creators_name: Nur Amalina Diyana Suhaimi , 
creators_name: Norshaliza Kamaruddin, 
creators_name: Thirumeni T Subramaniam, 
creators_name: Nilam Nur Amir Sjarif, 
creators_name: Maslin Masrom, 
creators_name: Nurazean Maarop, 
type: conference_item
datestamp: 2022-08-05 00:45:52
lastmod: 2022-08-05 00:45:52
metadata_visibility: show
title: Classification of Learner Retention using Machine Learning Approaches
ispublished: pub
subjects: 1028
subjects: LB2300
full_text_status: none
pres_type: paper
keywords: learner retention, supervised machine learning, classification, performance, CRISP-DM Process
abstract: Learner retention issues require a huge commitment from a university as the process of monitoring learners' re-registration status from the beginning of each semester until they graduate can be quite tedious. When the number of learners who re-register for a subsequent semester is low, it not only affects the university's image but also its ranking and reputation in the education sector. Therefore, the university must identify, at an early stage, the likelihood of a learner is not retained in the following semester. This study proposed to experiment with the classification methods for solving the issue of learner retention at Open University Malaysia by comparing three Supervised Machine Learning algorithms namely Logistic Regression, Support Vector Machine, and k-Nearest Neighbor. The performance of these algorithms was evaluated based on accuracy, precision, recall, and f-measure. It is determined that Support Vector Machine showed the best accuracy in classifying the learners' retention rate with 80% accuracy. The benefit of performing Machine Learning is that it enables the identification of at-risk learners at the earliest opportunity and therefore implement the earliest interventions to retain them. (Abstract by authors)
date: 2021
date_type: published
event_title: 2021 7th International Conference on Research and Innovation in Information Systems (ICRIIS)
event_location: Johor Bahru, Malaysia
event_dates: 25-26 October 2021
event_type: conference
refereed: TRUE
official_url: https://ieeexplore.ieee.org/abstract/document/9617055
citation:   Nur Amalina Diyana Suhaimi ,  and Norshaliza Kamaruddin,  and Thirumeni T Subramaniam,  and Nilam Nur Amir Sjarif,  and Maslin Masrom,  and Nurazean Maarop,   (2021) Classification of Learner Retention using Machine Learning Approaches.  In: 2021 7th International Conference on Research and Innovation in Information Systems (ICRIIS), 25-26 October 2021, Johor Bahru, Malaysia.