Undergraduate Students’ Financial Condition, Mental Health, Remote Class Participation, and Perceived School Support during COVID–19
Policymakers, educators, and scholars are concerned with the extent to which educational inequality is worsened when schools are locked down during the COVID–19 pandemic. In this paper, we ask how school closures affect economically disadvantaged students, and whether there are variations in school support across different types (or tiers) of tertiary educational institutions in Taiwan. More specifically, we address how 1) students’ economic background, 2) the type/tier of schools in which they are enrolled, and 3) the cross-level interaction between these two factors were associated with the probability of perceived school-level support and resources in response to the lockdown period between May and June 2021. Our analyses are based on data from 5,904 undergraduate students across 92 universities and colleges who participated in an online survey in July 2021. We employ multilevel linear probability modeling (LPM), due to the hierarchical nature of the data, as students (Level 1) are nested within schools (Level 2). Because the data are from a nonprobability sample, we apply model-based weighting in the analyses, calculated by the Stata command “svywt” (Valliant and Dever 2018). Our focus is on comparing the differences between five types of schools, namely top universities, public four-year universities, private four-year universities, public technical colleges, and private technical colleges. Top universities refers to the 11 schools that received hundreds of millions of NT dollars in funding from the Ministry of Education to promote academic excellence in higher education between 2011 and 2015. We argue that tertiary educational institutions are highly stratified by school type, mainly because the expansion of higher education in Taiwan in the 2000’s had been too rapid and rushed, thereby creating a crisis for lower-ranked schools that experienced a lack of funds and shortage of educational resources. This problem had existed long before COVID–19 arrived in Taiwan and has been worsened during the epidemic.There are several notable findings. First, when COVID–19 cases were surging and campuses were locked down during the studied period, students from lower income backgrounds were more likely to apply for financial aid than those from higher income backgrounds. Additionally, the level of mental stress increased among these economically underprivileged undergraduates when they sensed that their family financial condition became worse due to the pandemic. Second, in line with previous literature, we find that economically underprivileged undergraduates were less likely to enroll in higher-ranked universities in Taiwan. Third, our findings also reveal significant cross-level interactions between students’ income economic background (LV1) and school type (LV2). During the school lockdown, for instance, economically underprivileged undergraduates attending top universities were more likely to perceive their schools as having various online consultation services, such as career counseling and psychological counseling, compared to other economically underprivileged undergraduates who attended other types of schools. Interestingly, economically privileged undergraduates attending public four-year universities were more likely to report that their schools provided similar consultation services than their less privileged counterparts. Fourth, in comparison with economically more privileged undergraduates, less privileged undergraduates were less likely to report that their schools had provided enough e-learning resources or adequate remote teaching support. More importantly, this problem was more pronounced in public schools—especially among top universities—than in private schools. This suggests a larger e-learning gap by family income within top universities. Fifth, private technical colleges, compared to other types of schools, provided less in the way of remote services or educational support during the school lockdown, although the within-school e-learning gap by family income was smaller among this type of school. In the conclusion, we further discuss these findings and other important implications of our research.