“New Tools for Learners”
Larry
L.
Stewart
The College of Wooster, USA
Peter
L.
Havholm
The College of Wooster, USA
In a recent essay in Salon, Christopher Ott argues that
much of educational technology is used in the service of a model of education as
"a passive transfer of information ...." As Ott says, "Web sites and CD-ROMs are
very good at delivering information, but not so good at teaching what it means
or raising difficult questions about it." During the last ten to twelve years,
we have assembled a portfolio of technological tools which we believe lead
students in the undergraduate classroom to ask those difficult questions and to
become active learners rather than passive recipients. We have developed two of
these programs, and the others are readily available. This demonstration will
allow participants to experiment with several of these tools, to see examples of
student work, and to consider how the tools might be used in their own
classrooms. Of the tools we use, we propose to have four available for
demonstration.
We will demonstrate the two programs we have developed (and, in earlier versions,
discussed at ALLC/ACH '98): the Linear Modeling Kit (LMK) and the Stylistic
Analysis Kit (SAK). As well, we have also used and will demonstrate a freeware
beta version of PennMUSH and SemNet(r), a tool for creating conceptual networks.
The Linear Modeling Kit or LMK is an authoring system which allows users to
create applications that generate any kind of text according to principles
proposed by the user. For example, a student can use the LMK to create a
"tragedy generator" by entering what the student perceives to be the parts or
elements of a tragedy, any principles of order among those parts, and
characteristic text for each part. Depending on the complexity of the input, the
generator will produce hundreds, thousands, or millions of different texts. The
task of creating a generator calls for students to think abstractly insofar as
they are dealing with stories, not simply a story. That is, students must know
well a number of tragedies or romance novels or bildungsroman in order to
abstract those qualities or elements that the texts share or that seem central
to the genre. However, they must also think very precisely in order to translate
their understandings into the unforgiving and unambiguous language of what is
essentially computer programming. In essays or articles, we, as well as our
students, know how to smooth over those things about which we are not quite
sure; we know how either to hide ambiguity or to make it a virtue. Obviously,
one cannot do that when creating a generator.
In short, students have to work at a level both of abstraction and of detail that
may be greater than that forced by a paper. The Stylistic Analysis Kit is a
combination concordance and counting program. When a text is opened from within
the program, the SAK displays basic statistical information about word,
sentence, and paragraph lengths and a word list, which can be arranged by
frequency or alphabetically or which can show punctuation. Students can learn to
use the SAK with less than five minutes of instruction, a significant factor in
undergraduate education. In our classes, students have used the SAK to consider
both literary texts and their own essays. In either case, students find
themselves having to confront and explain the relationship between the abstract
and the specific or concrete. When analyzing their own essays, for example,
students constantly are driven back to their own texts to account for the
statistics they have discovered. Nearly all find themselves, to return to Ott's
phrasing, raising difficult questions about information. SemNet(r), by the
SemNet Research Group, allows users to create layered and linked conceptual maps
or networks. Our use of SemNet(r) has been primarily in writing courses
although, again, students have used it both with professional writing and in the
creation or analysis of their own essays. We have found that asking students to
create Semnet networks causes them to think deeply about the relationships
between concepts either in their own papers or in professional essays we have
assigned. Creating a visual map of relationships forces students not only to be
explicit about the connections between ideas but to recognize when those
connections are missing.
In the demonstration, participants will be able to look at networks created by
students and experiment with the program by creating their own networks.
Students at our college have also used a MUSH to improvise an on-line serial
drama as a laboratory section of an English course in dramatic structure. In the
course, students play characters and invent actions on-line, edit the logs of
their online sessions into scripts, and then publish a final version on the web.
By writing and publishing a play, students in the class are testing the
principles of structure they have learned from their reading of a dozen plays
and Aristotle's Poetics. They are forced to confront
the concrete implications of abstract ideas. While it would be impractical for
this demonstration to set up a full-scale MUSH environment (which would require
at least two Macintosh machines linked to the internet), we can show samples of
student work in our MUSH and the ultimate form of those samples as a drama
published on the web. The tools we will demonstrate engage students in making or
doing, not in receiving information passively. Using such tools, students learn
to use the new technology to explore and test ideas.