research projects. One involves
a socially interactive animated pedagogical agent, and the other involves shared
hint-giving collaborative tools. The latter is the primary focus of this web site
as it was the research discussed at the CSCL conference. |
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In the classroom, traditional learning involves students communicating to
learn from one another. Shared hint-giving tools facilitate
this in the educational computer environment. Thus, various tools have been
integrated into PrimeClimb, most notably the Magnifying Glass and Flag tools.
These tools display factor breakdowns, which often prove useful in finding
shared common factors between numbers. Several factors that define a "shared"
tool are: resource limitation, visual effect permanence, distributed nature of feedback (do
both players see the result, or just the tool user, or just the partner), their effects. |
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The Magnifying Glass tool presents factorization information visually as a factor tree.
It is unlimited in number and the factor tree remains visible so long as the user does not apply
the magnifying glass onto another number (in which the factor breakdown of the new number is
displayed). Only the user of this tool will see its results. |
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| The magnifying glass tool |
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| The Flag tool presents one equation that contains the factors of a number. This tool is limited
in number. When used on a mountain number, a flag marks the usage area and an equation is placed
on the screen. This equation, which both players can see, remains on the screen throughout the
entire game. |
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| The flag tool |
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| Currently, we are interested in exploring whether or not shared hint-giving tools improve
mathematical and collaborative learning through encouragement of individual accountability
and communication between peers. One way of promoting accountability on the individual level
is to allow both members of the team to use a tool and then place a team limit on the number
of tool usages. (The flip side would be to put individual limits on the number of available
resources.) For example, we may find that students teach one another through the use of their
shared tools. In order to draw conclusions about patterns of behaviour and learning, we need
to record and document both a student's game inputs and a student's off-screen interactions
while playing PrimeClimb. |
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| Game log documentation and video annotations |
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| To record the former, game play logs generated by the application can be used. For
the latter, we can video tape the playing sessions of a student. This can be done by
recording (with the use of two cameras): what is happening on the computer screen, and what
physical actions are being performed. Note that these video feeds should ultimately be
synchronized to make annotations easier. It is important to recognize that we must overcome
some underlying challenges of documenting social interactions. For example, when annotating video,
what criteria constitute a "student explanation" or a "hand gesture"? |
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| Synchronizing the game screen with social interations |
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Documenting Collaborative Interactions |
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| Challenges For our study, we need to document informal activity to find patterns in collaborative interactions. Two challenges we face are: (1) Combining documentation of social interactions with documentation of game events, and (2) Facilitating the analyses of various pattern hypotheses. Our Approach To combine both social interaction documentation and game event documentation, we can create a multi-dimensional timeline that includes both sets of data. This can potentially aid in the identification of interesting patterns of behaviour through visual pattern matching.
We want to adopt an open-ended approach to these challenges such that we can satisfy openness. If we were able to support mechanisms of testing various pattern hypotheses about how tool usage and planning ties in to communication, we would be able to quickly answer different questions and address specific hypotheses. By annotating only interesting items and then analyzing that data, we can achieve our open-ended goal. This is because we can come up with interesting questions, and only annotate what is necessary from the video. If that information is already processed, then much time can be saved (as annotation of video can be very time consuming). This methodology allows others to carry out future work using the same data set to test out new ideas and suggestions. |