Measuring Engineering Students? Intellectual Development Using Neural Network And Expert System Technology

Session 3530 Measuring Engineering Students’ Intellectual Development Using Neural Network and Expert System Technology Ronald L. Miller, Barbara M. Olds, Michael J. Pavelich Colorado School of Mines Summary Students completing an undergraduate engineering degree are expected to develop intellectual...

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Bibliographic Details
Published inAssociation for Engineering Education - Engineering Library Division Papers p. 3.401.1
Main Authors Pavelich, Michael J, Olds, Barbara, Miller, Ronald
Format Conference Proceeding
LanguageEnglish
Published Atlanta American Society for Engineering Education-ASEE 28.06.1998
Subjects
Engineering
Engineering education
Evaluation
Expert systems
Knowledge acquisition
Neural networks
Software
Software engineering
Students
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Summary:Session 3530 Measuring Engineering Students’ Intellectual Development Using Neural Network and Expert System Technology Ronald L. Miller, Barbara M. Olds, Michael J. Pavelich Colorado School of Mines Summary Students completing an undergraduate engineering degree are expected to develop intellectually in addition to acquiring specific engineering knowledge and skills. However, effectively measuring intellectual development involves a time-consuming and expensive interview conducted and evaluated by trained human experts. In order to develop a quick and inexpensive alternative method for making these measurements, we are writing a software package based on neural network and expert system technology to emulate the interview and evaluation process. If successful, the software will allow engineering programs to rapidly and reliably measure the intellectual development of their students as a formative and summative assessment tool. This paper describes our progress on the project and remaining research questions under investigation.