Abstract
There is growing interest in “gaming the system” behavior, where students in online learning environments seek to progress without engaging in authentic learning processes. This study addresses this issue, aiming to automatically recognize this behavior in beginning programmers from a public and rural school in Northeast Brazil, as well as analyzing the demographic context of these students identified with this behavior. With the participation of 67 students, we collected data through student interactions with a programming learning environment, developing an automatic detection model. As a result, our detector based on the decision tree algorithm provided the best performance. Our findings highlight a significant difference between the group of students who exhibit “gaming the system” behavior and those who do not. Furthermore, younger students are more likely to exhibit such behavior.
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Joyse Barbosa Rocha, H., de Barros Costa, E., Cabral de Azevedo Restelli Tedesco, P. (2024). Automated Detection and Analysis of Gaming the System in Novice Programmers. In: Olney, A.M., Chounta, IA., Liu, Z., Santos, O.C., Bittencourt, I.I. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2024. Communications in Computer and Information Science, vol 2150. Springer, Cham. https://doi.org/10.1007/978-3-031-64315-6_30
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