Neuro Linguistic Programming for Academic Cheating in Mathematics Classes

Abstract

This research aims to determine and identify the factors responsible for academic cheating in mathematics learning using the Neuro Linguistic Programming (NLP). This qualitative research with the Miles and Huberman data analysis techniques consists of reduction, presentation, and drawing conclusions used as a case study design. Data were collected from students of one of the schools in Majalengka City using interview techniques and still image data collection. The results showed 14 forms of academic cheating in mathematics learning classified into plagiarism, fabrication, exploitation of other people's weaknesses, wrong cooperation, attempts to cheat before the test, use of prohibited tools during the exam, and manipulation of assignments. A total of 12 factors trigger academic cheating in mathematics learning. These include internal, external, learning, and academic cheating resistance factors. The identification results using NLP showed some students do not aim to commit in academic cheating. However, a total of 9 obstacles were in accordance with their viewpoints using the frame and metamodels. Therefore, students assume academic cheating is an appropriate action to respond to a situation.