Mental Models of Students and Practitioners in the Development of an Authentic Assessment Instrument for Traffic Signal Engineering

David S. Hurwitz; Shane A. Brown; Mohammad Rabiul Islam; Kelvin Daratha

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Conference: 2013 ASEE Annual Conference & Exposition
Location: Atlanta, Georgia
Publication Date: June 23, 2013
Start Date: June 23, 2013
End Date: June 26, 2013
ISSN: 2153-5965
Conference Session: NSF Grantees' Poster Session
Tagged Topic: NSF Grantees Poster Session
Page Count: 6
Page Numbers: 23.896.1 - 23.896.6
DOI: 10.18260/1-2--22281
Permanent URL: https://peer.asee.org/22281
Download Count: 342

Paper Authors

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David S. Hurwitz Oregon State University orcid.org/0000-0001-8450-6516

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Dr. David Hurwitz is an assistant professor in the Department of Civil and Construction Engineering at Oregon State University and he serves as the point of contact for the Driving and Bicycling Research Laboratory. He is interested in the integration of user behavior in the design and operation of transportation systems. He teaches classes at the graduate and undergraduate level in highway engineering, traffic operations and design, isolated traffic signals, and driving simulation.

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Shane A. Brown P.E. Washington State University orcid.org/0000-0003-3669-8407

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Dr. Shane Brown conducts research on cognition and conceptual change in engineering. He received his bachelor’s and Ph.D. degrees from Oregon State University, both in Civil Engineering. His Ph.D. degree includes a minor in Science and Mathematics Education. His master’s degree is in Environmental Engineering from the University of California, Davis. Dr. Brown is a licensed professional civil engineer and has six years of experience designing water and waste water treatment facilities in central California. He was the recipient of the NSF CAREER award in 2011. Dr. Brown’s research focuses on theoretical approaches to understanding why some engineering concepts are harder to learn than others, and how the concepts are embedded in contexts.

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Mohammad Rabiul Islam Oregon State Univeristy

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Mohammad Islam is a Ph.D. student of Civil Engineering at Oregon State University. He earned his M.S. in Civil Engineering from the University of Idaho in 2011. He earned his B.S. in Civil Engineering from the Bangladesh University of Engineering & Technology in 2005.
Islam's current research at the School of Civil and Construction Engineering at Oregon State University includes developing a concept inventory for traffic signal timing, a tool for undergraduate transportation engineering education. He is also studying driver behavior using driving simulator to identify benefits and issues of traffic signal countdown timer in USA
His previous research at the National Institute for Advanced Transportation Technology (NIATT) at the University of Idaho include extending the architecture of previously developed Smart Signal System by NIATT using ITS communication protocol (NTCIP) to automatically implement performance monitoring and control strategy decisions. He has also studied queue spill-back mitigation strategies applying hardware-in-the-loop simulation (HILS) with ASC/3 traffic controllers and VISSIM micro-simulation.

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Kelvin Daratha Graduate Student at Washington State University

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Abstract

Mental Models of Students and Practitioners in the Development of an Authentic Assessment Instrument for Traffic Signal Engineering By David S. Hurwitz, Shane Brown, Kelvin Daratha, & Mohammad IslamConducting fundamental engineering education research on student andpractitioner ways of knowing is a critical and often overlooked first step incurriculum and assessment design. This research project determined the coreconcepts related to and synthesized student and practitioner conceptualunderstanding of isolated and coordinated signal systems. A modified version ofthe Delphi Method was used to develop consensus among 16 transportationengineering faculty and engineering professionals on the most consistent, relevant,and core concepts in traffic signals. The most important concepts are warrantanalysis (or determining the need or justification for a new signalized intersection)and signal timing, calculations, and phasing. Clinical interviews were conductedwith approximately 50 students and 35 early career engineering professionals toinvestigate, characterize and synthesize their understandings of traffic signaloperations. Comparison of understandings were conducted to determinedifferences in how engineering students and early career engineering professionalsthink about signal design and to determine persistent misconceptions within thisdiscipline. Additionally, interviews were analyzed to determine commonmisconceptions. This research will produce a taxonomy of differences in theknowledge of students and early career engineering professionals related to trafficsignals and a summary of misconceptions. These project outcomes will be the basisof a newly-developed concept inventory and curriculum, such as inquiry basedconceptual exercises and assessments, both of which will be situated inengineering thinking and design. This study is significant because it fundamentallyadvances the field by identifying differences in conceptual understanding betweenpracticing engineers and students with respect to the design and operation of trafficsignal systems. Traffic signals are a central component of transportationinfrastructure as they directly contribute to the safety and efficiency of the surfacetransportation system.Title:1. Title: The title must be centered with at least a one and one-half inch margin onthe left and right.2. Font: Times New Roman typeface is required, bold faced, 14 point.3. Author and Affiliation: Submissions are done in a double blind. No author oraffiliation information is to be included on any abstracts.4. Footers: Do not include any in your abstract.Body of the Abstract (beginning under title information)1. Format: The document will be in a one-column format with left justification.There must be a 1 inch margin on the left, right, and bottom.2. Font: Times New Roman typeface is required, 12 point, skipping one linebetween paragraphs.3. Length: Abstracts should generally be between 250 - 500 words.Biographical InformationBiographical information is to be saved in Monolith on the Author/Co-Authorpage. It will be automatically added to your paper at the end of the process.OtherDo not include session numbers in any part of the document, unless specificallyrequested to do so by a call for papers.Do not include any author or affiliation information in any part of your abstract sothat your abstract is able to receive a blind review.Additional Guidelines and Suggestions:• As appropriate, include the pedagogical theory or approach being used;• Indicate the form that your outcome(s) will take as appropriate;• As applicable, methods of assessment should be made clear;• A second page may be used to include a graph or image to clarify the nature ofyour work or to include limited references toIndicate a basis for the work undertaken.Peer review occurs for both abstracts and papers. Abstract acceptance does notguarantee acceptance of the paper. All division have a Publish-to-Presentrequirement and final papers must be written and accepted in order for the work tobe presented at the 2013 ASEE Annual Conference in Atlanta, GA. Submission ofabstracts and final papers will be via the Monolith system and in accordance withASEE published deadlines.

Citation
Format

Hurwitz, D. S., & Brown, S. A., & Islam, M. R., & Daratha, K. (2013, June), Mental Models of Students and Practitioners in the Development of an Authentic Assessment Instrument for Traffic Signal Engineering Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22281

TY - CPAPER
AB - Mental Models of Students and Practitioners in the Development of an Authentic Assessment Instrument for Traffic Signal Engineering By David S. Hurwitz, Shane Brown, Kelvin Daratha, &amp; Mohammad IslamConducting fundamental engineering education research on student andpractitioner ways of knowing is a critical and often overlooked first step incurriculum and assessment design. This research project determined the coreconcepts related to and synthesized student and practitioner conceptualunderstanding of isolated and coordinated signal systems. A modified version ofthe Delphi Method was used to develop consensus among 16 transportationengineering faculty and engineering professionals on the most consistent, relevant,and core concepts in traffic signals. The most important concepts are warrantanalysis (or determining the need or justification for a new signalized intersection)and signal timing, calculations, and phasing. Clinical interviews were conductedwith approximately 50 students and 35 early career engineering professionals toinvestigate, characterize and synthesize their understandings of traffic signaloperations. Comparison of understandings were conducted to determinedifferences in how engineering students and early career engineering professionalsthink about signal design and to determine persistent misconceptions within thisdiscipline. Additionally, interviews were analyzed to determine commonmisconceptions. This research will produce a taxonomy of differences in theknowledge of students and early career engineering professionals related to trafficsignals and a summary of misconceptions. These project outcomes will be the basisof a newly-developed concept inventory and curriculum, such as inquiry basedconceptual exercises and assessments, both of which will be situated inengineering thinking and design. This study is significant because it fundamentallyadvances the field by identifying differences in conceptual understanding betweenpracticing engineers and students with respect to the design and operation of trafficsignal systems. Traffic signals are a central component of transportationinfrastructure as they directly contribute to the safety and efficiency of the surfacetransportation system.Title:1. Title: The title must be centered with at least a one and one-half inch margin onthe left and right.2. Font: Times New Roman typeface is required, bold faced, 14 point.3. Author and Affiliation: Submissions are done in a double blind. No author oraffiliation information is to be included on any abstracts.4. Footers: Do not include any in your abstract.Body of the Abstract (beginning under title information)1. Format: The document will be in a one-column format with left justification.There must be a 1 inch margin on the left, right, and bottom.2. Font: Times New Roman typeface is required, 12 point, skipping one linebetween paragraphs.3. Length: Abstracts should generally be between 250 - 500 words.Biographical InformationBiographical information is to be saved in Monolith on the Author/Co-Authorpage. It will be automatically added to your paper at the end of the process.OtherDo not include session numbers in any part of the document, unless specificallyrequested to do so by a call for papers.Do not include any author or affiliation information in any part of your abstract sothat your abstract is able to receive a blind review.Additional Guidelines and Suggestions:• As appropriate, include the pedagogical theory or approach being used;• Indicate the form that your outcome(s) will take as appropriate;• As applicable, methods of assessment should be made clear;• A second page may be used to include a graph or image to clarify the nature ofyour work or to include limited references toIndicate a basis for the work undertaken.Peer review occurs for both abstracts and papers. Abstract acceptance does notguarantee acceptance of the paper. All division have a Publish-to-Presentrequirement and final papers must be written and accepted in order for the work tobe presented at the 2013 ASEE Annual Conference in Atlanta, GA. Submission ofabstracts and final papers will be via the Monolith system and in accordance withASEE published deadlines.
AU - David S. Hurwitz
AU - Shane A. Brown P.E.
AU - Mohammad Rabiul Islam
AU - Kelvin Daratha
CY - Atlanta, Georgia
DA - 2013/06/23
PB - ASEE Conferences
TI - Mental Models of Students and Practitioners in the Development of an Authentic Assessment Instrument for Traffic Signal Engineering
UR - https://peer.asee.org/22281
DO - 10.18260/1-2--22281
ER -