Information Technology Reference
In-Depth Information
Instant Messaging system, which was freely available and was already familiar to
many students. We included a researcher in the chat room with each small group of
students. The facilitator told the students their math task, dealt with any technical
difficulties, posted drawings from the students on a web page where they could be
seen by all the students, notified the group when the session was over and saved an
automatically generated log of the chat. In this way, we obtained a complete and
objective log of the interaction, captured everything that the students shared on their
computers and excluded any unknown influences from affecting the interaction.
The issue of including everything affecting the interaction is a subtle issue. Of
course, the interaction is influenced by the life histories, personalities, previous
knowledge and physical environment of each student. A student may have win-
dows other than AIM open on the computer, including Internet browsers with math
resources. A student may be working out math problems on a piece of paper next
to the computer. Also, a student may leave the computer for some time to eat, lis-
ten to music, talk on the phone and so on without telling anyone in the chat. In
such ways, we do not have information about everything involved in a particular
student's online experience. We do not even know the student's gender or age. We
do not know whether the student is shy or attractive, speaks with an accent or stut-
ters. We do not know if the student usually gets good grades or likes math. We do
not know what the student is thinking or feeling. We only know that the students
are in an approximate age group and academic level—because we recruited them
through teachers. However, the VMT Project is only concerned with analyzing the
interaction at the
group unit of analysis
. Notice that the things that are unknown to
us as researchers are also unknown to the student group as a whole. The students do
not know specifics about each other's background or activities—except to the extent
that these specifics are brought into the chat. If they are mentioned or referenced in
the chat, then we can be aware of them to the same extent as are the other students.
The desire to generate a complete record for analysis of everything that was
involved in a team's interaction often conflicted with the exploration of technol-
ogy and service design options. For instance, we avoided speech-based interaction
(VOIP, Skype, WIMBA) and support for individual work (e.g. whiteboards for
individual students to sketch ideas privately), because these would complicate our
review of the interactions. We tried to form teams that did not include people who
knew each other or who could interact outside of the VMT environment.
In addition to personal influences, the chat is responsive to linguistic and cultural
matters. Of course, both students and researchers must know English to understand
the chats. In particular, forms of English that have evolved with text chat and cell-
phone texting have introduced abbreviations, symbols and emoticons into the online
language. The linguistic subculture of teenagers also shows up in the VMT chats.
An interdisciplinary team of researchers comes in handy for interpreting the chats.
In our case, the research team brought in experience with online youth lingo based
on their backgrounds as Math Forum staff, teachers or parents.
The early AIM chats used simple math problems, taken from standardized
math tests and Math Forum Problems-of-the-Week. One experiment to compare
individual and group work used problems from a standardized multiple-choice
