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Work-in-Progress: The Effects of Concurrent Presentation of Engineering Concepts and FEA Applications

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016





Conference Session

Computing & Information Technology Division Poster Session

Tagged Division

Computing & Information Technology

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Paper Authors


John Martin Youngstown State University

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John Martin is an Assistant Professor of Mechanical Engineering at Youngstown State University. John has seven years of mechanical engineering experience.

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Anna M. Martin Kent State University

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Anna Martin is a doctoral student of Educational Psychology and Instructional Technology at Kent State University and a high-school social studies teacher at Canfield High School with 9 years of experience.

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Work-in-Progress: The Effects of Concurrent Presentation of Engineering Concepts and FEA Applications

Computer-based instructional materials, specifically engineering software, are a necessary component of many practical applications of engineering knowledge across many engineering domains. In order to most effectively present instructional material containing computer technologies, instructional designers must consider the human cognitive architecture. Existing research regarding cognitive load theory (CLT) has examined the ways in which information should be presented to maximize learning while reducing strain on a student’s working memory capacity (Mayer & Moreno, 2003). However, a gap in current understandings of instructional delivery of computer-based materials lies in the sequencing of learning content-based concepts and the computing software, especially when considering the current knowledge base of the student (Kalyuga et al., 2003).

To maximize learning the instructional delivery of course materials should differ for novice and expert learners (Bruning, Shaw & Norby, 2010). In fact, when experts are presented information in the same way as novices research suggests they may experience the “expertise reversal effect,” where the presentation of information is redundant and has a negative effect on learning (Kalyuga et al., 2003). At this point there has been a great deal of research assessing the negative effects of CLT on student learning, however there is a very limited amount of research that examines the simultaneous learning of computer software and engineering concepts. Prior research has identified the benefits of sequential presentation of information to learners with low-levels of computer-based technology knowledge, while much less is known about the presentation of computer-based materials to those that are more experienced (Clarke, Ayres, Sweller, 2005; Kalyuga et al., 2003).

As a result of existing gaps in the research on CLT, this study will further examine the effect of concurrently learning engineering software skills in applying software applications to engineering concepts. More specifically, we will focus on one research question: Does concurrent presentation of engineering software and engineering concepts effect student learning for those students with high-levels of existing software knowledge?

Given the limited understanding of learners with advanced technology skills, we will seek to gain a better understanding of the effects of a concurrent presentation of Finite Element Analysis (FEA) software skills and application of engineering concepts on student learning. Students within an FEA design course with a confirmed demonstrated knowledge of the software will be divided into two groups, where instructional design will differ between sequential and concurrent presentation of information. Additionally, a subjective measure of cognitive load will be used to quantify between group cognitive load, while a posttest will measure student learning of both software skills and engineering knowledge. The instructional technique will serve as the independent variable consisting of two groups, sequential and concurrent instructional groups, while engineering concept knowledge and FEA skills scores, along with the subjective cognitive load scores will serve as the dependent variables to be measured using multivariate analysis of variance (MANOVA). These results will be important, as student understanding of both engineering concepts along with related engineering software encourages student ability to apply both aspects of knowledge to problems encountered in industry. References Bruning, R. H., Schraw, G. J., & Norby, M. N. (2010). Cognitive Psychology and Instruction (5thedition), Pearson Merrill Prentice Hall.

Clarke, T., Ayres, P., & Sweller, J. (2005). The impact of sequencing and prior knowledge on learning mathematics through spreadsheet applications. Educational Technology Research and Development, 53(3), 15-24.

Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational psychologist, 38(1), 23-31.

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational psychologist, 38(1), 43-52.

Martin, J., & Martin, A. M. (2016, June), Work-in-Progress: The Effects of Concurrent Presentation of Engineering Concepts and FEA Applications Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.27050

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