Combating Plagiarism: Function-based – and Other – Approaches

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Harla Frank, M.S., BCBA

bSci21 Contributing Writer

Borrowed thoughts, like borrowed money, only show the poverty of the borrower.

(Marguerite Gardiner, 19th Century, Irish novelist)

Research has identified many reasons college students borrow the intellectual property of others.  The primary reasons given by researchers are that students lack an education in the fine points of paraphrasing and providing attribution to the owners of the intellectual property, or students believe that if information is readily accessible in the public domain, i.e., Internet, it is “up for grabs” (Harris, 2015).  Researchers recommend confronting these causes through various educational programs.  Even those researchers who have found that some plagiarism is a result of lack of understanding and training point out that there are students who intentionally steal the intellectual property of others – or purchase it, and pass it off as their own (Harris, 2015; Owens & White, 2013).

Within these two broad categories, unintentional and intentional plagiarism, there exist many variables.  For example, researchers have found that those who unintentionally plagiarize have not benefited from proper training in what constitutes plagiarism or how to provide attribution to source material when used in the students’ work (Bradley, 2015; Harris, 2015; Owens & White, 2013; Belter & du Pré, 2009).  Interestingly, researchers have documented the reasons students give for intentionally plagiarizing, which include the desire to “save time;” earn a better grade; demonstrate “cleverness” at cutting corners; and show “a lack of respect” for the instructor or “authority” (Teh Eng Choo & Paull, 2013, p 286).  In addition, students report a belief that there will be no punishing consequence (Teh Eng Choo & Paull, 2013).

In this author’s previous article, “Plagiarism: A Behavioral Perspective,” variables connected to plagiarism were discussed; these include motivating operations (time and energy constraints); negative reinforcement (escaping the aversive assignment); and positive reinforcement (increased leisure and social opportunities) (Frank, 2017).  It was pointed out that response effort (easier to purchase a paper than research and write one) and delayed consequences (belief that one will not be caught) also play roles in the decision to plagiarize (Frank, 2017).

This “perfect storm of motivating operations; negative and positive reinforcement; response effort; and delayed consequences come together to maintain academic dishonesty” (Frank, 2017, para. 9).  Researchers have proposed several different approaches to quelling this storm.  These approaches include prevention, i.e., education and assignment adjustments; detection and policing; and punishment.

Educational approaches take many forms.  Belter and du Pré (2009) conducted a study in which an “academic integrity module” was added to an abnormal psychology college course (p. 258).  Students were required to “complete the module with 100% accuracy” before the “first test of the semester” (Belter & du Pré, 2009, p. 258).  Students could take the “module as many times as necessary” up to the first test (Belter & du Pré, 2009, p. 258).  The module included information regarding what constituted plagiarism and cheating and provided “strategies” to avoid both (Belter & du Pré, 2009).  Penalties for plagiarism and cheating were presented and a quiz was given to assess student learning (Belter & du Pré, 2009).  Embedded in the module were instructions with examples of correct and incorrect approaches to “paraphrasing, citing, and quoting” (Belter & du Pré, 2009, p. 259).  The control group for the study had access to the academic integrity policies of the university via the student handbook (Belter & du Pré, 2009).  The percentage of plagiarism in the control group’s paper assignment was 25.8% (Belter & du Pré, 2009).  The intervention was conducted in three experimental groups in three semesters (Belter & du Pré, 2009).  Each of the three experimental groups had an average incidence of plagiarism of 6.5% (Belter & du Pré, 2009).  Belter and du Pré hypothesize that their experiment shows that lack of knowledge regarding plagiarism is a major contributing factor to incidence rates (Belter & du Pré, 2009).  It is certainly possible; however, there may be an extraneous variable contributing to the results of this intervention, i.e., students’ awareness of instructor focus on plagiarism may have influenced behavior.  Students may have produced original work to avoid likely punishment (negative reinforcement).

Educational approaches to teach students skills in paraphrasing, citing, and quoting take similar paths.  Owens and White (2013) conducted a 5-year plagiarism reduction study with first year psychology students.  It was their belief that a “one-size-fits-all approach” would be less effective than a “multilayered” longitudinal study (Owens & White, 2013, p. 16).  Beginning in the students’ first year of study, the researchers required students to submit their assignments online (Owens & White, 2013).  Students were told that plagiarism detection software would be used (Owens & White, 2013).  Owens and White (2013) considered this their baseline, or control group.  In the second phase of the study, students were required to “read a paragraph from a published article” and write an in-class paragraph in which they responded to a question about the reading (Owens & White, 2013, p. 17).  Students were told to submit their paragraph online (Owens & White, 2013).   Plagiarism detection software would be utilized and online feedback provided (Owens & White, 2013).  Those students who copied several sentences from the original paragraph were sent an E-mail stating that plagiarism was detected but because this was an “exercise designed to prevent plagiarism in the future,” there would be no consequence this time (Owens & White, 2013, p. 17).  The researchers report a dramatic decrease in plagiarism that continued throughout the remaining years of the study (Owens & White, 2013).  They attribute the reduction to a combination of raising students’ awareness of the ease of detection of plagiarism (and the resultant consequences) and education regarding proper attribution of source materials (Owens & White, 2013).

Most researchers agree that education regarding what constitutes plagiarism, coupled with training in the proper use of quotations, paraphrasing, and attribution, should be a staple in the curriculum of freshmen students.  The manner in which this training is presented varies little across researchers.  However, Elizabeth Bradley (2015) in her article, “Using Computer Simulations and Games to Prevent Student Plagiarism,” presents some unique approaches that many universities are using to engage and teach students about plagiarism and how they can identify and avoid it.  She reviews 10 computer games of varying complexity and style and discusses the advantages of using this interactive approach with students (Bradley, 2015).  This use of technology seems quite promising, but data was not presented regarding the effectiveness of such approaches in reducing plagiarism.

Teh Eng Choo and Paull (2013) present a convincing argument for the shared responsibility of accountability among instructors, administrators, and students with regard to the incidence of plagiarism.  The researchers cite varying perceptions among instructors and administrators regarding plagiarism and point to the response effort involved in policing and reporting suspected cases (Teh Eng Choo & Paull, 2013).  This effort is often a deterrent to the oversight needed to consistently address cases of plagiarism (Teh Eng Choo & Paull, 2013).  The inconsistent oversight feeds students’ beliefs that they will not suffer any consequences for submitting work that is not their own.  The authors recommend that instructors, administrators, and students be provided training regarding what constitutes plagiarism (Teh Eng Choo & Paull, 2013).  They further recommend that universities make use of plagiarism detection software; design specific policies regarding plagiarism and the consequences of plagiarism; and that instructors and administrators consistently enforce those policies (Teh Eng Choo & Paull, 2013).

Educating students, as well as instructors and administrators, regarding plagiarism is not the only antecedent modification approach that can be used to prevent plagiarism.  A growing number of researchers discuss the need for instructors to take more responsibility for the high incidence of plagiarism by creating “low-risk” assessments and novel assignments (Walker & White, 2014, p. 681).  Walker and White (2014), as well as other researchers, propose creating novel assignments and scaffolding the assignments’ components by having students submit work representing their stepwise process, for example, first, submit the paper topic; second, submit an annotated bibliography; third, submit a draft of the paper; fourth, submit the final paper.  Creative projects that encourage students to demonstrate understanding of the course topics can reduce plagiarism due to the personal aspects of the assignments, i.e., “reflection journals, peer-review tasks, and video or poster projects” (Walker & White, 2014, p. 682).

Gómez-Espinosa, Francisco, and Moreno-Ger (2016) conducted a study in which they analyzed activities in an “online university” course in order to identify what types of activities engender the most plagiarism (p. 39).  From their analysis, they determined that assignments that “encourage involvement, originality, and creativity” have lower incidences of plagiarism (Gómez-Espinosa et al., 2016, p. 43).  With this in mind, the researchers selected a student group and assessed the scored activities in the course to determine which activity had the highest levels of plagiarism (Gómez-Espinosa et al., 2016).  The activity that demonstrated the highest plagiarism rate had the most specific topic and was easily researched online (Gómez-Espinosa et al., 2016).  The original assignment is as follows:

Reading: First class numbers: In the recommended reading for this chapter, the

Devil of Numbers introduces Robert to some special numbers: those he was calling, “first

class numbers.”  In the real world, these numbers are called, “prime numbers,” and as our protagonist says, “Mathematicians have spent over a thousand years puzzling over them.”  They are wonderful numbers.  For example, eleven, thirteen, or seventeen . . . . Research

the meaning of prime numbers and write a short essay presenting the key ideas about

these numbers (definition, historical development, properties, curiosities . . .).  (Gómez-Espinosa et al., 2016, pp. 43-44).

The researchers hypothesized that by modifying the assignment instructions to encourage more involvement and creativity, the plagiarism rate would be reduced (Gómez-Espinosa et al., 2016).  The modified assignment is as follows:

Reading: Explaining what first-class numbers are: In the recommended reading

for this chapter, the Devil of Numbers introduces Robert to some special numbers: those

he used to call, “first class numbers.”  In the real world, these numbers are called, “prime

numbers,” and, as our protagonist says, “Mathematicians have spent a thousand years

puzzling over them.”  They are wonderful numbers.  For example, eleven, thirteen, or seventeen . . . .”  Research prime numbers, then we propose the following activity: Imagine you in front of a class of children between 9 and 10 years, to whom you have to explain briefly what the prime numbers are.  Write half a side of paper (no more than 30 lines), on how would you explain it.  If you wish, you may also add a picture or a diagram in the lower half of the sheet.  Try to make it fun, original, educational, etc., remember that you are explaining it to children!

Activity objectives: Be aware of the relevance for Mathematics of the primes; assume the role of teacher preparing (schematically) a class for elementary students; design a motivating activity relevant to your future career as a teacher.

Criteria for assessing the activity: The concepts presented and explained about prime numbers and their properties must be correct; the level of originality and creativity in the development of the class will be valued; suitable writing and spelling.  (Gómez-Espinosa et al., 2016, p. 44).

The control group’s average rate of plagiarism for this assignment was 47.66%, while the average plagiarism rate for the experimental group was 3.87% (Gómez-Espinosa et al., 2016).  The results of this study have strong implications for taking a second look at how we present assignment instructions.  By simply modifying the original instructions to encourage students to bring in their own personalities and creativity, plagiarism was reduced dramatically.

Training students to properly cite and acknowledge sources of information, as well as to paraphrase, and informing students of the use of plagiarism detection software are proactive approaches to reducing plagiarism.  Training instructors in strategies to detect plagiarism and requiring them to report suspected cases can contribute to a comprehensive approach to reduce plagiarism.  But, even the “ounce of prevention” will need a “pound of cure.”

Plagiarism detection software is being used by most universities.  Many programs allow instructors to set up the software so students can submit assignments directly to the program.  Instructors can also copy and paste student assignments into the program for similarity detection.  These programs work well when there is material already in the system with which to compare, but “cheat sites” are continually updating their methods in order that their products escape detection.  Increasingly, students are purchasing “novel” papers from these “homework for hire” Internet companies that hire “tutors” to create original works.  Plagiarism detection software will not be of help in these situations.  Instructors will have to go several steps further in screening student work.

Anil Singh (2013) presents a simple method of identifying plagiarized work in “computer-based assignments” (p. 177).  By utilizing data macros, i.e., Microsoft Access 2010, he is able to identify a student who removes another student’s name from the assignment and inserts his/her own (Singh, 2013).  Singh (2013) outlines a step-by-step method of setting up the macros so that when a student changes the name in the “Employees table,” a “new row in the product table will be created” without the user’s “knowledge” (p. 178).  The new row in the product table will contain the name of the student who has replaced the previous student’s name with his/her own (Singh, 2013).  The new row will remain hidden until the instructor enters the program and makes it visible (Singh, 2013).

There are many technologies being used in the online classroom to detect plagiarism.  Besides plagiarism detection software, there are browser lockdowns that prevent students from opening other search engines or screens during testing (Hill, 2010).  Remote proctoring devices are used by some distance learning courses that require students to purchase “monitoring devices that connect to their computers and ‘watch’ them take the exams” (Hill, 2010, p. 11).  “Fingerprint scanning is required periodically” and the system will turn on a “microphone and 360 degree camera if noise or movement thresholds are reached” (Hill, 2010, p. 11).  Western Governors University (WGU) utilizes an online proctoring system that includes “keystroke analytics” (Lorenzetti, 2010, p. 14).  “Keystroke rhythms of a given user” are measured and “a profile” is created (Lorenzetti, 2010, p. 14).  WGU’s system is proctored by an “individual working for Kryterion” and the testing is also recorded (Lorenzetti, 2010, p. 14).  Technology certainly aids in the detection, and perhaps the deterrence, of plagiarism, but those wishing to profit from the sale of intellectual property will continually strive to beat the existing systems.  Detection is ultimately in the hands of those who judge the work.

McNabb and Anderson (2010) offer some tips for identifying plagiarism.  Several good ideas include comparing student writing in various assignments and comparing portions of a paper with another, e.g., introduction and conclusion (McNabb & Anderson, 2010, p. 12).  Robert Harris (2015) suggests some things to look for, such as several different citation styles; formatting issues; general, rather than focused, discourse on assignment topic(s); old information; and varying writing styles within the paper (formal and informal).

Instructors must become familiar with their students’ writing styles.  It only takes a few assignments to learn the idiosyncrasies in their writing; their personalities are reflected in their words.  Beyond all that we can do to prevent, detect, and punish academic dishonesty, we must promote the desire in our students to create their own original works – a desire to learn something valuable – a desire to seek growth beyond the degree.  We can do this through reinforcement of what the student does well.  Once an instructor told a story of a student she had who had very poor writing skills.  The final paper was almost indecipherable, but she always searched for something good upon which to comment.  In this case, she wrote on the student’s paper that she could tell that he obviously read the material.  She thought it was a very meager comment, especially when compared with the notes that indicated areas that needed work, until he showed up at her office door, beaming, and repeated word-for-word the compliment she had paid him in the paper.  It was such a small thing, but it gave him pride of ownership and confidence that he could meet this instructor’s expectations.

References

Belter, R. W. & du Pre, A.  (2009). A strategy to reduce plagiarism in an undergraduate course.

Teaching of Psychology, 36, 257-261.

Bradley, E. G.  (2015). Using computer simulations and games to prevent student plagiarism.

Journal of Educational Technology Systems, 44(2), 240-252.

Frank, H.  (2017).  Plagiarism: A behavioral perspective.  Behavioral Science in the 21st Century.  Retrieved from http://www.bsci21.org/plagiarism-a-behavioral-perspective/#comment-5318

Gómez-Espinosa, M., Francisco, V., & Moreno-Ger, P.  (2016). The impact of activity design in

internet plagiarism in higher education.  Comunicar, 24(48), 39-47.

Harris, R. (2015).  Anti-plagiarism strategies for research papers.  Retrieved from

http://www.virtualsalt.com/antiplag.htm

Hill, C. (2010).  Student authentication: What are your duties under the HEA reauthorization? In Hill (Ed.), Promoting academic integrity in online education (pp. 10-11). Madison,

WI: Magna Publications, Inc.

Lorenzetti, J. P.  (2010). Remote proctoring: Key to secure exam administration? In C.  Hill

(Ed.), Promoting academic integrity in online education (pp. 14-15).  Madison,

WI: Magna Publications, Inc.

McNabb, L., & Anderson, M. (2010).  91 Ways to maintain academic integrity in online courses.

In C.  Hill (Ed.), Promoting academic integrity in online education (pp. 12-14).

Madison, WI: Magna Publications, Inc.

Owens, C., & White, F. A.  (2013). A 5-year systematic strategy to reduce plagiarism among

first-year psychology university students.  Australian Journal of Psychology, 65, 14-21.

Singh, A.  (2013). Detecting plagiarism in MS Access assignments. Journal of

Information Systems Education, 24(3), 177-180.

Teh Eng Choo, E., & Paull, M.  (2013). Reducing the prevalence of plagiarism: A model for staff, students and universities.  Issues in Educational Research, 23(2), 283-298.

Walker, C. & White, M.  (2014). Police, design, plan and manage: Developing a framework for

integrating staff roles and institutional policies into a plagiarism prevention strategy.

Journal of Higher Education Policy and Management, 36(6), 674-687.

 

Harla Frank, M.S., BCBA earned her Master’s degree in Psychology, with an emphasis in Applied Behavior Analysis, from Florida State University.  Since receiving her certification as a Board Certified Behavior Analyst (BCBA) in 2007, she has worked primarily with children and young adults on the Autism Spectrum, but has also worked with adults with a variety of diagnoses and needs. She has served as an expert witness for Applied Behavior Analysis (ABA) in the Colorado court system and has had the privilege of providing “ABA approaches” training to foster care staff and families.

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