Memorization and Performance During Pandemic Remote Instruction: Evidence of Shifts from an Interactive Textbook

Authors

  • Jose L Salas California State University, Los Angeles
  • Xinran Wendy Wang University of California, Los Angeles
  • Mary C Tucker University of California, Los Angeles
  • Ji Y Son California State University, Los Angeles

DOI:

https://doi.org/10.24059/olj.v28i2.3435

Keywords:

Memorization beliefs, COVID-19, academic institution, academic performance, in-person instruction, fully remote instruction

Abstract

Students believe mathematics is best learned by memorization; however, endorsing memorization as a study strategy is associated with worse learning (Schoenfeld, 1989). When the world changed with the onset of the COVID-19 global pandemic, instruction transitioned to fully remote instruction where many assignments and examinations became open-textbook, open-note, and even open-internet. In this new world, did students change their beliefs about the role of memorization in learning? Did academic performance change? And did the relationship between memorization beliefs and academic performance change? The current study takes advantage of data (N = 2668) collected in an online interactive statistics textbook used by courses before (in-person) and after (remote) the declaration of the COVID-19 pandemic at three institutions, each representing a part of the California Master Plan for Higher Education (e.g., University of California, California State University, and California Community Colleges). Results showed that the UC institution had lower memorization belief scores compared to both the CSU and CCC institutions. Even when controlling for institution and chapter of the textbook, lower memorization belief scores were related to higher performance. Surprisingly, there were no significant differences in either memorization beliefs nor performance pre- and post-declaration of the pandemic. Although much of educational research is conducted in one institution, this kind of research can identify differences across institutional contexts to understand how learning can be affected by disruptive social changes such as a global pandemic.

References

Barber, P. H., Shapiro, C., Jacobs, M. S., Avilez, L., Brenner, K. I., Cabral, C., Cebreros, M., Cosentino, E., Cross, C., Gonzalez, M. L., Lumada, K. T., Menjivar, A. T., Narvaez, J., Olmeda, B., Phelan, R., Purdy, D., Salam, S., Serrano, L., Velasco, M. J., … Levis-Fitzgerald, M. (2021). Disparities in remote learning faced by first-generation and underrepresented minority students during COVID-19: Insights and opportunities from a remote research experience. Journal of Microbiology & Biology Education, 22(1). https://doi.org/10.1128/jmbe.v22i1.2457

Boaler, J., Wiliam, D., & Brown, M. (2000). Students' experiences of ability grouping—disaffection, polarisation and the construction of failure 1. British Educational Research Journal, 26(5), 631-648. https://doi.org/10.1080/713651583

Bombardieri, M. (2021, April 15). Covid-19 changed education in America permanently. Politico. https://www.politico.com/news/2021/04/15/covid-changed-education-permanently-479317

Boniface, D. (1985). Candidates' use of notes and textbooks during an open-book examination. Educational Research, 27(3), 201–209.

https://doi.org/10.1080/0013188850270307

Block, R. M. (2012) A discussion of the effect of open-book and closed-book exams on student achievement in an introductory statistics course, PRIMUS, 22(3), 228-238. https://doi.org/10.1080/10511970.2011.565402

Broyles, I. L., Cyr, P. R., & Korsen, N. (2005). Open book tests: assessment of academic learning in clerkships. Medical Teacher, 27(5), 456–462.

https://doi.org/10.1080/01421590500097075

Cinelli, C., Forney, A., & Pearl, J. (2022). A crash course in good and bad controls. Technical Report R-493. http://dx.doi.org/10.2139/ssrn.3689437

Crawford, K., Gordon, S., Nicholas, J., & Prosser, M. (1994). Conceptions of mathematics and how it is learned: The perspectives of students entering university. Learning and Instruction, 4(4), 331-345. https://doi.org/10.1016/0959-4752(94)90005-1

Daniel, J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1), 91-96. https://doi.org/10.1007/s11125-020-09464-3

Deng, X. N., & Yang, Z. (2021). Digital proficiency and psychological well-being in online learning: Experiences of first-generation college students and their peers. Social Sciences, 10(6). https://doi.org/10.3390/socsci10060192

Er, H.M., Nadarajah, V. D., Wong, P. S., Mitra, N. K., & Ibrahim, Z. (2021). Practical considerations for online open book examinations in remote settings [Version 2]. MedEdPublish, 9(1). https://doi.org/10.15694/mep.2020.000153.2

Engzell, P., Frey, A., & Verhagen, M. D. (2021). Learning loss due to school closures during the COVID-19 pandemic. Proceedings of the National Academy of Sciences, 118(17). https://doi.org/10.1073/pnas.2022376118

Esquivel, P. & Lee, R. (2021, October 21). Falling grades, stalled learning. L.A. students ‘need help now,’ Times analysis shows. Los Angeles Times.

https://www.latimes.com/california/story/2021-10-21/covid-era-learning-challenges-lausd-after-school-closures

George, D. S., Strauss, V., Meckler, L., Heim, J., & Natanson, H. (2021, March 15). How the pandemic is reshaping education. The Washington Post. https://www.washingtonpost.com/education/2021/03/15/pandemic-school-year-changes/

Givvin, K. B., Stigler, J. W., & Thompson, B. J. (2011) What community college developmental mathematics students understand about mathematics, Part II: The interviews. The MathAMATYC Educator, 2(3), 4-18. https://www.researchgate.net/publication/260908914_What_community_college_developmental_mathematics_students_understand_about_mathematics_Part_II_The_interviews

Goan, S. K., & Cunningham, A. F. (2007). Differential characteristics of 2-year postsecondary institutions (NCES 2007-164rev). Washington, DC: U.S. Department of Education., National Center for Education Statistics.

https://nces.ed.gov/pubs2007/2007164rev.pdf

Goudeau, S., Sanrey, C., Stanczak, A., Manstead, A., & Darnon, C. (2021). Why lockdown and distance learning during the COVID-19 pandemic are likely to increase the social class achievement gap. Nature human behaviour, 5(10), 1273-1281. https://doi.org/10.1038/s41562-021-01212-7

Gray, K. E., Adams, W. K., Wieman, C. E., & Perkins, K. K. (2008). Students know what physicists believe, but they don’t agree: A study using the CLASS survey. Physical Review Special Topics. Physics Education Research, 4(2). https://doi.org/10.1103/PhysRevSTPER.4.020106

House, J. D. (2006). Mathematics beliefs and achievement of elementary school students in Japan and the United States: Results from the Third International Mathematics and Science Study. The Journal of genetic psychology, 167(1), 31-45. https://doi.org/10.3200/GNTP.167.1.31-45

Le, A., Joordens, S., Chrysostomou, S., & Grinnell, R. (2010). Online lecture

accessibility and its influence on performance in skills-based courses. Computers and Education, 55(1), 313–319. https://doi.org/10.1016/j.compedu.2010.01.017

Lin, S. W., & Tai, W. C. (2015). Latent class analysis of students' mathematics learning strategies and the relationship between learning strategy and mathematical literacy. Universal Journal of Educational Research, 3(6), 390-395. https://doi.org/10.13189/ujer.2015.030606

Mesa, V., Wladis, C., & Watkins, L. (2014). Research problems in community college mathematics education: Testing the boundaries of K—12 research. Journal for Research in Mathematics Education, 45(2), 173–192. https://doi.org/10.5951/jresematheduc.45.2.0173

Myyry, L., & Joutsenvirta, T. (2015). Open-book, open-web online examinations: Developing examination practices to support university students’ learning and self-efficacy. Active Learning in Higher Education, 16(2), 119–132. https://doi.org/10.1177/1469787415574053

Nickerson, L.A., & Shea, K. M. (2020). First-semester organic chemistry during COVID-19: Prioritizing group work, flexibility, and student engagement. Journal of Chemical Education, 97(9), 3201–3205. https://doi.org/10.1021/acs.jchemed.0c00674

Phelps-Gregory, C. M., Frank, M., & Spitzer, S. M. (2020). Prospective elementary teachers’ beliefs about mathematical myths: a historical and qualitative examination. The Teacher Educator, 55(1), 6-27.

https://doi.org/10.1080/08878730.2019.1618423

Pokhrel, S. & Chhetri, R. (2021). A literature review on impact of COVID-19 Pandemic on teaching and learning. Higher Education for the Future, 8(1), 133–141. https://doi.org/10.1177/2347631120983481

Public Policy Institute of California Higher Education Center (2017). Higher Education in California. https://www.ppic.org/wp-content/uploads/r_0917hebkr.pdf

Redish, E. F., Saul, J. M., & Steinberg, R. N. (1998). Student expectations in introductory physics. American Journal of Physics, 66(3), 212–224. https://doi.org/10.1119/1.18847

Schoenfeld, A. H. (1989). Explorations of students' mathematical beliefs and behavior. Journal for Research in Mathematics Education, 20(4), 338–355. https://doi.org/10.2307/749440

Songer, N. B., & Linn, M. C. (1991). How do students' views of science influence knowledge integration? Journal of Research in Science Teaching, 28(9), 761–784. https://doi.org/10.1002/tea.3660280905

Soria, K.M., Horgos, B., Chirikov, I., & Jones-White, D. (2020). First-generation students’ experiences during the COVID-19 pandemic. SERU Consortium, University of California -Berkeley and University of Minnesota. https://escholarship.org/uc/item/19d5c0ht

Stigler, J. W., Givvin, K. B., & Thompson, B. J. (2010) What community college developmental mathematics students understand about mathematics. The MathAMATYC Educator, 1(3), 4-16.

Stigler, J. W., Son, J. Y., Givvin, K. B., Blake, A. B., Fries, L., Shaw, S. T., & Tucker, M. C. (2020). The better book approach for education research and development. Teachers College Record, 122(9), 1–32.

https://doi.org/10.1177/016146812012200913

Son, J. Y., & Stigler, J. W. (2016-21), “Statistics and Data Science: A Modeling Approach” https://coursekata.org/preview/default/program

Sutter, C. C., Hulleman, C. S., Givvin, K. B., & Tucker, M. (2022). Utility value trajectories and their relationship with behavioral engagement and performance in introductory statistics. Learning and Individual Differences, 93, 102095. https://doi.org/10.1016/j.lindif.2021.102095

Theophilides, C., & Dionysiou, O. (1996). The major functions of the open-book

examination at the university level: A factor analytic study. Studies in

Educational Evaluation, 22(2), 157–170.

https://doi.org/10.1016/0191-491X(96)00009-0

Tucker, C. M., Shaw, S. T., Son, J. Y., & Stigler, J. W. (under review). Teaching

statistics and data analysis with R. Journal of Statistics and Data Science

Education.

University of California Office of the President. (n.d.). California master plan for higher education. https://www.ucop.edu/institutional-research-academic-planning/content-analysis/academic-planning/california-master-plan.html

US News. (2022a). Los Angeles Pierce College. https://www.usnews.com/education/community-colleges/los-angeles-pierce-college-CC04814

US News. (2022b). California State University--Los Angeles.

https://www.usnews.com/best-colleges/california-state-university-los-angeles-1140

US News. (2022c). University of California--Los Angeles.

https://www.usnews.com/best-colleges/university-of-california-los-angeles-1315

Weber, L. J., McBee, J. K., & Krebs, J. E. (1983). Take home tests: An experimental

study. Research in Higher Education, 18(4), 473–483. https://doi.org/10.1007/BF00974810

Winthrop, R. (2020, April 10). Top 10 risks and opportunities for education in the face

of COVID-19. Brookings. https://www.brookings.edu/blog/education-plus-development/2020/04/10/top-10-risks-and-opportunities-for-education-in-the-face-of-covid-19/

Wheeler, D. L., & Montgomery, D. (2009). Community college students’ views on

learning mathematics in terms of their epistemological beliefs: a Q method study.

Educational Studies in Mathematics, 72(3), 289-306.

https://doi.org/10.1007/s10649-009-9192-2

Downloads

Published

2024-06-01