On Regression Modeling for Students’ Attitude towards Statistics Online Learning in Higher Education
Keywords:
Statistics online learning, Students’ attitude, Statistical Model, Higher educationAbstract
Students during the distance education were experiencing solitude and depression in their studies due to no social interaction which led to psychological suffering. In this article, college students' attitudes toward statistics learning were investigated, and its predictors by statistical modeling. Secondary data was extracted from a current study from the literature, summarized using descriptive statistics, and presented in tabular form. As for modeling the predictors of students' attitudes in learning statistics, it was done through multiple linear regression via the ordinary least square (OLS) approach. The finding of statistical calculations revealed that, on average, students possess a "neutral attitude" towards learning statistics online. This suggests that students do not show active involvement and positive engagement in the classroom environment due to some challenges they have encountered during online learning. The regression model I revealed that students who are using mobile phones, fewer study hours in statistics, and intimate relationships with teachers are the significant factors of positive attitude in learning. On the other hand, regression model II showed that low internet signal and low mental health are significant determinants of positive behavior in learning statistics online. Conclusively, students who have suitable gadgets for online learning and with good vibes with their teachers have good performance in class even if they study less, however, effective. Moreover, students with less distraction on social media and with mental stress, tend to deviate their attention in studying their lessons in statistics which positively increases their learning attitude and well-being.
References
Alabekee, E. C., Samuel, A. and Osaat, S. D. (2015). Effect of cooperative learning strategy on students' learning experience and achievements in mathematics. International Journal of Education Learning and Development, 3(4), 67-75.
Allison, P. D. (2012). Logistic regression using SAS: Theory and application. SAS Institute. Retrieved from https://mycourses.aalto.fi/pluginfile.php/889996/mod_resource/content/2/Paul%20D.%20Allison%20%20Logistic%20Regression%20Using%20SAS%20%20Ch%202.pdf
Almarashdi, H., & Jarrah, A. M. (2021). Mathematics distance learning amid the COVID-19 pandemic in the UAE: High school students' perspectives. International Journal of Learning, Teaching and Educational Research, 20(1), 292-307.
Amendola, S., von Wyl, A., Volken, T., Zysset, A., Huber, M., & Dratva, J. (2021). A longitudinal study on generalized anxiety among university students during the first wave of the COVID-19 pandemic in Switzerland. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.643171
Arribathi, A. H., Suwarto, Miftakhu Rosyad, A., Budiarto, M., Supriyanti, D., & Mulyati, F. (2021). An analysis of student learning anxiety during the COVID-19 pandemic: a study in Higher Education. The Journal of Continuing Higher Education, 69(3), 192-205.
Azizah, A., Rizal, R., Yudtika, A. P., & Sitepu, M. S. (2022). Teacher Creativity Relationship with Interest Students Learning at SD Inpres Lolu During Pandemic. Nazhruna: Jurnal Pendidikan Islam, 5(2), 777-786.
Bacolod, D. B. (2022). Mobile Learning as a Solution for Restricted Learning during the COVID-19 Pandemic. J. Digit. Educ. Technol, 2(1), 1-7. https://doi.org/10.21601/jdet/11584
Boruchowicz, C., Parker, S. W., & Robbins, L. (2022). Time use of youth during a pandemic: evidence from Mexico. World Development, 149, 1-13. https://doi.org/10.1016/j.worlddev.2021.105687
Bustillo, E., & Aguilos, M. (2022). The Challenges of modular learning in the wake of COVID-19: A digital divide in the Philippine countryside revealed. Education Sciences, 12(7), 1-16.
Capinding, A. T. (2021). Analysis of Learning and Academic Performance of Education Students before and during the Coronavirus Disease Pandemic. European Journal of Educational Research, 10(4), 1953-1962.
Casinillo, L. F. (2022a). Modeling determinants of challenge in learning statistics in time of the COVID-19 pandemic. Philippine Social Science Journal, 5(3), 131-139.
Casinillo, L. F. (2022b). Modeling Creativity and Enjoyment in Learning Statistics Online in the New Normal. Philippine Social Science Journal, 5(4), 100-108. https://doi.org/10.52006/main.v5i4.601
Casinillo, L. F., & Miñoza, S. B. (2020). The suitability of students in Bachelor of Science in Statistics (BSS) program. Journal of Education Research and Evaluation, 4(4), 343-351.
Cassibba, R., Ferrarello, D., Mammana, M. F., Musso, P., Pennisi, M., & Taranto, E. (2021). Teaching mathematics at a distance: A challenge for universities. Education Sciences, 11(1), 1-20.
Chrikov, I., Soria, K. M., Horgos, B., & Jones-White, D. (2020). Undergraduate and graduate students’ mental health during the COVID-19 pandemic. Retrieved from https://conservancy.umn.edu/handle/11299/215271
Code, W., Merchant, S., Maciejewski, W., Thomas, M., & Lo, J. (2016). The Mathematics Attitudes and Perceptions Survey: an instrument to assess expert-like views and dispositions among undergraduate mathematics students. International Journal of Mathematical Education in Science and Technology, 47(6), 917-937.
Counsell, A., & Cribbie, R. A. (2020). Students' Attitudes toward Learning Statistics with R. Psychology Teaching Review, 26(2), 36-56.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.
De Aquino, M. A., Balingit, A. M., Bontog, A. D., Fortugaliza, P. J. S., Hungo, M. O., & Casinillo, L. F. (2023). The sentiments of students and teachers on modular distance learning amid the health crisis. Indonesian Journal of Educational Research and Review, 6(2), 299-309. https://doi.org/10.23887/ijerr.v6i2.61478
Essadek, A., & Rabeyron, T. (2020). Mental health of French students during the Covid-19 pandemic. Journal of Affective Disorders, 277, 392-393.
Garzon, J. R., & Casinillo, L. (2021). 5E guided inquiry model and students’ attitude and achievement in algebraic expressions. Review of Socio-Economic Research and Development Studies, 5(1), 1-22.
Hooshyar, D., Malva, L., Yang, Y., Pedaste, M., Wang, M., & Lim, H. (2021). An adaptive educational computer game: Effects on students' knowledge and learning attitude in computational thinking. Computers in Human Behavior, 114, Retrieved from https://doi.org/10.1016/j.chb.2020.106575
Ismaili, Y. (2021). Evaluation of students’ attitude toward distance learning during the pandemic (COVID-19): a case study of ELTE university. On the Horizon, 29(1), 17-30.
Jazayeri, M., Li, X., Morris, E., Laurence, D., & Loch, B. (2022). Reducing statistics anxiety for psychology students during the global pandemic: a methodology approach. International Journal of Mathematical Education in Science and Technology, 53(2022), 1-20.
Lederer, A. M., Hoban, M. T., Lipson, S. K., Zhou, S., & Eisenberg, D. (2021). More than inconvenienced: The unique needs of US college students during the COVID-19 pandemic. Health Education & Behavior, 48(1), 14-19.
Macher, D., Paechter, M., Papousek, I., & Ruggeri, K. (2012). Statistics anxiety, trait anxiety, learning behavior, and academic performance. European journal of psychology of education, 27(4), 483-498.
Mátyás, L., & Sevestre, P. (Eds.). (2013). The econometrics of panel data: Handbook of theory and applications (Vol. 28). Springer Science & Business Media. Retrieved from https://link.springer.com/book/10.1007/978-94-009-0375-3
Miñoza, S. B., & Casinillo, L. F. (2022). Profiling Bachelor of Science in Statistics (BSS) students under the open enrolment policy. IJIET (International Journal of Indonesian Education and Teaching), 6(1), 1-24.
Nikolopoulou, K. (2022). Students’ Mobile Phone Practices for Academic Purposes: Strengthening Post-Pandemic University Digitalization. Sustainability, 14(22), 1-13.
Savage, M. J., James, R., Magistro, D., Donaldson, J., Healy, L. C., Nevill, M., & Hennis, P. J. (2020). Mental health and movement behaviour during the COVID-19 pandemic in UK university students: Prospective cohort study. Mental Health and Physical Activity, 19, 1-6.
Sinaga, R. R. F., & Pustika, R. (2021). Exploring students’ attitude towards English online learning using Moodle during COVID-19 pandemic at smk yadika bandarlampung. Journal of English Language Teaching and Learning, 2(1), 8-15.
Wang, X., Hegde, S., Son, C., Keller, B., Smith, A., & Sasangohar, F. (2020). Investigating mental health of US college students during the COVID-19 pandemic: Cross-sectional survey study. Journal of Medical Internet Research, 22(9), 1-11.
