TY - GEN
T1 - Factors associated with academic dishonesty in Peruvian engineering students
AU - Valdivia, Victoria Emperatriz Ramirez
AU - Goycochea, Hugo Andres Bayona
AU - Davila, Federico Alexis Duenas
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/5
Y1 - 2020/11/5
N2 - Academic dishonesty has become a general practice at school and university. What is more, it is, nowadays, on the rise due to virtual education. This is a problem that needs to be fought so as to avoid its probable transfer to professional performance. For this, additional research is needed to understand the causes of academic dishonesty, and develop methods promoting prevention. This study aims to explore this phenomenon through factors related to different social cognitive theory models, learning approaches and regulatory academic environment. With a sample of 186 university students from a private university in Lima, results show the existing relation between academic dishonesty and associated factors. Furthermore, it is shown the interaction effect among them. It was found that three important dimensions or vectors can be determined: Unethical Manipulation, Deep Learning and Regulatory Context.
AB - Academic dishonesty has become a general practice at school and university. What is more, it is, nowadays, on the rise due to virtual education. This is a problem that needs to be fought so as to avoid its probable transfer to professional performance. For this, additional research is needed to understand the causes of academic dishonesty, and develop methods promoting prevention. This study aims to explore this phenomenon through factors related to different social cognitive theory models, learning approaches and regulatory academic environment. With a sample of 186 university students from a private university in Lima, results show the existing relation between academic dishonesty and associated factors. Furthermore, it is shown the interaction effect among them. It was found that three important dimensions or vectors can be determined: Unethical Manipulation, Deep Learning and Regulatory Context.
KW - academic dishonesty
KW - associated factors.
KW - ethics
KW - university students
UR - http://www.scopus.com/inward/record.url?scp=85099163925&partnerID=8YFLogxK
U2 - 10.1109/ICACIT50253.2020.9277689
DO - 10.1109/ICACIT50253.2020.9277689
M3 - Conference contribution
AN - SCOPUS:85099163925
T3 - Proceedings of the 2020 IEEE International Symposium on Accreditation of Engineering and Computing Education, ICACIT 2020
BT - Proceedings of the 2020 IEEE International Symposium on Accreditation of Engineering and Computing Education, ICACIT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Symposium on Accreditation of Engineering and Computing Education, ICACIT 2020
Y2 - 5 November 2020 through 6 November 2020
ER -