Research Article
Analysing correlation between sequential event in student’s learning path
@INPROCEEDINGS{10.4108/eai.11-10-2022.2326327, author={Sulfikar Sallu and Tekad Matulatan and Muhammad Resha}, title={Analysing correlation between sequential event in student’s learning path}, proceedings={Proceedings of the 1st International Conference on Sustainable Engineering Development and Technological Innovation, ICSEDTI 2022, 11-13 October 2022, Tanjungpinang, Indonesia}, publisher={EAI}, proceedings_a={ICSEDTI}, year={2023}, month={1}, keywords={learning analytics educational data mining correlation analysis}, doi={10.4108/eai.11-10-2022.2326327} }- Sulfikar Sallu
Tekad Matulatan
Muhammad Resha
Year: 2023
Analysing correlation between sequential event in student’s learning path
ICSEDTI
EAI
DOI: 10.4108/eai.11-10-2022.2326327
Abstract
The relationship between a course and other subjects described in the curriculum does not explain how much the relationship is supposed to influence the success of students’ learning path. Also, some courses are not explicitly written as prerequisites to any other course in the curriculum, but still contribute significantly to the success of the subsequent course. One common way to find the correlation between these courses is by using the classical Pearson Test, but this might ignore the detail of the relationship. This can be improved by incorporating the PCA cross-matrix technique with an improved and more-detailed per-grade relation, not just a general view. This means that students who perform excellently in the previous course might also perform very well in a subsequent one. From the obtained results, it can be seen that the incorporation of the PCA cross matrix technique with a detailed description of the correlation's strength between the prerequisite course and the course it is prerequisite to, based on the results of the former, added more details to the classical Pearson test.