Predicting Outcomes in Introductory Programming using J48 Classification
| Main Authors: | Ayub, Mewati, Karnalim, Oscar |
|---|---|
| Format: | Article PeerReviewed Book |
| Terbitan: |
World Institute for Engineering and Technology Education (WIETE)
, 2017
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| Subjects: | |
| Online Access: |
http://repository.maranatha.edu/24316/1/A3%202017-07%20WTE%26TE%20ISSN-1446-2257.pdf http://repository.maranatha.edu/24316/ |
Daftar Isi:
- In a computer science (CS) major, Introductory Programming becomes a substantial course, which determines whether students can complete that major or not. This study evaluates the correlation between student data with the students’ capacity to pass that course. Such correlation is exploited according to a data mining technique called J48. For each student, the work incorporates personal, prior education, admission and assessment data. Based on an evaluation of 41 pieces of student data, the national test score for mathematics in Indonesia presents the most promising attributes, followed by the admission test score. The results of this study are expected to provide a brief insight for CS lecturer and the university, so that they can handle emerging issues in CS education, especially, the low retention rate.