Data on higher education student ethics model

This article describes data collected between July 2018 and December 2018 in Yogyakarta, Indonesia. The data were collected from 566 Indonesian higher education students who completed a survey. The data were analysed using structural equational modelling (SEM) to develop a model of student ethics.


Distribution of students by department
Data were collected from a higher education institution in Indonesia. This study collected 566 surveys completed by respondents from various departments, such as the economic (20.1%), engineering (17.3%), mathematics and natural science (15%), social science (10%), sports science (2.7%), art (21.2%) and educational science (12.9%) departments. Value of data The data from the present sample pertain to the phenomenon of ethical behaviour and represent Indonesian higher education students. The data will be useful for scholars who are interested in investigating models of ethical behaviour among higher education students in Indonesia. The datasets can assist in creating comparative models of ethical behaviour of students based on various internal and external pressures. The data will be valuable for scholars who want to explore comparisons of student ethics inside and outside Indonesian higher education. ET 4. I prefer not to report friends' unethical behaviour to lecturers. ET 5. I commit unethical action when it is beyond my control (e.g., I plagiarize because the academic system emphasises excellent results). ET 6. Using a copy machine, paper and other supplies for personal use is not unethical behaviour. ET 7. I hold to my principle that honesty is more important than getting good grades. ET 8. I take full responsibility for any unethical actions that I take (e.g., I would confess if lecturers found me plagiarizing some assignments). ET 9. I behave ethically and adhere to regulations and codes of ethics outlined by the university. ET 10. I will accept all opinions/considerations of others if I need to make a decision regarding an ethical dilemma. ET 11. During my studies at university, I referred to others to resolve ethical dilemmas. ET 12. I personally dealt with ethical dilemmas while studying at university. ET 13. I have been confronted with ethical dilemmas during my studies at university. ET 14. The faculty (i.e., lecturers, administrators) will reward me when I do something ethical. In general, I believe I can do any assignment well. Mot 3.
In general, I believe I can only do a few assignments well. Mot 4.
In terms of effort, I sometimes try my best. Mot 5.
In terms of effort, I rarely try my best. Mot 6.
In terms of effort, I always try my best. Mot 7.
When my teacher asks a question in class, I volunteer (raise my hand) to answer a lot. Mot 8.
When my teacher asks a question in class, I never volunteer to answer. Mot 9.
When my teacher asks a question in class, I volunteer to answer every once in a while. Mot 10.
If   When uncertain things happen to me on campus, I usually come to the best conclusion. R2.
When mistakes happen to me, I take it as a sign of success. R3.
I always see the positive side of my learning.

R4.
I am optimistic about what will happen to me in the future as relates to my study.

R5.
In achieving my learning goals, I have encountered many failures. R6.
In learning, I always face various obstacles. My study group feels that the problems in the campus environment (related to employment opportunities, parent expectations, or curriculum) can be mitigated by course assignments. TS3.
My study group feels that, if there is a problem with employment, then the industrial practice task can help solve the problem.

Data analysis
The dataset was tested for the quality and adequacy of the measurement model, as suggested by Anderson and Garbing [7], to confirm the previous multi-item construct validation, construct validity and construct reliability The deletion of some items was found to increase acceptable fit. The Cronbach's alpha values for each construct [8] are displayed in Table 9, all showing at least 0.7. Thus, internal consistency was found for all of the constructs measured. Convergent validity was determined by the value of the correlation between each construct (Table 10). Fornell and Larcker suggest that correlations lower than .85 among constructs are good [9]. Therefore, the constructs used in this study show good convergent validity.

Experimental design, materials and methods
The statistical analysis conducted using AMOS version 7.0 showed that the model had an acceptable fit. The chi-squared test (df ¼ 5, c 2 ¼ 28.313) was significant (p < 0.01) [10]. The ratio of chi-square to degree of freedom (df) was 5.66 [11] (CFI ¼ 0.0.947, IFI ¼ 0.948, NFI ¼ 0.938, and TLI ¼ 0.856). Thus, based on the model fit standards endorsed by Marcoulides and Schumacker, the results of CFA indicated a satisfactory fit for the measurement model [12]. Students who follow the cooperation programme regularly report progress and performance regarding their respective cooperation. KA4.
Prodi maintains a 'repository' or database containing information from each agency working with it (e.g., date and purpose of establishment of cooperation, name of partners, names of students managing the cooperation, etc.). KA5.
Prodi has a directory or 'contact list' of individuals from within or outside the university who have the potential to provide input or assistance to improve the quality of co-management.

Table 7
Items measuring cooperative classroom environment.

CCE1.
The class is more fun when I study with other friends. CCE2.
I prefer to study alone. CCE3.
I learn best when with my classmates. CCE4.
I got better grades when I was studying with other friends. CCE5.
I prefer taking classes where students learn together to solve problems.  An empirical model testing the effects of motivation, self-efficacy, resilience, knowledge articulation, team strain, and cooperative classroom environment on students' ethics was examined. The SEM analysis of the final model of the ethical behaviour of higher education students is depicted in Fig. 1. The standardized regression weights of the default model are shown in Table 11.

Implication of construct modelling
Compared to previous datasets, the validation process of the measurement model [7] included item validity and construct reliability and validity. This behaviour model was used to measure the internal and external factors promoting ethical behaviour among higher education students. According to the fit values of the datasets, further investigations of outcomes are encouraged.