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Using a Course Learning Management System to Promote Academic Honesty

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Technology for Faculty Development and Classroom Management

Tagged Division

New Engineering Educators

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Paper Authors


Gillian M. Nicholls Southeast Missouri State University

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Dr. Gillian M. Nicholls is an Assistant Professor of Quantitative Methods at Southeast Missouri State University. Her research interests are in applying statistical analysis and optimization to supply chain management, transportation management, and engineering education. She holds the B.S. in Industrial Engineering (Lehigh University), Masters in Business Administration (Penn State University), M.S. in Industrial Engineering (University of Pittsburgh.), and Ph.D. in Industrial Engineering (University of Pittsburgh). Prior to entering academia, Dr. Nicholls was a practicing industrial engineer in the freight transportation industry. Address: Donald L. Harrison College of Business, Southeast Missouri State University, One University Plaza – MS 5815, Cape Girardeau, MO 63701; telephone (+1) 573.651.2016; fax: (+1) 573.651.2992; e-mail:

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Neal Lewis University of New Haven

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Neal Lewis received his Ph.D. in engineering management in 2004 and B.S. in chemical engineering in 1974 from the University of Missouri – Rolla (now the Missouri University of Science and Technology), and his MBA in 2000 from the University of New Haven. He has over 25 years of industrial experience, having worked at Procter & Gamble and Bayer. He has taught at UMR, UNH, Marshall University, and the University of Bridgeport. Neal is a member of ASEE, ASEM, and IISE.

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Academic dishonesty cases have appeared in the news with greater frequency in recent years. Students employ methods that range in complexity from simply glancing at another’s exam, smuggling in a note sheet, or using a watch with calculator functions to more sophisticated methods such as scanner pens, smartwatches, camera-equipped eyeglasses, or impostors with fake ID. Cheating is now commercialized with websites offering completion of assignments or an entire online course. Instructors and educational institutions are caught in a veritable arms race to prevent, detect, and punish academic misconduct. New engineering educators are at a particular disadvantage since they are typically pressed for time, less experienced in dealing with cheating, and uncertain about formal “prosecution” of academic misconduct cases.

There are various ways to use a course learning management system (LMS) to educate students about what constitutes academic dishonesty, school and instructor policies regarding academic dishonesty, and the sanctions that will be levied for academic dishonesty. Students can be required to sign, scan, and upload a document specifying the policies and sanctions for that course. The LMS can be used to prove students have received training about academic honesty standards and the sanctions for misconduct. Educating students about the policies can assist instructors in deterring academic dishonesty, disproving later claims of policy ignorance, and prosecuting misconduct.

LMS systems also offer ways to limits students’ ability to cheat on assignments. Various settings in the systems combined with strategies in designing online assignments discourage students from using unauthorized aids and hamper their ability to share answers. Time limits for completing assignments, using randomized algorithmic problems, randomizing question selection, including conceptual short answer questions, and using an online proctoring service for exams are all methods of deterrence.

Academic misconduct can be detected through the capture of Internet Protocol (IP) addresses and time stamp activity tracking features of LMS systems. The LMS reporting features can be used to research a student’s access of an assignment, compare IP addresses with those of other students in the course, and check the IP address location against the likely location of the student. University IT staff may be able to access additional LMS data if misconduct on a wider scale is suspected. These LMS features can rapidly be deployed to investigate suspected cases and provide solid evidence to punish academic dishonesty.

This paper presents best practices for time-constrained educators to use an LMS for supporting academic honesty and protecting honest students. Examples and actual experiences from using an LMS in this way are presented.

Nicholls, G. M., & Lewis, N. (2017, June), Using a Course Learning Management System to Promote Academic Honesty Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--29068

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