Year: 2020
Type: conference-paper
Abstract: NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Determining the Factor Structure of the Materials Concept Inventory Abstract A 30-item Materials Concept Inventory (MCI) was created six years ago in order to help measure conceptual change and identify misconceptions in introductory materials science and engineering classes. Since that time it has proven useful as a tool to examine student conceptual knowledge and the effect of pedagogy on conceptual change. However, the current effort and prior work by others indicate that an MCI with a reduced number of topical areas and more multiple representations of important concepts could improve its validity and reliability. In particular, we are reporting in this research the analysis of the factor structure of the MCI using a principle component factor analysis. 318 students completed pre-post course testing of the MCI while enrolled in sections of an introductory materials engineering course in six different semesters. There was a good degree of internal consistency, and the principal components analysis supported the notion of a seven-factor solution. The reliability coefficients for the MCI was determined to be alpha = .73. Factor analysis is being used to test the effect of substitution of new or modified items to improve the construct validity of the MCI. Ultimately, a more accurate measurement tool has the potential to improve student learning through better assessment of the effect of pedagogy on student conceptual change. Introduction Engineering faculty sometimes comment that even students who correctly solve problems in phase diagrams may mistakenly believe that, the atom size in a substance increases as it changes from liquid state to gaseous state or when heated1. These observations are supported by evidence in the literature that suggests that engineering students taking an introductory materials science course often have similar misconceptions about how molecular-scale processes fundamentally differ from observable, macroscopic causal behavior we experience in our daily lives2. The Accreditation Board for Engineering and Technology (ABET) commissioned a team of researchers at the Penn State Center for the Study of Higher Education to assess the impact of the accreditation criteria on student learning outcomes3. The first learning outcome of the ABET, Criterion 3 (a), states that, "Engineering programs must demonstrate that their graduates have an ability to apply knowledge of mathematics, science and engineering appropriate to the discipline"3. Simply stated, this requires that students need to be able to transfer previously acquired knowledge and skills to new engineering learning situations and applications. One important subject area taught in a fundamental way in chemistry and in an applied way in engineering is the domain of materials. It is an area of fundamental conceptual knowledge that is applied to a broad set of disciplines in chemical, mechanical, aerospace, physics and materials engineering4. It is usually assumed that prerequisite science classes provide students with a foundation of content that is strong enough to be challenged by this application to new domains, but students’ incorrect prior conceptions may be a barrier which handicaps this transfer.
DOI: 10.18260/1-2--4969
Institution: Arizona State University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: bronze
Funder: National Science Foundation
OpenAlex ID: W2594470129