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Computers learning from students

  • 1.  Computers learning from students

    Posted 03-02-1998 21:31
    Charlie Wankel wrote:

    >I would appreciate your posting the press release that you came across to
    mg-ed-dv.

    >[snip]

    >Cybercollegially,
    >Charlie Wankel
    >netmaster mg-ed-dv

    ************************************

    While doing some research for a client, I ran across this item. Fascinating
    possibilities. Anyone want to speculate on new applications beyond the
    classroom ? What if we substitute "customers" for the word "students"

    So here's the press release:

    FOR IMMEDIATE RELEASE: 27 FEBRUARY 1998


    Students Teaching Computers Teaching Students . . .

    Students learning from computers is nothing new, but now Temple University
    electrical engineering professor Brian P. Butz has devised a way that
    computers can learn back from the students.

    As a student answers a series of questions, Butz's tutorial program--which
    will be used in several classes at Temple this Fall--determines not only
    what that student does and does not know, but also how he or she likes to
    learn. It then creates an individualized program of study. "The intelligent
    system will sense the direction a student is taking through the interactive
    material, detect logical flaws the student is making and provide the
    student with focused tutoring," he explains, adding that the program
    software is adaptable to a wide variety of subject areas. His project will
    receive significant support from the National Science Foundation (NSF)
    over the next two years.

    Butz says that computer modules have come a long way from the
    right-or-wrong "canned remedial responses" of the past. Current programs
    have more explicit knowledge of the subject matter being taught and can
    give expanded explanations to the user. His innovation continues this
    progress by introducing an "expert system" to create an "interactive
    multimedia intelligent tutoring system." The expert system monitors and
    records every interaction of the student with the program (selection of an
    answer, change of selection, computation, and so on). It also "interrupts"
    the session occasionally to ask the user to clarify a response or explain
    why that answer was chosen. Once it has gathered enough information
    about the student's learning patterns, it modifies its questions to focus
    on the material the student understands least, presented in the way
    the student learns best.

    Butz reports that his expert system could be used for almost any subject,
    and that "it will be especially helpful for students in introductory and
    remedial classes. Students who do not quickly master basic skills are
    sometimes left behind, and become passive observers of material they do not
    understand." He hopes that "tutorials using the expert system will help
    teachers face the challenge of meeting the students' academic needs and
    ensuring that they are active participants in their own education."

    Butz will use his tutoring system in electrical engineering courses this
    coming Fall and Spring. He hopes to find results similar to those of his
    colleagues Gerardo Mendoza and Dan Reich of the mathematics department.
    They have written a interactive program which enables math students to work
    through calculus assignments on a class webpage. Their Calculus on the Web
    (COW) project, which has also received NSF funding, has resulted in an
    increase in the retention, enthusiasm, and performance of students in
    first- and second-semester calculus classes at Temple. They have made their
    program available to all high school and college students via the internet.


    Students supplementing classroom learning with computer tutorials is
    nothing new, but now Temple electrical engineering professor Brian P. Butz
    has devised a way that those tutorials can learn back from the students. As
    each student answers questions, his "expert system" gathers information
    about his or her learning patterns. It then modifies future questions to
    focus on the material the student understands least, presented in the way
    the student learns best.


    Walter Derzko
    Director Brain Space
    (formerly the Idea Lab at
    the Design Exchange)
    Toronto
    (416) 588-1122
    wderzko@pathcom.com