22. Research in Higher Education
Paper
Impacts of Class Size on Students’ Learning Outcomes in College Online Courses
Xuehan Zhou1, Liping Ma1, Xiaohao Ding1, Changjun Yue1, Suhong Yang2, Yajing Xu1
1Peking University, China, People's Republic of; 2Central University of Finance and Economics
Presenting Author: Ma, Liping
Synchronous online courses gained popularity during the pandemic and have since become the predominant course delivery format for online courses due to their ability to reduce educational cost while preserving real-time communication and immediate feedback (Bailenson, 2021). The rapid growth of synchronous course prompts questions about improving the quality of online courses at scale (Bettinger et al., 2017; Lowenthal et al., 2019; Russell & Curtis, 2013; Xu & Xu, 2020).. One area of intense debate in this context is the role of class size in online courses. However, limited research has quantitatively examined the effects of class size on student learning outcomes in college synchronous online courses. Assessing these effects is a pertinent issue: If increasing class size in synchronous online courses does not compromise student learning outcomes, it opens up the possibility for departments to consider offering larger synchronous online classes. This approach could help reduce educational costs and enhance accessibility without sacrificing student engagement.
This study addresses this gap by answering three main research questions. First, what is the impact of class size on students’ academic performance and course satisfaction? Second, what are the mechanisms through which class size effects operate? Third, how do class size effects vary along the distribution of class sizes (Non-linear effects)?
We analyzed data from an anonymous research university (ARU hereafter) in China. Due to the COVID-19 pandemic, all courses in the spring semester of 2020 in ARU were delivered online synchronously, with approximately 82% delivered via ClassIn, which was a popular platform for online course delivery in China at the time. This study focused on undergraduate students enrolled in synchronous online courses for the duration of the semester. Furthermore, this study examined courses categorized as “lecture” sections, excluding physical education and lab courses. As a result, our sample comprised 6,603 undergraduate students enrolled in one of the 638 synchronous online classes offered by 30 departments. We obtained data from two sources: (1) administrative data, which includes students’ and instructors’ demographic characteristics, class enrollment size, students’ academic performance, and instructors’ teaching evaluation, etc., and (2) clickstream data generated by the ClassIn platform, which captured information such as the length of time students were assigned to interact with their peers and instructors, as well as their time spent in the virtual classroom.
We began by estimating the effects of class size on students’ academic outcomes and course satisfaction. Our analyses indicate that class sizes negatively affect course grades and course satisfaction in synchronous online courses. Drawing on the rich clickstream information generated by the online platform, we examined two channels through which class size effects may operate: (i) students’ course attendance and (iii) course interaction opportunities. Our findings suggest that reduced course interaction opportunity is the most robust channel through which larger classes negatively affect students’ academic outcomes and course satisfaction. In addition, we explore non-linearities in the class size effect and heterogeneity by students’ academic preparation, grade level, and course credits. Our findings indicate a consistent negative effect across the entire spectrum of class sizes, with larger class sizes exhibiting increasingly detrimental effects. We also found that the negative relationship between class size and student outcomes is highly robust across different types of students.
Methodology, Methods, Research Instruments or Sources UsedWe analyzed the effects of class size on students’ outcomes, using within-student variation in class sizes:
yicm= αi + βm + γCScm + δXcm + θPcm + φTcm + εicm (1)
where yicm is an outcome, such as course grade for student i in class c in department m. αi represents student fixed effect, which allows for comparisons among different classes taken by the same student, thereby mitigating bias associated with students’ self-section into different classes. βm represents department fixed effects, enabling comparisons among different classes within the same field of study. CScm captures the class size in class c of department m, defined by the number of students enrolled in the classes and the average number of students presenting in the class over the semester. Xcm represents control variables on class c in department m, such as course credits and course classifications. To account for the peer group composition within a class, we controlled for Pcm, including the share of male students, the proportion of students with average grade points in the lowest quartile, and the proportion of seniors. Tcm captures the characteristics of teachers in a course, such as their gender, job title, age, educational attainment, etc. However, considering that more than one faculty member can teach a class, the term Tcm represents the faculty composition of class c. This term includes the number of faculty involved in teaching the particular class, the proportion of male faculty, the proportion of professors, the ratio of overseas returning faculty, the average age of teachers, and the average teacher evaluation score. Finally, the error term εicm was clustered by course to capture common unobservable shocks to students’ outcome variables.
We further calculated the implied effect size. The measure estimates the proportion of the within-student standard deviation in outcome variables that can be explained by a one standard deviation increase from the mean class size.
We then examined whether there were any nonlinear class size effects using Equation (2). To do so, we categorized students into four quantiles based on the distributions of both class enrollment sizes and actual class sizes.
yicm= αi + βm + ∑ γqCSqcm + δXcm + θPcm + φTcm + εicm (2)
where CSqcm equals to one if the class size is in the qth quantile of class size distribution, and zero otherwise.
Conclusions, Expected Outcomes or FindingsThere is robust evidence of a negative class size effect on students’ academic achievement. Our study also revealed evidence of nonlinear class size effects on course grades in synchronous online courses. Specifically, we observed a negative impact between the first two quantiles and the last two quantiles. The results indicate that there were beneficial effects when moving both from mid-sized to smaller classes and from the very large to large classes.
Our analysis also sheds light on the negative impact of class sizes on student course satisfaction. Unlike the nonlinear effects observed on course grades, the impact on course satisfaction showed a distinct pattern. It became more significant when moving from the first to the second quantile (class sizes ranging from 2 to 15 students and 16 to 24 students). However, there seems to be no further detrimental effect when moving from the second to the third quantile or from the third to the fourth quantile. Therefore, it appears that the class size range of 16 to 24 students was where the negative class size effect on course satisfaction reached its highest magnitude.
In terms of the mechanisms, our findings suggest that, on average, class size did not have a significant association with class attendance. However, we did observe nonlinear effects where the course attendance rate began to decline when class sizes exceeded 24 students. Additionally, we consistently observed notable negative correlations between class size and student course interaction opportunities. In conclusion, our study highlighted the importance of considering class size as a factor influencing student attendance and course interaction opportunities.
ReferencesBettinger, E. P., Fox, L., Loeb, S., & Taylor, E. S. (2017). Virtual Classrooms: How Online College Courses Affect Student Success. American Economic Review, 107(9), 2855–2875. https://doi.org/10.1257/aer.20151193
Lowenthal, P. R., Nyland, R., Jung, E., Dunlap, J. C., & Kepka, J. (2019). Does class size matter?: An exploration into faculty perceptions of teaching high-enrollment online courses. American Journal of Distance Education, 33(3), 152–168. https://doi.org/10.1080/08923647.2019.1610262
Russell, V., & Curtis, W. (2013). Comparing a large- and small-scale online language course: An examination of teacher and learner perceptions. The Internet and Higher Education, 16, 1–13. https://doi.org/10.1016/j.iheduc.2012.07.002
Xu, D., & Xu, Y. (2020). The ambivalence about distance learning in higher education: Challenges, opportunities, and policy implications. In L. W. Perna (Ed.), Higher Education: Handbook of Theory and Research (Vol. 35, pp. 351–401). Springer International Publishing. https://doi.org/10.1007/978-3-030-31365-4_10
22. Research in Higher Education
Paper
Metaphorical Conceptualizations of Undergraduate Students during Uncertain Times: Insights from an International Higher Education Institution
Leyla Silman-Karanfil, Iclal Can
Middle East Technical University Northern Cyprus Campus
Presenting Author: Silman-Karanfil, Leyla
Although much has been written on emergency remote teaching occasioned by the circulation of the COVID-19 virus around the world, existing studies tend to hold a somewhat single-dimensional perspective by paying attention solemnly in the initial stages of the pandemic or the post-pandemic period when education started to “normalize”. Moreover, directing more attention towards the unprecedented factor of the situation, existing studies seem to overlook the extent to which students were prepared for education during unexpected pandemics, wars, natural disasters, such as earthquakes, or navigating ethical concerns raised by generative AI, creating blind spots where higher education institutions are not critically evaluated. Departing from this premise, our paper puts a spotlight on the problematic nature of the COVID-19 pandemic and its implications for higher education as a vantage point.
To gain an in-depth understanding of how COVID-19 affected instruction so far and what it brought with it, we believe there is a need to consider both periods (switching to ERT and reverting to face-to-face) simultaneously. Considering the current wars and the possible outbreak of a similar pandemic where education has and might be disrupted again, it becomes much more important to conduct research in this area utilizing metaphorical images that students use to conceptualize themselves during online teaching and face to face teaching. Metaphors are useful in gaining a nuanced understanding of students’ experiences as they offer insight into the process participants go through by providing a conceptual framework through which we can perceive and interpret their experiences in relation to other familiar concepts or ideas (Saban, 2010). Moreover, metaphors can be used for reflection (e.g. Lynch & Fisher-Ari, 2017) as they are a powerful means to reify previous experiences (Zhao, Coombs & Zhou, 2010) or to explore participants' cognition, including identities (e.g. Thomas & Beauchamp, 2011) beliefs (Ulusoy, 2022), as well as experiences (e.g. Craig, 2018) because they not only add a new perspective, generate a discussion of a certain topic (Saban, 2010), also “tease out connections which might not be made use of by direct questions” (Leavy, McSorley, & Bote, 2007, p. 1220).
In this study, we captured undergraduate students’ metaphorical conceptualizations of themselves during COVID-19 not only during online teaching but also in times of face-to-face teaching periods while the pandemic was ongoing. By exerting attention towards understanding university students' cognitive constructs through the use of metaphors, it is hoped that the study will help university students situate their learning context, in this case, ERT, and switch back face-to-face into their own reality. In this sense, it will also guide educators and teacher trainers in designing programs to support university students' learning process and help them be ready for similar scenarios. The findings from this study will also build upon the growing literature on ERT within an international higher education English Medium University (EMI) context and thus shed light on perceptions and needs of undergraduate students particularly during uncertain times and new steps to be taken in designing effective educational programs.With this in the background, the following research questions were developed according to Saban’s (2010) metaphor research question structure:
-
What metaphorical images do undergraduate students use to describe students during the COVID-19 (a) online teaching period and (b) face-to-face teaching period?
-
What are the conceptual themes derived from the metaphorical images regarding undergraduate students’ concept of students during the COVID-19 (a) online teaching period and (b) face-to-face teaching period?
-
Which factors affect undergraduate students’ conceptualizations of undergraduate students during the COVID-19 (a) online teaching period and (b) face-to-face teaching period?
-
What are the implications for online teaching and face-to-face teaching periods during uncertain times?
Methodology, Methods, Research Instruments or Sources UsedWe collected the data using two metaphor-generation method prompts. We developed the prompts in English using Saban, Kocbeker, and Saban’s (2007) metaphor-generation method. We then revised and modified the writing prompts based on expert opinion from three faculty members. Our prompts were:
An undergraduate student during the COVID-19 online teaching period is like…because…
An undergraduate student during the COVID-19 face-to-face teaching period is like...because…
We conducted our study on the North Cyprus campus of an internationally recognized English-medium university located in Turkey. We sent an invitation email to all undergraduate students in the university. The email included information about our study and a link to the Google form we developed to collect the data. The form included three parts: (a) an informed consent form approved by the University’s Ethics committee, (b) demographic questions (i.e., gender, age, major, class level, and nationality, as well as accommodation status while attending online classes during ERT) and (c) the metaphor prompts. Undergraduate students who agreed to participate in the study responded to the questions anonymously. The data collection lasted around three weeks.
We ended up with 114 well-formed metaphors from undergraduate students from different year groups (76 male 37 female and 1 non-binary) enrolled in different programs, including Economics and Administrative Sciences, Education and Humanities, and Engineering programs. 87 participants were Turkish and Turkish Cypriots and 27 were international students. International students were from Azerbaijan (n=3), Kenya (n=4), Bangladesh (n=1), Egypt (n=2), India (n=1), Kazakhstan (n=2), Nigeria (n=4), Pakistan (n=5), RW (n=1), United Arab Emirates (n=1), Saudi Arabia (n=1), and Syria (n=1). One participant did not prefer to share citizenship information. Participants’ ages ranged between 17 and 28 years.
Data was exposed to inductive content analysis. We coded the participants' metaphorical images in their responses for each metaphor prompt (e.g., fish in an aquarium, prisoner). We eliminated the student responses that included a metaphorical image without metaphorical reasoning as recommended by Saban (2010), and that did not include a metaphor but general views about students or education during the pandemic (e.g., An undergraduate student during the Covid-19 online teaching period is depressed and hopeless because it was awful not to know when we will go to the campus). We double-coded the data to categorize the codes under the themes and eliminate overlapping and redundant codes (Creswell, 2011).
Conclusions, Expected Outcomes or FindingsThe results revealed three major themes regarding students’ conceptualizations of themselves during the COVID-19 online teaching period: (a) students as absolute complaints (among some representative metaphorical images were a prisoner, being trapped in an untidy room, fish in an aquarium, wings of a hummingbird trapped in a slow dream); (b) students as controllers of their own learning (among some representative metaphorical images were someone in heaven, a time controller, and an artist in an album zone); and (c) students as overwhelmed beings (among some representative metaphorical images were torture, fish out of the pond, punching a wall, and fitting everything in a room).
The results revealed three major themes regarding students’ conceptualizations of students during the COVID-19 face-to-face teaching period: (a) Students enjoying a long-awaited reunion (among some representative metaphorical images were having undergone a beautiful struggle, watching a slow-moving river, drinking cold water in a hot summer); (b) students experiencing discomfort (among some representative metaphorical images were a beast in a struggle, nightmare, a teenager navigating high school, and torture); and (c) students with mixed experiences (among some representative metaphorical images were astronaut returning to earth from space, and being a stranger).
Our results showed that students’ major, class level, and where they lived while attending online classes may have influenced their metaphorical images during COVID-19 online and face-to-face instruction. Although conducted with a small sample size, this study has important implications for fostering student resilience and sustainability of education during uncertain times. Our results suggest that undergraduate students need their voices to be heard. In occasions such as emergencies where new policies need to be implemented, it is necessary to include undergraduate students in the decision-making process. Educators need to revisit their teaching practices and adapt them according to students’ current needs particularly during emergent times.
ReferencesCraig, C. J. (2018). Metaphors of knowing, doing and being: Capturing experience in teaching and teacher education. Teaching and Teacher Education, 69, 300-311.doi.org/10.1016/j.tate.2017.09.011
Creswell, J. W. (2011). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson Education.
Leavy, A. M., McSorley, F. A., & Boté, L. A. (2007). An examination of what metaphor construction reveals about the evolution of preservice teachers’ beliefs about teaching and learning. Teaching and teacher education, 23(7), 1217-1233.doi.org/10.1016/j.tate.2006.07.016
Lynch, H. L., & Fisher-Ari, T. R. (2017). Metaphor as pedagogy in teacher education. Teaching and Teacher Education, 66, 195-203.doi.org/10.1016/j.tate.2017.03.021
Saban, A., Kocbeker, B. N., & Saban, A. (2007). Prospective teachers' conceptions of teaching and learning revealed through metaphor analysis, Learning and Instruction, 17(2), 123-139. doi.org/10.1016/j.learninstruc.2007.01.003
Saban, A. (2010). Prospective teachers' metaphorical conceptualizations of learner. Teaching and Teacher Education, 26 (2), 290-305. doi.org/10.1016/j.tate.2009.03.017
Thomas, L., & Beauchamp, C. (2011). Understanding new teachers’ professional identities through metaphor. Teaching and teacher Education, 27(4), 762-769.doi.org/10.1016/j.tate.2010.12.007
Ulusoy, M. (2022). A metaphorical journey from pre-service to in-service years: A longitudinal study of the concepts of the student and the teacher. Teaching and Teacher Education, 115, 103726. doi.org/10.1016/j.tate.2022.103726
Zhao, H., Coombs, S., & Zhou, X. (2010). Developing professional knowledge about teachers through metaphor research: Facilitating a process of change. Teacher Development, 14(3), 381-395.doi.org/10.1080/13664530.2010.504024
|
