Application of K-Means Algorithm for Clustering Student’s Computer Programming Performance in Automatic Programming Assessment Tool
- DOI
- 10.2991/aer.k.201124.075How to use a DOI?
- Keywords
- programming assessment tool, programming, clustering, K-Means
- Abstract
Programming is a course that is considered quite difficult for most students. Students are required to have abilities in all processes. Computer programming skills require a lot of practice through lab work assignments. Managing and assessing results of a student’s lab work assignment is complex and quite time-consuming task. The availability of automatic programming assessment tools to receive the results of lab work assignments and automatically correct and assess can ease the task of a lecturer. Grouping students according to their level of performance, makes it easy for lecturers to monitor student performance levels and can provide learning according to students’ abilities. Grouping was done using K-Means clustering method. Data was score obtained from the lab work assignment of the Automatic Programming Assessment Tool. From the results of clustering, there were 3 groups of students based on their abilities, namely 16 people in the medium ability group, 11 people were students with high ability and 14 people were students whose programming abilities were still lacking.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Anita Qoiriah AU - Rina Harimurti AU - Andi Iwan Nurhidayat AU - Asmunin PY - 2020 DA - 2020/11/24 TI - Application of K-Means Algorithm for Clustering Student’s Computer Programming Performance in Automatic Programming Assessment Tool BT - Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020) PB - Atlantis Press SP - 421 EP - 425 SN - 2352-5401 UR - https://doi.org/10.2991/aer.k.201124.075 DO - 10.2991/aer.k.201124.075 ID - Qoiriah2020 ER -