There has been an increase in the number of cheating incidences in most educational institutions. In fact, a big number of business executives are engaging in unethical behaviors. This is attributed to the rising cases of cheating in most business schools. In order to stem this tide, Bayview University has undertaken a study to determine the number of students who are involved in cheating in their business school.
According to Whitley and Spiegel (2002), academic cheating is defined as the deliberate attempt by students to use someone else’s work as their own. This could be in form of copying from someone during exams, copying from the internet, or collaborating on individual assignments, even when the instructions state otherwise.
The university used a questionnaire method to collect information about the number of students involved in various kinds of cheating in school. The study was necessitated by the fact that some members of staff in the University felt that the number of cheating cases at the Bayview University had risen as compared to other universities. Others were of the opinion that the number of cheating was not very widespread in the university. This information was meant to be used by the Dean of College of Business at Bayview University in order to put in place the necessary strategies to reduce the number of cheating cases.
Chronicle of Higher Education had done another study which revealed that the proportion of business students who cheated was 56%. 47% of the non-business students was also found to have participated in cheating. This information would be crucial as it would help in drawing conclusions from the study concerning whether cheating at Bayview was more widespread than at any other university. This paper presents a managerial report on the study done by the university. The report covers two main areas including developing confidence intervals, testing for hypotheses, results, conclusions and recommendations.
Developing 95% confidence intervals
95% confidence interval for the total number of students who cheated.
To develop a 95% confidence interval, we proceed as follows:
N = 90 and n = 63. The proportion of students who cheated is denoted by (p). The proportion of those who did not cheat is denoted by (q) and is given by (1-p).
p =63/90= 0.7
q = 1 – 0.7 = 0.3
The standard deviation (Sp) is given by: Sp =√pq/n=√(0.7)(0.3)/90 = 0.048
Population proportion confidence interval is as follows:
= P ± 1.96 (Sp)
= 0.7 ± 1.96 (0.048)
= 0.7 ± 0.094
= 0.606 to 0.794 or 60.6% to 79.4%, which is the 95% confidence interval.
According to this outcome, it can be seen that the interval is relatively narrow. This implies a greater certainty in the data at 95% confidence interval. As a result of the data, there is a high level of cheating among the business students at the Bayview University.
A 95% Confidence Interval for the Total Number of Female Students Who Cheated.
N = 42; p=29/42=0.690
Q = 1 – 0.690 = 0.310
The confidence interval is calculated as shown below:
= P ± 1.96 (Sp)
=0.690 ± 1.96 (0.071)
=0.690 ± 0.139
=0.551 to 0.829 or 55.1% to 82.9% which is the confidence interval.
This confidence interval is relatively large, implying that there is a high likelihood of uncertainty in the data collected. This shows that the data do not conclusively provide the intended information about the number of cheating cases among the female business students. This is because the sample size is relatively small and additional information is required. In order to get a more reliable data, the management should consider having a bigger sample than the one available in order to enhance the certainty of the outcome.
A 95% Confidence Interval for the Total Number of Male Students Who Cheated.
N = 48; p=34/48= 0.708
Q = 1- 0.708 = 0.292
The confidence interval is computed as shown below:
= P ± 1.96 (Sp)
=0.708 ± 1.96(0.022)
=0.708 ± 0.043
=0.665 to 0.751 or 66.5% to 75.1% which is the confidence interval.
This is a relatively narrow range, which indicates that there is a high level of certainty in the data which was collected. This implies that the data are reliable in decision making. It points out that there is a high level of cheating among the male business students. However, the accuracy and reliability of the data can be enhanced by having a sample that is larger than this.
We are testing the hypothesis at 5% level of significance.
The null and alternative hypotheses are as stated below:
H0 = the number of business students at the Bayview University who cheated is less than that of business students in other institutions as reported by Chronicle of Higher Education.
H1 = the number of business students at the Bayview University who cheated is not less than that of business students who cheated in other institutions as reported by Chronicle of Higher Education.
To test the hypothesis, we proceed as follows:
Sp =√pq/n=√(0.7)(0.3)/90= 0.048
Z = 0.70-0.56/0.048=2.917.
At 5% level of significance, for a two-tailed test, the critical value is 1.96.
Since the calculated Z value is greater than the tabulated value (1.96) (i.e. 2.917 >1.96), we reject the null hypothesis and take the alternative hypothesis.
This implies that the number of cheating students at Bayview Business College is not less than the number of business students who cheated in other universities. This seems to support the assertion that cheating at Bayview is widespread than in other universities as alleged by some employees in the university.
We are testing the hypothesis at 5% level of significance.
The null and alternative hypotheses are as follows:
H0 = the number of business students who cheated at the Bayview University is less than that of the non-business students who cheated in other institutions as reported by Chronicle of Higher Education.
H1 = the number of cheating business students at the Bayview University is not less than non-business students at other institutions as reported by Chronicle of Higher Education.
To test the hypothesis, we proceed as shown below
Sp =√pq/n=√(0.7)(0.3)/90= 0.048
Z =0.70-0.47/0.048= 4.792.
At 5% level of significance for a two-tailed test, the critical value is 1.96.
Since calculated Z value is greater than tabulated value (1.96) (i.e. 4.792 > 1.96), the null hypothesis is rejected. We, therefore, take the alternative hypothesis.
This means that the number of students at Bayview University who cheat is more than the number of non- business students in other universities as reported by the Chronicle of Higher Education.
From the data collected in this study, it can be concluded that there is a high level of cheating for all business students at the Bayview University. The proportion of cheating students at the Bayview University was 70%. Moreover, the number of male students who cheated was slightly higher than that of female students. Thus, the males are more likely to cheat than the females.
While some people might be of the opinion that cheating has not increased over time, there is a general consensus that other types of academic dishonesty have been increasing among the students. This is evident since the study revealed that 17.7% of the students copied from the internet while 32.2% collaborated in individual assignments.
However, this study has some weaknesses which should be addressed. Firstly, the sample size which was used in this study was relatively small. This implies that the data collected have very low certainty. In order to enhance this certainty, the management should consider having a larger sample. Secondly, this sample consisted of only the graduating class. The sample should have been drawn across the entire student body in order to give a more realistic picture of the incidences of cheating in the school. This view can be supported by the assertion that the senior students are more likely to cheat in their examinations than the lower level students.
Conclusions and recommendations
The cases of academic dishonesty have gone up in learning institutions, especially in the current times when technology has greatly improved. The institutions need to be more vigorous in fighting this unethical behavior in schools. Brown (2005) claims that in today’s internet age, the level of academic dishonesty has gone up considerably. Cheating among university students is believed to be catalyzed by peer influence, declining sense of academic integrity and procrastination. Peer effects arise since students who engage in club activities in the school are likely to find other students who do not uphold academic integrity. This reinforces the belief in the mind of the students that there is nothing wrong with cheating. However, if a student has got academic ethics, he is likely to keep company with others who uphold the same values.
Another cause of academic cheating is the students GPAs. Students with higher GPAs uphold academic ethics and are less likely to engage in academic dishonesty. On the other hand, those with lower GPAs are more likely to engage in academic cheating. Moreover, another cause of academic dishonesty is the low likelihood of being put on academic probation. This is because most of the students who engage in academic dishonesty do not get caught. This shows that the deterrent measures put in place to stop academic dishonesty are very weak. This reinforces the perception that the likelihood of being caught is low; hence, engaging in academic dishonesty is acceptable.
Also, students who engage in academic dishonesty are not aware of how much the vice affects their ability to acquire the necessary skills. This denies them a competitive edge in the job market. Instructors also fail to educate students on the personal consequences which culminate from engagement in academic dishonesty. One of the consequences of academic dishonesty is the loss of trust on the student by the teacher. This would prevent the instructor from giving a recommendation letter for employment to such a student. Other students claim that they engage in academic cheating since there are so many assignments given by the instructors which are normally due for submission on a short notice. This puts undue pressure on the students who may resort to engaging in academic dishonesty.
Some of the students engage in academic dishonesty because of the perception that they have to get very good grades since the competition in the job market is very stiff. Consequently, there is a lot of pressure on the students to perform extremely well. This, perhaps, tempts them to engage in academic dishonesty. Additionally, it has been observed that universities today have turned into commercial centers, where even those students who are not proficient in writing skills are given an opportunity to study. Since these students cannot perform as expected, they are more likely to engage in academic dishonesty to ensure that they graduate. The net effect of this is that the students who graduate from the universities are not skilled enough to meet the performance targets in the job market.
In order to address this problem, the business school at Bayview should consider having smaller classes during the exam period and also engage strict invigilators. The university should look for ways of reinforcing integrity among the college students with a view of curbing cases of academic cheating. The students can be trained on academic ethics and be encouraged to prioritize their studies above the leisure activities. This would ensure that the students studied on a regular basis, which would help them to be adequately prepared for examinations. This would help in reducing cheating cases among the students.
Furthermore, the university can consider procuring software which can help in detecting plagiarism. This can be used to check the students’ assignment to ensure that they abide by the academic code of ethics. The university should also review its policy on punishing the students who engage in cheating.
Additionally, the university should also consider setting up an ethics centre whose mandate would be to ensure that academic ethics are upheld at all times. This centre should consider having regular seminars where the principles of academic ethics will be transmitted to the students’ body. Additionally, the university should also consider introducing the honor-code system. This is where the students commit themselves to observing academic ethics in their academic pursuits.
The lecturers should also be encouraged to vary the exam and assignment questions to ensure that the students do not get tempted to copy from those done previously by other students. The university policy should also specify the extent of collaboration between students which do not constitute academic dishonesty. This is meant to clarify to the students about what constitutes academic dishonesty and what does not. This would greatly help in reducing cases of academic dishonesty.
The students can also be incorporated in the fight against academic dishonesty. They should be encouraged to report such cases whenever they witness them happen. This can work especially in situations where the students uphold the principles of academic ethics. It can be concluded that if the students are taught to uphold these principles, they are likely to transfer this to the job market. This would ensure that employers would have employees who observe business ethics at all times in their work. This will play a big role in curbing cheating and any other form of academic dishonesty in the universities. Learning institutions should work extra hard and implement measures that they consider apt in dealing with cheating, especially during exams.
Brown, A. (2005). Proceedings of the 4th European Conference on Research Methodology for Business and management studies. London, United Kingdom: Academic Conferences Limited.
Whitley, B., & Spiegel, P. (2002). Academic Dishonesty: An Educator’s Guide. Mahwah, NJ: Taylor & Francis.