Exploring student emotional experiences in mathematics and statistics courses via online learning
Abstract
Online learning is now generally acknowledged and seen as a crucial strategy for overcoming the drawbacks of on-campus instruction, particularly in higher education. Online learning adaptability provides students with a wide range of placement options, from on-the-go placements in the midst of their daily lives to dedicated time and space for learning. Since student emotional involvement has been linked to learning and academic success, it is crucial to investigate student emotions. Therefore, this study uses a factor analysis approach to explore the emotional experiences of all Universiti Poly-Tech Malaysia (UPTM) students that enrolled in Mathematics and Statistics courses for the academic semester of April 2022. The students have completed a survey-adapted version of the Achievement Emotions Questionnaire (AEQ-S) consisting of 24 items that surveyed emotional experiences before, during and after online classes. Demographic information was collected, encompassing variables like cumulative grade point average (CGPA), online learning tools, internet stability and measurement of students' enjoyment, pride, anxiety, anger, hopelessness, and boredom. A ten-point Likert scale ranging from "strongly disagree" to "strongly agree" measured the respondents' agreement with each item. The result demonstrated that emotions towards an online-based learning system are multifaceted, with three components explored, namely "Frustration and Disengagement", "Motivation and Achievement", and "Anxiety and Apprehension".
Full text article
References
AlAteeq, D. A., Aljhani, S., & AlEesa, D. (2020). Perceived stress among students in virtual classrooms during the COVID-19 outbreak in KSA. Journal of Taibah University Medical Sciences. https://doi.org/10.1016/j.jtumed.2020.07.004
Anshari, M., Alas, Y., Hj Mohd Yunus, N., Pg Hj Sabtu, N. I., & Sheikh Abdul Hamid, M. H. (2016). Online learning: Trends, issues, and challenges in the big data era. Journal of E-Learning and Knowledge Society, *12*(1), 121–134. https://doi.org/10.20368/1971-8829/1003
Artino, A. R. (2012). Emotions in online learning environments: Introduction to the special issue. Internet and Higher Education, *15*(3). https://doi.org/10.1016/j.iheduc.2012.04.001
Ashcraft, M. H., & Faust, M. W. (1994). Mathematics anxiety and mental arithmetic performance: An exploratory investigation. Cognition and Emotion, *8*(2), 97–125. https://doi.org/10.1080/02699939408408931
Ashcraft, M. H., & Krause, J. A. (2007). Working memory, math performance, and math anxiety. Psychonomic Bulletin and Review, *14*(2), 243–248. https://doi.org/10.3758/BF03194059
Biasutti, M. (2017). A comparative analysis of forums and wikis as tools for online collaborative learning. Computers and Education, *111*, 158–171. https://doi.org/10.1016/j.compedu.2017.04.006
Bieleke, M., Gogol, K., Goetz, T., Daniels, L., & Pekrun, R. (2021). The AEQ-S: A short version of the Achievement Emotions Questionnaire. Contemporary Educational Psychology, *65*. https://doi.org/10.1016/j.cedpsych.2020.101940
Bonett, D. G., & Wright, T. A. (2017). Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior. https://doi.org/10.1002/job.1960
Bower, M. (2019). Technology-mediated learning theory. British Journal of Educational Technology, *50*(3), 1035–1048. https://doi.org/10.1111/bjet.12771
Cattell, R. B. (2010). The scree test for the number of factors. Multivariate Behavioral Research, *1*(2), 245–276. https://doi.org/10.1207/S15327906MBR0102_10
Estonanto, A. J. J., & Dio, R. V. (2019). Factors causing mathematics anxiety of senior high school students in calculus. Asian Journal of Education and E-Learning, *7*(1). https://doi.org/10.24203/AJEEL.V7I1.5701
Gaballa, S., Hlaing, K., Lindsay, J., Aljaf, A., Patel, K., Owusu, A., Moursy, S., Ahmed, A., & Patel, B. (2020). COVID-19 fears may be worse than the virus: A case of cardiogenic shock secondary to post myocardial infarction ventricular septum rupture. Chest. https://doi.org/10.1016/j.chest.2020.08.948
Gonzalez, T., De la Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, L., Fort, S., & Sacha, G. M. (2020). Influence of COVID-19 confinement on students' performance in higher education. PLoS ONE, *15*(10), 1–23. https://doi.org/10.1371/journal.pone.0239490
Hannula, M. S. (2019). Young learners' mathematics-related affect: A commentary on concepts, methods, and developmental trends. Educational Studies in Mathematics, *100*(3). https://doi.org/10.1007/s10649-018-9865-9
Ilias, A., Baidi, N., Ghani, E. K., & Razali, F. M. (2020). Issues on the use of online learning: An exploratory study among university students during the COVID-19 pandemic. Universal Journal of Educational Research, *8*(11), 5092–5105. https://doi.org/10.13189/ujer.2020.081109
Jaggars, S. S., & Xu, D. (2016). How do online course design features influence student performance? Computers and Education, *95*, 270–284. https://doi.org/10.1016/J.COMPEDU.2016.01.014
Landrum, B., Bannister, J., Garza, G., & Rhame, S. (2021). A class of one: Students' satisfaction with online learning. Journal of Education for Business, *96*(2), 82–88. https://doi.org/10.1080/08832323.2020.1757592
Lyons, I. M., & Beilock, S. L. (2012). When math hurts: Math anxiety predicts pain network activation in anticipation of doing math. PLoS ONE, *7*(10). https://doi.org/10.1371/JOURNAL.PONE.0048076
Pekrun, R., Lichtenfeld, S., Marsh, H. W., Murayama, K., & Goetz, T. (2017). Achievement emotions and academic performance: Longitudinal models of reciprocal effects. Child Development, *88*(5), 1653–1670. https://doi.org/10.1111/CDEV.12704
Rasheed, F. A., & Abadi, M. F. (2014). Impact of service quality, trust and perceived value on customer loyalty in Malaysia services industries. Procedia - Social and Behavioral Sciences, *164*, 298–304. https://doi.org/10.1016/j.sbspro.2014.11.080
Riegel, K., & Evans, T. (2021). Student achievement emotions: Examining the role of frequent online assessment. Australasian Journal of Educational Technology, *37*(6), 75–87. https://doi.org/10.14742/ajet.6516
Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, *9*(1), 4–11. https://doi.org/10.12691/ajams-9-1-2
Stephan, M., Markus, S., & Gläser-Zikuda, M. (2019). Students' achievement emotions and online learning in teacher education. Frontiers in Education, *4*, 1–12. https://doi.org/10.3389/feduc.2019.00109
Sun, J., & Zhang, X. (2021). Exploring Chinese college students' emotions as they engage in online learning during a pandemic. Asia Pacific Journal of Education. https://doi.org/10.1080/02188791.2021.1965541
Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students' characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, *34*(3), 302–323. https://doi.org/10.1080/01587919.2013.835779
Authors
Copyright (c) 2024 SURIANA ISHAK, EMI AMIELDA AHMAD MOKHTAR, NOOR FARAH WAHIDA ABDUL RASHID, NIK NUR SYAZREEN NIK ROHAIMI, SYAHIRAH ABDUL KADIR, HAZRINA TAJUDIN

This work is licensed under a Creative Commons Attribution 4.0 International License.