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Employing Model-Eliciting Activities in Cybersecurity Education

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Computing & Information Technology Division Technical Session

Tagged Division

Computing & Information Technology

Tagged Topic

Diversity

Page Count

10

DOI

10.18260/p.26943

Permanent URL

https://peer.asee.org/26943

Download Count

555

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Paper Authors

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Mayari I. Serrano Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0003-1033-6459

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MAYARI SERRANO is currently a graduate research assistant in the College of Engineering at Purdue University. She earned her B.S. degree from the Army Polytechnic School, Quito, Ecuador. She completed her M.S. in Computer and Information Technology at Purdue University. Mayari is currently a PhD student at Purdue University and is working in for the Women in Engineering Program. Her interests include foster STEM enthusiasm, and technology innovation.

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Alejandra J. Magana Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0001-6117-7502

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Alejandra Magana is an Associate Professor in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyber-physical systems,visualizations and modeling and simulation tools.

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Baijian Yang Purdue University

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Dr. Yang is current an Associate Professor at Department of Computer and Information Technology, Purdue University

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Abstract

Employing Model-Eliciting Activities in Cybersecurity Education

College cybersecurity courses should ensure that the activities employed engage and allow translation from conceptual knowledge to practice. We propose to use model-eliciting activities (MEAs) to develop students’ representational fluency in the cybersecurity domain. MEAs are activities that intent to simulate real-word client-driven scenarios, this activities relay on teamwork and student ability to apply concepts. Properly constructed and implemented MEAs can increment use of: (1) student reflection tools in assessments, and (2) learning technologies. MEAs require students to iteratively build, test and refine their knowledge by encouraging students to build different forms of representations and connect and translate among them (Yildirim, Shuman, Besterfield-Sacre, & Yildirim, 2010). They focus on eliciting from students conceptual models that they iteratively revise in problem-solving episodes (Hamilton, et al., 2008). The cybersecurity topic chosen for the MEA implementation was Hyper-Text Transfer Protocol Secure (HTTPS). The MEA developed, “Migration to HTTPS”, comprises core concepts of HTTPS and their application on a real-world cybersecurity tasks. The activity was pilot tested with a group of 12 third year Electrical and Computer Engineering undergraduate students who participated in a Four-hour workshop in cryptography prior to working on the project in a group of two.

In this paper we will describe the underlying learning theory that guided our rationale for using MEA as a pedagogical approach to promote deep learning in cybersecurity principles. We will also describe how design principles guided the design of the “Migration to HTTPS MEA”, along with a justification of how we aligned learning objectives with assessment procedures and the implementation of the MEA. Finally, we will present the results of our pilot study, identify implications for teaching and learning, and propose future work.

Serrano, M. I., & Magana, A. J., & Yang, B. (2016, June), Employing Model-Eliciting Activities in Cybersecurity Education Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26943

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