|
Research
Description
Progressive
engineering educators are transforming engineering courses from a passive,
lecture-based delivery mode to active, student-centered learning communities
in which students "make meaning" of what they are learning.
With this transition comes the need to find better techniques for accurately
assessing the complex activity that we call learning traditional
exams are often no longer adequate. One of my projects involves developing
graphics-based interactive software which measures students intellectual
development using expert system and neural network technologies. We are
studying human experts who measure intellectual development using a lengthy
and complex interview process and converting the experts knowledge
into a series of open-ended scenarios which are designed to measure specific
student beliefs about the nature of knowledge, use of evidence in problem-solving,
and the role of authorities in seeking truth. Student responses to each
scenario are scored by a trained neural net which places each student
on a hierarchical scale ranging from a dualistic (black/white) objective
view of knowledge, through a relativist view (all ideas equally valid)
to a more realistic view in which the best answer to any real-world problem
is contextually based. This project, supported by the U.S. Department
of Education, is currently testing the alpha version of our software on
student volunteers. When completed and validated, the program will be
used to assess the longitudinal intellectual growth of our students while
at CSM and will provide us with valuable data for further improving our
curriculum and teaching methods.
|