Academic Dishonesty: A Probabilistic Model Using Markov Chains
- Conference
- Location
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Chicago, Illinois
- Publication Date
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June 18, 2006
- Start Date
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June 18, 2006
- End Date
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June 21, 2006
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Engineering Ethics
- Page Count
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14
- Page Numbers
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11.153.1 - 11.153.14
- DOI
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10.18260/1-2--383
- Permanent URL
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https://peer.asee.org/383
- Download Count
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526
Paper Authors
Adly Fam University at Buffalo, SUNY
Indranil Sarkar University at Buffalo, SUNY
Indranil Sarkar was born in Calcutta, India on May 18, 1979. He received the BE degree in electronics and communication engineering from Visveswaraiah Technological University, India and the MSEE degree in electrical engineering from the State University of New York at Buffalo in 2002 and 2004, respecetively. He is currently a doctoral candidate in electrical engineering at the State University of New York at Buffalo.
Khaled Almuhareb University at Buffalo, SUNY
Khaled Almuhareb is a Doctoral Student at the department of Learning and Instructions, University at Buffalo. He has taught different ESP courses to undergraduate engineering students at Kuwait University for seven years. He has also chaired the English Language Unit of the College of Engineering, Kuwait University for three years. His current research focuses on theories of learning and behavior as they pertain to various educational settings.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
Academic Dishonesty: A Probabilistic Model Using Markov Chains
Abstract
Academic dishonesty is modeled via Markov chains. The case of student behavior in class assignments, quizzes and exams is analyzed in modeling examples with various levels of surveillance. The choice of modeling based on surveillance and sanctions is motivated by the research literature on the deterrence theory analysis of cheating. In addition, surveillance and sanctions could be controlled to achieve the desired degree of intervention with the least intrusion. This could also be used to formulate optimal university policies regarding academic dishonesty.
Section I: Introduction
The body of research attempting to estimate the extent of academic dishonesty among college students has produced widely varying results. Karlins1 et. al. found that only 3% of college students engage in the act of academic dishonesty whereas Gardner2 et. al. reported a whopping 98%. According to McCabe and Trevino3, this apparent disagreement in the literature on the prevalence of these incidents can be mainly attributed to the differences in the definitions of academic dishonesty, data collection methods and interpretations adopted by different authors investigating the phenomenon. Robinson4 et. al. defined cheating as: “[the] intentional use or attempted use of unauthorized materials, information or study aids in any work submitted for academic credit.” In light of this definition, it can be argued that there is a striking evidence of a large percentage of college students actually engaging in cheating. Regardless of the type or seriousness of the cheating behavior, there is a consensus that cheating appears to be inherent to the college experience5.
The motivation for writing this paper arose while one of the authors was teaching a junior level class on probability at The State University of New York at Buffalo. There seemed to be a growing evidence of duplication and cheating in both the homeworks and quizzes conducted as a part of the course. There was a strong need to bring this subject up in some form to alert the students to the negative consequences of such behavior on both the professional and personal levels as well as to remind them of the university policies in this regard.
After considerable deliberation, it was decided to use the subject of the course itself to analyze the consequences of cheating and in the process, convey the moral and ethical messages to the students.
As it turned out, the resulting analysis proved to be very enlightening and could be of value in evaluating school policies that deal with cheating and ethics. This analysis could also be used to help formulate such policies. By presenting this material as a part of the course in probability, it was very well received by the students and had a very good impact.
Fam, A., & Sarkar, I., & Almuhareb, K. (2006, June), Academic Dishonesty: A Probabilistic Model Using Markov Chains Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--383
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