Cheating in Online Learning: A Mixed Method Study with Undergraduate Students
Concurrent Session 1
Cheating has been an area of concern in educational institutions for decades, especially at the undergraduate level. A particular area of concern is the increasing reports of the rise of cheating behaviors and the perceived cheating potential in online learning. As online learning continues to grow and become an integral part of education, concerns exist regarding academic integrity in online learning. The purpose of this study was to explore cheating behaviors, practices and online learners' perceptions and motivation towards cheating online.
Academic dishonesty is not a new phenomenon in education. Researchers have studied cheating from different perspectives and viewpoints. Psychologists, for example, have focused on personality types to tackle possible links between ethical behavior and personality (Barger et al., 1998; Tieger & Baron, 1993; Williams et al., 2010). Students’ characteristics such as age, gender and GPA have been investigated for possible connections to scholastic cheating (Barger et al., 1998; Coombe & Newman, 1997; Ford & Richardson, 1994). Scholars have also studied differences in cheating behaviors across academic majors and found that academic major indeed plays a significant role on cheating (Hanson & McCullagh, 1995; Sankaran & Bui, 2003).
Scholastic cheating has been a subject of research for many decades and scholars consistently concluded that academic dishonesty has been increasing and continues to compromise the integrity of the educational process. In many studies, as many as 80-90% of students admitted to one or more instances of cheating during their college years (Davis et al., 1992; Jendrek, 1989). Cheating seems to be growing at a faster rate than ever according to recent data. For example, Yardley et al. (2009) conducted a study on self-reported cheating at the college level using a large sample and found that over 80% of participants admitted to cheating. The study concluded that students who reported cheating in classes for their majors represented more than half and were one-time offenders. In contrast, nearly all respondents who reported cheating in classes outside of their majors reported cheating more than once. Diekhoff et al. (1996) uncovered a 10% growth in cheating after pursuing a follow up study 10 years later at the same institution. His findings are consistent with current statements on the widespread growth in cheating in higher education institutions.
The purpose of this study was to explore cheating behaviors in online learning environments, and to determine students’ perceptions and motivation towards cheating. More specifically, how and why the online environment might make cheating easier for students engaged in online learning.
The focus of this study led to the following research questions.
- What motivates students to cheat in online courses?
- What factors do students feel minimize cheating in online courses?
- What is the relationship between a student’s perception of transactional distance and their decision to engage in cheating?
- What is the relationship between students’ perception and behaviors toward cheating in online courses?
- In what ways do the participants’ perceptions and beliefs of cheating explain what they reported in the survey results?
There is evidence that cheating is on the rise. Although research on scholastic cheating have focused on measuring incidence in traditional classrooms, most recent research has shifted focus to understanding why students engage in unethical practices and how. The new focus on understanding the underlying causes of cheating has provided researchers with new directions to better understand the cheating phenomena, which continue to be one of the top challenges faced by educational institutions.
Although the concept of transactional distance is well established in the field, relatively little empirical research has tested the validity of its constructs. Educators have called for improvements in the areas of course design, teaching strategies and assessment practices to minimize learners’ hardships such as misunderstandings and unclear expectations that are common to online learning due to transactional distance (Moore, 1993). This study seeks to explore how participants’ perceptions towards learning community and connectedness experienced in online courses affected integrity behaviors while learning online.
The limited literature on the effectiveness of honor codes suggests that institutions with established honor codes have usually reported less cheating and less major cheating issues than institutions that operate without honor codes (McCabe, Trevino, & Butterfield, 2002; McCabe & Trevino, 1993). This study aims to find out what is participants overall perception towards the effectiveness of honor codes on cheating.
The perceived cheating potential in online learning is one of the major barriers to acceptance by both faculty and administrators according to the literature. Technology seems to be playing a key role on new cheating trends as online students can use their personal devices to cheat. Technology assisted cheating has been reported by recent research, and many scholars believe the cheating potential to be greater in online learning environments due to technological advances. This study investigated the role of technology on participants’ cheating practices.
Population and Sampling Procedures
This study used a non-probability sample. It was assumed that subjects who choose to participate in the survey were representative of the target population, which in this case were undergraduate students enrolled in online courses (N= 1206). To determine the appropriate sample size needed for accurate results, sample size formula from Bartlett et al. (2001) was used. With a significant level of .05 and an estimated proportion of participants that cheat being .80, a sample size of 245 was calculated. Using Cochran’s (1977) correction formula for survey research, a sample size of 226 was found to be a minimal return sample size.
All participants were enrolled in several online courses offered during in a business college. Participants were enrolled in online courses in the areas of finance, accounting, economics, management and business law.
Data collected included both quantitative and qualitative using an online survey instrument. The bulk of data collection was quantitative in nature, with qualitative data collected through the inclusion of several open-ended questions in the survey instrument. The survey was constructed of various instruments as discussed in the Measures section. The survey was piloted with two classrooms to confirm interpretation of questions and validity of the survey. Quantitative and qualitative data were collected and analyzed. Analyses included quantitative, qualitative, and a complementary (mixed data) design.
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