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Abstract

In this study, we focus on self-disclosure, communicating mathematics, and infrastructure support in determining the ease of online learning for students of mathematics education study programs. The sample in this study were students (n=465) who were asked voluntarily to fill out an online questionnaire. Participants consisted of 335 female students (72%) and 130 male students (28%) from various universities in Indonesia. The data were analyzed quantitatively using structural equation modeling. The results of the path analysis show that the ease of online learning is influenced by self-disclosure, communicating mathematics, and infrastructure support. The R square results show that these factors influence 47%. Each path analysis shows that self-disclosure (r = 0.556 p= 0.000) and infrastructure support (r = 0.243 p = 0.000) have a significant positive relationship with the ease of online learning. Meanwhile, communicating mathematics (r = -0.025 p =0.507) has an insignificant negative relationship to the ease of online learning. Further research is needed to see how the impact of mathematical application support communicating mathematics in online learning.

Keywords

Higher Education Infrastructure Support Mathematical Communication Online Learning

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References

  1. Akaslan, D., & Law, E. L.-C. (2011). Measuring student e-learning readiness: A case about the subject of electricity in higher education institutions in Turkey. In H. Leung, E. Popescu, Y. Cao, R. W. H. Lau, & W. Nejdl, In Advances in Web-Based Learning - ICWL 2011, Berlin, Heidelberg.

  2. Assunção Flores, M., & Gago, M. (2020). Teacher education in times of COVID-19 pandemic in Portugal: national, institutional and pedagogical responses. Journal of Education for Teaching, 46(4), 507-516. https://doi.org/10.1080/02607476.2020.1799709

  3. Bao, W. (2020). COVID-19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113-115. https://doi.org/10.1002/hbe2.191

  4. Bernhold, Q. S., & Rice, R. (2020). Toward an integrated model of online communication attitudes, communication frequency, and relational closeness. Communication Studies, 71(1), 1-21. https://doi.org/10.1080/10510974.2019.1683594

  5. Borba, M. C. (2012). Humans-with-media and continuing education for mathematics teachers in online environments. Zdm, 44(6), 801-814. https://doi.org/10.1007/s11858-012-0436-8

  6. Bussey, S. (2021). Inclusivity in online postgraduate teaching. In T. Fawns, G. Aitken, & D. Jones (Eds.), Online Postgraduate Education in a Postdigital World: Beyond Technology (pp. 105-120). Springer International Publishing. https://doi.org/10.1007/978-3-030-77673-2_6

  7. Chen, R., & Sharma, S. K. (2015). Learning and self-disclosure behavior on social networking sites: the case of Facebook users. European Journal of Information Systems, 24(1), 93-106. https://doi.org/10.1057/ejis.2013.31

  8. Chorrojprasert, L. (2020). Learner readiness—why and how should they be ready? LEARN Journal: Language Education and Acquisition Research Network, 13(1), 268-274.

  9. Dangol, R., & Shrestha, M. (2019). Learning readiness and educational achievement among school students. The International Journal of Indian Psychology, 7(2), 467-476.

  10. Diana, N., Suhendra, S., Yohannes, Y., & Sukma, Y. (2021). Primary students’ perceptions toward the effectiveness of online learning during the COVID-19 pandemic. Journal of Hunan University Natural Sciences, 48(10), 577-584.

  11. Elmunsyah, H., Hidayat, W. N., Ulfa, S., Surakhman, E., & Wakhidah, R. (2020). Measuring user experience on personalized online training system to support online learning. IOP Conference Series: Materials Science and Engineering, 732(1), 012115. https://doi.org/10.1088/1757-899X/732/1/012115

  12. Engelbrecht, J., Llinares, S., & Borba, M. C. (2020). Transformation of the mathematics classroom with the internet. Zdm, 52(5), 825-841. https://doi.org/10.1007/s11858-020-01176-4

  13. Gay, G. H. E. (2016). An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education, 28(2), 199-220. https://doi.org/10.1007/s12528-016-9115-z

  14. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203

  15. Hariyono, M., Widhi, E. N., & Ulia, N. (2021). Digital geoshapes learning media In supporting mathematics education II PGSD. Journal of Physics: Conference Series, 1764(1), 012124. https://doi.org/10.1088/1742-6596/1764/1/012124

  16. Hashim, H., & Tasir, Z. (2014, 11-13 April 2014). E-learning readiness: A literature review. In 2014 International Conference on Teaching and Learning in Computing and Engineering. https://doi.org/10.1109/LaTiCE.2014.58

  17. Hidayat, W., & Sumarmo, U. (2013). Kemampuan komunikasi dan berpikir logis matematika serta kemandirian belajar [Communication skills and mathematical logical thinking as well as learning independence]. Delta-Pi: Jurnal Matematika dan Pendidikan Matematika, 2(1), 1-14.

  18. Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080-1090. https://doi.org/10.1016/j.compedu.2010.05.004

  19. Hutajulu, M. (2022). The effectiveness of using Google Meet In online learning to improve mathematical communication skills. (JIML) Journal of Innovative Mathematics Learning, 5(1), 53-61.

  20. Hwang, W.-Y., Chen, N.-S., & Hsu, R.-L. (2006). Development and evaluation of multimedia whiteboard system for improving mathematical problem solving. Computers & Education, 46(2), 105-121. https://doi.org/10.1016/j.compedu.2004.05.005

  21. Irfan, M., Kusumaningrum, B., Yulia, Y., & Widodo, S. A. (2020). Challenges during the pandemic: use of e-learning in mathematics learning in higher education. Infinity Journal, 9(2), 147-158. https://doi.org/10.22460/infinity.v9i2.p147-158

  22. Johnson, E. L., & Green, K. H. (2007). Promoting mathematical communication and community via blackboard. PRIMUS, 17(4), 325-337. https://doi.org/10.1080/10511970601131563

  23. Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654-1664. https://doi.org/10.1016/j.compedu.2011.02.008

  24. Joosten, T., & Cusatis, R. (2020). Online learning readiness. American Journal of Distance Education, 34(3), 180-193. https://doi.org/10.1080/08923647.2020.1726167

  25. Kosko, K. W., & Gao, Y. (2017). Mathematical communication in state standards before the common core. Educational Policy, 31(3), 275-302. https://doi.org/10.1177/0895904815595723

  26. Kosko, K. W., & Wilkins, J. L. (2010). Mathematical communication and its relation to the frequency of manipulative use. International Electronic Journal of Mathematics Education, 5(2), 79-90. https://doi.org/10.29333/iejme/251

  27. Ledbetter, A. M. (2009). Measuring online communication attitude: Instrument development and validation. Communication Monographs, 76(4), 463-486. https://doi.org/10.1080/03637750903300262

  28. Ledbetter, A. M. (2014). Online communication attitude similarity in romantic dyads: Predicting couples' frequency of e-mail, instant messaging, and social networking site communication. Communication Quarterly, 62(2), 233-252. https://doi.org/10.1080/01463373.2014.890120

  29. Lee, J., Lee, H. J., Song, J., & Bong, M. (2021). Enhancing children's math motivation with a joint intervention on mindset and gender stereotypes. Learning and Instruction, 73, 101416. https://doi.org/10.1016/j.learninstruc.2020.101416

  30. Lee, S. J., Srinivasan, S., Trail, T., Lewis, D., & Lopez, S. (2011). Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning. The Internet and Higher Education, 14(3), 158-163. https://doi.org/10.1016/j.iheduc.2011.04.001

  31. Loch, B., Gill, O., & Croft, T. (2011). Complementing mathematics support with online MathsCasts. ANZIAM Journal, 53, C561-C575. https://doi.org/10.21914/anziamj.v53i0.4984

  32. Lomibao, L. S., Luna, C. A., & Namoco, R. A. (2016). The influence of mathematical communication on students’ mathematics performance and anxiety. American Journal of Educational Research, 4(5), 378-382.

  33. López Meneses, E., Vázquez Cano, E., & Mac Fadden, I. (2020). MOOC in higher education from the students’ perspective. A sustainable model? In J. L. Sarasola Sánchez-Serrano, F. Maturo, & Š. Hošková-Mayerová (Eds.), Qualitative and Quantitative Models in Socio-Economic Systems and Social Work (pp. 207-223). Springer International Publishing. https://doi.org/10.1007/978-3-030-18593-0_17

  34. Ma, L., & Lee, C. S. (2019). Investigating the adoption of MOOCs: A technology–user–environment perspective. Journal of Computer Assisted Learning, 35(1), 89-98. https://doi.org/10.1111/jcal.12314

  35. Mazer, J. P., & Ledbetter, A. M. (2012). Online communication attitudes as predictors of problematic internet use and well-being outcomes. Southern Communication Journal, 77(5), 403-419. https://doi.org/10.1080/1041794X.2012.686558

  36. McSporran, M., & Young, S. (1969). Does gender matter in online learning? Research in Learning Technology, 9(2), 3-15. https://doi.org/10.3402/rlt.v9i2.12024

  37. Mseleku, Z. (2020). A literature review of e-learning and e-teaching in the era of COVID-19 pandemic. International Journal of Innovative Science and Research Technology, 5(10), 588-597.

  38. Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26(1), 29-48. https://doi.org/10.1080/01587910500081269

  39. Okoye, K., Hussein, H., Arrona-Palacios, A., Quintero, H. N., Ortega, L. O. P., Sanchez, A. L., Ortiz, E. A., Escamilla, J., & Hosseini, S. (2022). Impact of digital technologies upon teaching and learning in higher education in Latin America: an outlook on the reach, barriers, and bottlenecks. Education and Information Technologies, 28(2), 2291-2360. https://doi.org/10.1007/s10639-022-11214-1

  40. Olayemi, O. M., Adamu, H., & Olayemi, K. (2021). Perception and readiness of students’ towards online learning in Nigeria during Covid-19 pandemic. Perception, 3(1), 4-21.

  41. Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 7. https://doi.org/10.1186/s41239-019-0136-3

  42. Ramírez-Correa, P. E., Arenas-Gaitán, J., & Rondán-Cataluña, F. J. (2015). Gender and acceptance of e-learning: A multi-group analysis based on a structural equation model among college students in Chile and Spain. PLoS One, 10(10), e0140460. https://doi.org/10.1371/journal.pone.0140460

  43. Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701

  44. Retnawati, H. (2016). Analisis kuantitatif instrumen penelitian (panduan peneliti, mahasiswa, dan psikometrian) [Quantitative analysis of research instruments (researchers' guides, students, and psychometricians)]. Yogyakarta: Parama Publishing.

  45. Rohayani, A. H. H., Kurniabudi, K., & Sharipuddin, S. (2015). A literature review: Readiness factors to measuring e-learning readiness in higher education. Procedia Computer Science, 59, 230-234. https://doi.org/10.1016/j.procs.2015.07.564

  46. Silver, E. A., & Cai, J. (1996). An analysis of arithmetic problem posing by middle school students. Journal for Research in Mathematics Education, 27(5), 521-539. https://doi.org/10.5951/jresematheduc.27.5.0521

  47. Smith, P. J., Murphy, K. L., & Mahoney, S. E. (2003). Towards identifying factors underlying readiness for online learning: An exploratory study. Distance Education, 24(1), 57-67. https://doi.org/10.1080/01587910303043

  48. Steiner, G. (1997). Educational Learning Theory. In S. Dijkstra, F. Schott, N. Seel, R. D. Tennyson, & N. M. Seel (Eds.), Instructional Design: International Perspectives I. New York: Routledge. https://doi.org/10.4324/9780203062920

  49. Szopiński, T., & Bachnik, K. (2022). Student evaluation of online learning during the COVID-19 pandemic. Technological Forecasting and Social Change, 174, 121203. https://doi.org/10.1016/j.techfore.2021.121203

  50. Taskin, N., & Erzurumlu, K. (2021). Investigation into online learning readiness of higher education students during COVID-19 pandemic. Malaysian Online Journal of Educational Technology, 9(3), 24-39.

  51. Tong, D. H., Uyen, B. P., & Van Anh Quoc, N. (2021). The improvement of 10th students' mathematical communication skills through learning ellipse topics. Heliyon, 7(11), e08282. https://doi.org/10.1016/j.heliyon.2021.e08282

  52. Trenholm, S., & Peschke, J. (2020). Teaching undergraduate mathematics fully online: a review from the perspective of communities of practice. International Journal of Educational Technology in Higher Education, 17(1), 37. https://doi.org/10.1186/s41239-020-00215-0

  53. Volery, T., & Lord, D. (2000). Critical success factors in online education. International Journal of Educational Management, 14(5), 216-223. https://doi.org/10.1108/09513540010344731

  54. Watson, R. (1998). Rethinking readiness for learning. In The Handbook of Education and Human Development (pp. 145-167). https://doi.org/10.1111/b.9780631211860.1998.00009.x

  55. Wawan, W. (2020). Teknik analisa data penelitian pendidikan [Educational research data analysis techniques]. Yogyakarta: UNY Press.