Artificial Intelligence Integration: Error Self-Reflection in Solving Integral Problems

Integrity has had plenty of impact on human civilization development, especially in the development of human technology. The primary role of an integral is not well supported by students’ skill in solving integral problems. Due to this fact, mathematics educators need solutions. Artificial Intelligence (AI) integration is one of the solutions that mathematics educators can choose. This qualitative descriptive research aims to explore students' mistakes in solving integral problems with the help of Photomath. This research will describe student mistakes and explain how students realize mistakes during rework assisted by Photomath. This research involved ten mathematics students who joined an integral course at a university in Indonesia. The errors were analyzed based on Newman error analysis. Errors found based on research results include (1) Comprehension and transformation, (2) Process skills, and (3) Encoding. This research found that comprehension errors have implications for transformation. Students who make comprehension errors will cause transformation errors. Meanwhile, the subject's errors in the previous stage affect the encoding stage. Apart from the errors already mentioned, errors were also found due to carelessness, which was not a significant part of Newman's error analysis.