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

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Conference

1998 Annual Conference

Location

Seattle, Washington

Publication Date

June 28, 1998

Start Date

June 28, 1998

End Date

July 1, 1998

ISSN

2153-5965

Page Count

8

Page Numbers

3.401.1 - 3.401.8

Permanent URL

https://peer.asee.org/7275

Download Count

21

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Paper Authors

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Michael J. Pavelich

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Barbara Olds

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Ronald Miller

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

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.

Introduction and Background

Most engineering programs expect that their students will develop intellectually in addition to acquiring knowledge and skills in a specific engineering discipline. However, nearly all measures of student achievement are focused on content knowledge, process ability (e.g. design), or communication skills; students are assumed to be developing intellectually, especially in their ability to think critically, but rarely are meaningful data collected and reported which support such an assumption.

Using the techniques presently available to us, measuring intellectual development is difficult, time-consuming, and expensive. However, the recent movement towards outcomes assessment now requires reliable measures of students’ abilities to make reasoned decisions as they solve complex problems. For example, ABET requires institutions to develop assessment processes which can demonstrate “that the outcomes important to the mission of the institution and the objectives of the program are being measured.” [1]

Numerous pencil-and-paper test instruments including the Watson-Glaser Critical Thinking Appraisal [2] and California Critical Thinking Skills Test [3] purport to measure some aspect of intellectual development or ability to think critically. These types of tests are typically inexpensive and easy to administer, but their validity in measuring true intellectual development and thinking ability is questionable because pencil-and-paper instruments rely on close-ended questions with one right answer; no information is collected describing how or why the student chose a particular answer and no mechanism exists to adapt exam questions based on prior responses from the student.

Pavelich, M. J., & Olds, B., & Miller, R. (1998, June), Measuring Engineering Students? Intellectual Development Using Neural Network And Expert System Technology Paper presented at 1998 Annual Conference, Seattle, Washington. https://peer.asee.org/7275

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