Introduction
Before proceeding with the statistical analysis, it can be assumed that students with lower test scores will be more likely to cheat. One reason for this behavior might be a desire to raise one’s score on the test in any way possible, even if it is an academic offense. At the same time, it can be assumed that the lowest-achieving students tend to have the worst understanding of the topic, so they do not have enough knowledge to take the test (Noorbehbahani et al., 2022). Using opportunities to cheat, they may thus be seen as a tool to get the work done.
Analysis
The students were divided into three cohorts based on their prior performance for the analysis. Each student was asked about their cheating opportunities on a hundred-point scale, in which 100 indicated the maximum degree of agreement that they would cheat. Importantly, students were told that the consequences for such behavior would be critically limited, increasing their responses’ freedom and honesty.
As shown in Table 1, each cohort had similar numbers (N = 20) of respondents, with the average propensity to cheat being highest among the high-performing cohort (M = 74.20, SD = 13.88), then falling in order from low-performing (M = 53.25, SD = 12.86) to medium performing (M = 30.80, SD = 8.46). A one-way ANOVA was conducted to determine statistically significant differences in the data (Table 2) (SL, 2021).
The results showed statistically significant differences between cohorts, F(2, 57) = 65.795, p <.001. In other words, there were differences between the mean cheating aspirations of the different student cohorts. The Tukey post hoc test also demonstrated that differences were observed between all groups.
Conclusion
From the analysis, it can be concluded that the average propensity to cheat was highest for students with the highest academic achievement and lowest for students with average academic achievement. The lowest-achieving students were roughly between the two cohorts on this measure. To put it another way, this rejects the initial hypothesis and may indicate that it is essential for high-achieving students to maintain their level, so they could resort to cheating with comparable ease. Now that achievement differences have become apparent, regression tests need to be run to determine the predictors of this propensity in students.
References
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022). A systematic review of research on cheating in online exams from 2010 to 2021. Education and Information Technologies, 27(6), 8413-8460. Web.
SL. (2021). One-way ANOVA. Statistics Laerd. Web.