Decoding digital learning: a cart analysis insight

Harini, Sri ORCID: https://orcid.org/0000-0001-9664-027X, Mulyanto, Angga Dwi ORCID: https://orcid.org/0000-0002-7068-5784 and Rozi, Fachrur ORCID: https://orcid.org/0000-0002-6380-0297 (2023) Decoding digital learning: a cart analysis insight. BAREKENG: Jurnal Ilmu Matematika dan Terapan, 17 (4). pp. 1845-1854. ISSN 2615-3017

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Abstract

In today's digital era, online education has become an integral component of the global educational system. However, the quality of providers, mastery of online learning media, and the capability of teachers in delivering content significantly influence students' comprehension. Understanding how these factors impact students is crucial for optimizing online educational experiences. This article examines the effect of provider quality, mastery of online learning media, and teacher's capability in teaching on students' understanding in an online learning environment using Classification and Regression Trees (CART). The study focused on the active students of UIN Maulana Malik Ibrahim Malang, totaling 18,104 based on data from PDDIKTI. Due to the vastness of this population, stratified random sampling was employed. The sample size was determined using the Kock and Hadaya method, resulting in a minimum sample of 271. Each sample in the stratum was taken based on the proportion of the population across 19 departments, with the Department of Psychology having the largest sample size of 20 students and the Department of Library and Information Science the smallest with 4 students. The findings revealed that a teacher's capability has a more profound influence on students' understanding than mastery of online learning media, while provider quality showed no significant impact. To enhance the effectiveness of online learning, it's recommended that educational institutions invest in teacher training focused on effective teaching methodologies and technological utilization, and also ensure the selection of online learning platforms that cater to student needs.

Item Type:	Journal Article
Keywords:	classification and regression trees; teaching in students’ understanding; online learning; provider quality; mastery of online learning media; teacher's capability
Subjects:	01 MATHEMATICAL SCIENCES > 0104 Statistics
Divisions:	Faculty of Mathematics and Sciences > Department of Mathematics
Depositing User:	Angga Dwi Mulyanto
Date Deposited:	22 Dec 2023 08:59

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