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This is the second installment in a three-part series by Bishop and Cini. In the first installment, they discussed a few forms of academic dishonesty prevalent in the online space. In this piece, they share a few strategies designed to overcome these obstacles.
Park (2003) and others have recommended that higher education develop frameworks for dealing with academic dishonesty that are “based on prevention supported by robust detection and penalty systems that are transparent and applied consistently” (pp. 483-484). Strategies in the literature for addressing academic dishonesty in the digital age can be sorted broadly into three categories: educating students, redesigning courses and assessments, and detecting and punishing offenders (Carroll, 2013).
Blum (2009) argued that academic dishonesty may be less about the emerging technologies and more about the rise of two opposing views on this issue: university professors and administrators who believe academic dishonesty is an ethical transgression, and their students who are used to having open access, mixing and mashing media, sharing files, and collaborating. The concepts of “cheating” and “intellectual property” are in flux both inside and outside of the classroom, often leading to a disconnect if expectations about what is and is not permissible are not explicitly discussed. Improving communication between these two distinct cultures is an issue higher education must address whether instruction is delivered online or face-to-face.
Therefore, recommended strategies for combating academic dishonesty often begin with educating students about what academic dishonesty is and specifically how to avoid it (Fischer & Zigmond, 2011). According to McCabe, Butterfield, & Treviño (2012) student attitudes toward cheating are often shaped prior to college, suggesting that discussions about academic integrity should be part of advisement and institutions’ “onboarding” or “transition” programs. For example, many students, particularly international students, know little about plagiarism and either are unaware they have been dishonest in how they are representing another’s work (Ma, McCabe, & Liu, 2013; Xueqin, 2002) or genuinely believe that material on the internet is “free for the taking” (Scanlon & Neumann, 2002).
It appears that still others who are tempted to commit acts of academic dishonesty can benefit from being made aware and regularly reminded that honesty matters. Ariely’s (2012) social science research of over 40,000 individuals has suggested that, while few cheat a lot, more than half of us cheat a little bit –giving in to our “personal fudge factor” when conditions are right. Ariely also found that moral reminders, like student honor codes, significantly shrink the amount of cheating the majority of us are likely to do (see also McCabe & Treviño, 1993, 1997). Even “modified honor codes” that are easier to implement at large institutions by placing more of the burden on students to develop programs and enforcement strategies have been shown to significantly decrease instances of academic dishonesty (McCabe, Treviño, & Butterfield, 2002). University of Maryland’s “Code of Academic Integrity,” in particular, has been pointed to as a viable alternative for schools that feel a traditional academic honor code would not work on their campus. However, while these reminders of the social expectations can work, they need to be woven into the institution’s culture and not just signed at the start of the year and forgotten.
Redesigning Courses and Assessments
Vilic and Cini (2006) argued that well designed instruction and assessments are “the strongest means of deterring and reducing the number of academic integrity violations” (p. 341). As discussed earlier, findings from research on students’ reported rates and levels of academic dishonesty have indicated that they are more tempted to cheat when assessments incorporate more objective rather than subjective measures (Watson & Sottile, 2010). Instead of high-stakes exams, course designs incorporating more frequent, varied and authentic assessments that require students to write about course-specific topics, reflect on experiential learning, or collaborate on team-based projects can be strong academic dishonesty deterrents given the nature of the task being asked of the learner. As an added benefit, those same assessment strategies that make cheating less worthwhile are also the ones that have been found to improve student learning (Lang, 2013).
According to Sterngold (2004), clear criteria and expectations for assignments with multi-stage feedback can also reduce academic dishonesty. When a student is required to turn in successive drafts of a larger assignment, for example, it is very difficult to plagiarize all the way through. Carroll (2013) also noted that when the assignment is interesting and appealing to students they are more likely to engage in the task instead of cheating. Vilic and Cini (2006) suggested that projects and assessments that require students to connect the material to their lives or to specific things that occurred in the class are not only more engaging, but also make it that much harder to buy or “borrow” a paper from someone else (see also Semple, Hatala, Franks, & Rossi 2011). Further, assignments that require students to apply course content and new learnings directly to their own lives, community, job, or family make both plagiarism and identify falsification very difficult because faculty become knowledgeable about the student’s context, writing, and cognitive capabilities. Portfolio-based assignments can be a particularly effective way to more authentically assess and validate students’ work in these situations.
Detecting and Punishing Offenders
Increasingly sophisticated technologies are playing an increasing role in helping to detect and deter academic dishonesty (Vilic & Cini, 2006). Tools for plagiarism detection such as Turnitin and iThenticate are now used widely in both online and face-to-face courses to detect instances where students have copied another’s writing or other creative work without attribution. These tools provide detailed information about the percentage of the student’s submission that is plagiarized as well as links to the original sources on the web. However, while these programs make it possible for faculty to detect issues quickly and document them easily for grade rebuttals and student conduct hearings, they are just tools—useful only after the plagiarism has occurred (Vilic & Cini, 2006). In fact, some institutions have recently begun experimenting with incorporating plagiarism detection software into courses and encouraging students to use it to critique their own papers as self-assessment and self-learning aids (Chew, Ding, & Rowell, 2013; Rolfe, 2010).
The types of technologies developed for identity authentication include those that require specific and unique knowledge (such as challenge questions from public databases); involve biometrics (fingerprints, keyboard strokes, or mouse-based signature assessment); use live proctoring via webcam; or take video recordings of “suspicious” behavior during an in-person proctored exam. While these technologies show promise, they are far from a panacea at this stage in their development, often creating other issues that militate against adoption.
This is the second installment in a three-part series by Bishop and Cini exploring academic dishonesty in the online education space. In the final installment, the authors will share how the University of Maryland University College has moved to combat digital academic dishonesty.
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