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Computer-based Adaptive Testing for Assessing Problem-Solving Skills N. Khandan

Civil & Geological Engineering Department New Mexico State University, Las Cruces, NM 88003

Introduction Problem-solving is one of the skills that engineering programs strive to instill in their graduates. In typical engineering programs, students are expected to gain this skill by observing instructors solving example problems and by practicing with homework assignments that are similar to example problems. These problems can be elementary problems, complex problems, or open- ended problems. Since complex problems and open-ended problems can be solved by breaking them down to a series of elementary problems, it is essential that students master the basic skills required for solving elementary problems.

In recent times, employers, professional organizations, and accreditation agencies have been expressing concern about the poor problem-solving skills of engineering graduates [1-4]. The national performance of engineering graduates in the Fundamental of Engineering (FE) exam conducted by the National Council of Examiners for Engineers and Surveyors (NCEES) affirms this concern. Figure 1, for example, shows a statistically significant declining trend in the percentage of questions answered correctly by civil engineering graduates in the FE exam. Considering that the problems in the FE Exam are elementary problems and that it is a summative evaluation of engineering education and is a prerequisite for professional licensure, such poor performance is alarming. This paper presents a computer-based system that has the potential to improve and assess problem-solving skills of engineering students.

Literature Review The importance of conceptual knowledge as one of the prerequisites for expert-like problem- solving has been recognized in several studies [5-11]. Dufresne et al [9, 11] have proposed a model for problem solving, identifying three key knowledges: i) concept knowledge, ii) operational/procedural knowledge, and iii) problem-state knowledge. According to this model, the conceptual knowledge of an expert is richly clustered and hierarchically arranged with strong bi-directional links with the other two knowledges. In contrast, the novice’s conceptual knowledge is poorly clustered and chronologically arranged, with weak, unidirectional, and inappropriate links with the other two knowledges.

Clough and Kauffman [12] have recommended that students should be given opportunities to make repetitive “connections” between concepts in different contexts and applications, to achieve deeper and long lasting understanding that can enhance problem-solving skills. By challenging the students, starting with single-concept problems and gradually progressing to multi-concept problems, and by making repetitive connections between the different concepts, students are able to apply concepts learned in different places and times to solve problems in new “Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright @2005, American Society for Engineering Education”

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Khandan, N. (2005, June), Computer Based Adaptive Testing For Assessing Problem Solving Skills Paper presented at 2005 Annual Conference, Portland, Oregon. 10.18260/1-2--15181