Demographic Influences towards Online Classes: A Correlational Analysis
DOI:
https://doi.org/10.51983/arss-2021.10.1.2679Keywords:
Business and Accountancy, Online Teaching, Descriptive Correlational, Mandaue City, PhilippinesAbstract
An online teacher needs to give a constant flow of commitment that can serve the progression of unessential data that goes after both time and core interest. The study determines the correlation of demographic profile and its influences on student’s perception towards online classes. The study contrived 313 respondents who are currently enrolled in the College using the snowball inspecting strategy. Frequency and simple percentage, Weighted Mean, Chi-Square Test of Independence, and one-way ANOVA were used to analyzed and interpret the data accumulated. The discoveries uncovered that the understudies slightly perceived online classes in learning diversification, peer interactions, user-friendliness, online course quality, and course design. The investigation also revealed a statistically significant relationship between the respondent's course, family income, and family structure to the level of perception towards online classes. Moreover, there is a statistically significant difference between family income and family structure by its influence on students' perception of online classes. The study concluded that correlational analysis among students explains the demographic factors affecting their concentration on online classes. Family income and structure play a significant role and greatly influences understudies enthusiasm in the College of Business and Accountancy online classes.
References
Alampay L.P. (2014). Parenting in the Philippines. In: Selin H. (eds) Parenting Across Cultures. Science Across Cultures: The History of Non-Western Science, 7, Springer, Dordrecht. Retrieved from https://bit.ly/3h7aVVX
Chao, I. T., Saj, T., & Hamilton, D. (2010). Using collaborative course development to achieve online course quality standards. The International Review of Research in Open and Distributed Learning, 11(3), 1-106. Retrieved from https://bit.ly/37ZzFen
Chen, H. T. (2012). Theory-driven evaluation: Conceptual framework, application, and advancement. Alabama, Birmingham, Sage Publications. ISBN- 1452252440. Retrieved from https://bit.ly/37XIpBT
Crecelius, S. A. (2014). The Effect of Socioeconomic Status on Student Perceptions of Instructional Communication Behaviors. Sycamore Scholars. Retrieved from https://bit.ly/2JbAHM9
Crews, T. B., Bordonada, T. M., & Wilkinson, K. (2017. ) Student Feedback on Quality Matters Standards for Online Course Design. Educause review. Retrieved from https://bit.ly/2XFMciO
Dail, T. K. (2010). Online student engagement tools and strategies. Magna Publications Inc. Retrieved on August 6, 2020. Retrieved from https://bit.ly/2PtW6zF
Dee, L. F. (2017). The Power of Course Design to Increase Student Engagement and Learning. Association of American Colleges & Universities. Retrieved from https://bit.ly/3a9Cv11
Dela Pena, M. M. (2009). E-learning in the Philippines: trends, directions, and challenges. International Journal of on E-learning. 8(4), 1-16. Retrieved from https://bit.ly/37ggON7
Department of Education (2020). The basic education learning continuity plan in the time of COVID-19. Retrieved from https://bit.ly/30DcG6J
Donaldson, S. (2012). Strategies and Applications: Program Theory-Driven Evaluation of Science. Hove, East Sussex BN3 2FA, New York: Routledge. Retrieved from https://bit.ly/37cOUkY
Downes, S. (2010). New technology supporting informal learning. Journal of Emerging Technologies in Web Intelligence, 2(1), 27-33. Retrieved from https://bit.ly/2mStsO0
Funnell, C., & Rogers, P. J. (2011). Purposeful Program Theory: Effective Use of Theories of Change and Logic Models. San Francisco, California. John Wiley & Sons. Retrieved from https://bit.ly/2LpUpEw
Han, W.-J., Huang, C.-C., & Garfinkel, I. (2003). The importance of Family Structure and Family Income on Family’s Educational Expenditure and children's College Attendance: Empirical Evidence from Taiwan. Journal of Family Issues, 24(6), 753–786. Retrieved from https://bit.ly/37Dj1lO
Juvonen, J., Espinoza, G., & Knifsend, C. (2012). The Role of Peer Relationships in Student Academic and Extracurricular Engagement. Handbook of Research on Student Engagement, 387–401. Retrieved from https://bit.ly/3qRR5SU
Llego, M. A. (2020). DepEd's readiness for distance learning. Professional learning online community of teachers and for teachers. Retrieved from https://bit.ly/30DcG6J
Lynch, M. (2019). 6 elements that hinder the user-friendliness of your online training. The tech advocate. Retrieved from https://bit.ly/33F0lAL
Nikitina, A. (2019). Adaptive Learning Technologies For People With ADHD. Educational Technology. Retrieved December 22, 2020, from https://bit.ly/3mJkewe
Rogers, E. M. (2003). Diffusion of innovations. (5th Ed.). New York: Free Press. Retrieved from https://bit.ly/3mhOFcN
Semuels, A. (2017). Poor Girls are Leaving their Brothers Behind, The Atlantic. Retrieved from https://bit.ly/2KH4w7E
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1). Retrieved from https://bit.ly/3h9Eqq0
Parrish, G. (2020). Designing a Course. The Teaching Center. Retrieved from https://bit.ly/30Gw96r
Philippines Statistics Authority (2019). Filipino Families in the Poorest Decile Earn Six Thousand Pesos Monthly, on Average in 2012 (Results from the 2012 Family Income and Expenditure Survey). Retrieved from https://bit.ly/2KHkXRo
Wragg, E.T., Raby, C., Ménard, L., & Plante, I. (2019). The use of diversified teaching strategies by four university teachers: what contribution to their students' learning motivation?, Teaching in Higher Education, Retrieved from https://bit.ly/3h6F4EO
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 The Research Publication
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.