Earticle

초록

영어

Background/Objective. The COVID-19 has accelerated the conduct of online classes around the world. To administer distant learning, schools are now relying on learning management systems. With the problems of the abrupt shift to an online modality, there must be measures in place to cluster students’ characteristics in order to assist their learning requirements, struggles, and academic performances. Methods/Statistical Analysis. Based on Delone and McLean’s IS Success model, this study used quantitative approaches and exploratory techniques to explain the higher education learners’ clusters. From March to April 2021, 303 samples were randomly selected from students participating in online programs at a higher education school on Taft Avenue in Manila. Sex, school, frequency of use, time duration, and experience with the LMS were all factors in the study. Both Hierarchical Cluster Analysis and K-Means Cluster Analysis were used to classify the samples. Findings. The results revealed that there are four clusters formed which are labeled as: service-oriented, system quality-oriented, holistic-oriented, and LMS-averse. Based on the results, information quality has the greatest influence. Since the clustering analysis is non-inferential and it is used as an exploratory technique, the researchers do not guarantee a unique solution as this depends on the elements of the subjects and the variables used. Improvements/Applications. The academic stakeholders can use the cluster analysis to make the appropriate interventions to improve the online course content and enhance the students’ academic performance. Some of these appropriate interventions include creating course policies, planning the necessary training of teachers and students, and developing the online delivery of the lessons.

목차

Abstract
I. INTRODUCTION
II. METHODS
A. Research Design
B. Participants
C. Measures
D. Reliability
D. Validity
E. Procedures
F. Data Analysis
III. RESULTS
A. Demographic Profile
B. Descriptive Statistics
C. Hierarchical Cluster Analysis
IV. DISCUSSIONS
V. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Dr. Hector John T. Manaligod [ Computer Applications Program, SMIT, De La Salle College of Saint Benilde, Manila, Philippines ] Corresponding author
• Rogelio V. del Cano [ Busines Intelligence and Analytics Program, SMIT, De La Salle College of Saint Benilde, Manila, Philippines ]
• Jelica Enriquez [ Busines Intelligence and Analytics Program, SMIT, De La Salle College of Saint Benilde, Manila, Philippines ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  IJASC

• 간기

  계간

• pISSN

  2619-8150

• 수록기간

  2019~2024

• 십진분류

  KDC 327 DDC 332