In my capstone project, I investigated the impact of COVID-19 on education. Using data analysis and statistical methods, I explored various aspects such as enrollment trends, access to resources, and socioeconomic disparities. I found a significant association between children missing classes and a lack of internet connection at home, as well as between household financial situations and children's enrollment in school. These findings highlight the importance of addressing disparities in internet access, household finances, and geographical location to ensure equal educational opportunities for all students during and beyond the pandemic.

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24 SPHS492301 Capstone in Interprofessional Informatic
IMPACT OF COVID 19 ON EDUCATION
Lakpa Yanzi Sherpa
Texas Woman’s University
28/04/2024

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Contents
Introduction.................................................................................................................................................4
Background of the study ........................................................................................................................4
Problem statement ..................................................................................................................................5
Research questions..................................................................................................................................6
Significance of the study.........................................................................................................................6
Literature review ........................................................................................................................................7
Methods and Materials.............................................................................................................................11
Data ........................................................................................................................................................11
Data analysis method............................................................................................................................11
Data preparation...................................................................................................................................12
Evaluation metric..................................................................................................................................12
Results........................................................................................................................................................12
Conclusion .................................................................................................................................................17
Reference ...................................................................................................................................................18

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Abstract
The COVID-19 virus which spread across the continents in late 2019 prompted health
organizations like WHO, governments, and other communities around the globe to take
unprecedented actions. It was caused by the novel coronavirus SARS-cov-2. The decision to
close schools and switch to remote/distance learning was to minimize the possibility of the virus
transmitting in the crowded school place but it disrupted learning. The pandemic intensified the
already existing disparities in the education system such as access to resources. The purpose of
this study was to determine the impact of COVID-19 on several aspects of the education sectors
such as enrollment trends and class attendance. This study used data visualization, and summary
statistics to provide an overview of the data. This study used the Chi-square test, to answer the
research objective. For the first objective, there was a significant association between the
children missing classes and a severe deficit of internet connection at home. The results from the
Chi-square test also indicated a significant association between the household financial situation
and the children’s enrolment in school.

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IMPACT OF COVID 19 ON EDUCATION
Introduction
Background of the study
The COVID-19 virus which is caused by the novel coronavirus SARS-cov-2 emerged as
a global health concern and spread across the continents in late 2019 prompting health
organizations like WHO, governments, and other communities around the globe to take
unprecedented actions. Governments around the world imposed tighter measures to prevent the
further transmission of the disease as COVID-19 was highly communicable and the virus spread
quickly and death rates were rising exponentially. These measures included lockdowns, travel
restrictions, and the social distancing policy. One of the most significant measures implemented
by the governments and the schools was closing schools which affected millions of the students
and teachers around the school.
The decision to close schools and switch to remote/distance learning was to minimize the
possibility of the virus transmitting in the crowded school place. This abrupt disruption of
learning presented several challenges to students, teachers, parents, instructors, and other school
officials. The students, teachers, and instructors who came from remote areas where there was
limited access or weak internet connection were affected the most as remote learning in those
areas was not a realistic choice (Ali, 2020). The lack of internet access in some areas
compounded the education inequality that was already in existence between the haves and have
not (Ferri et al., 2020). The sudden closure of the schools was also associated with the disruption
of the student’s daily routines and their interactions patterns which are crucial aspects of a
student’s academic performance and their social-emotional development (Zamir & Wang, 2023).

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The impact that COVID-19 had on education went beyond the disruptions in how
instruction was given in class (Di Pietro et al., 2020). The pandemic revealed, brought to light,
and intensified the already existing disparities in the education system. It pointed out the
disparity in access to resources, educational outcomes, and social-economic opportunities.
Students who come from households with a low income, those who are orphaned, and those from
disadvantaged groups such as blacks in some cases have difficulties accessing remote learning
and other support services (Reimers, 2022).
Given the complexity and the magnitude of the challenges posed by the COVID-19
pandemic on the education sector, there is a need to understand how different dimensions in the
education sector were affected. This study aims to enrich the knowledge in this sector by
investigating the effect of the pandemic on education. The disparity enhanced by the pandemic,
identification of vulnerable populations and informing the policies that would support further
recovery in the education sector will be discussed in this study.
Problem statement
The understanding of the multifaceted impact of COVID-19 on education is important for
education stakeholders like policymakers, educators, and stakeholders in the effective design of
measures for mitigating the challenges posed by the pandemic. The purpose of this study is to
determine the impact of COVID-19 on several aspects of the education sectors such as
enrollment trends, access to resources, socioeconomic disparity and quality of instructions. There
is still limited information on the impact of the pandemic on education which this study tries to
respond to.

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Research questions
 Is there a significant association between the children missing classes and a severe deficit of
internet connection at home?
 Is there an association between the household financial situation and the children’s
enrolment in school?
 What is the impact of internet access, electricity access, and geographical location on
student class enrollment during the pandemic?
Significance of the study
This study holds significant importance due to some of the reasons highlighted below:
The policy implications: The findings from this study will be able to inform policies
about the challenges faced by the different population demographics groups in accessing quality
education during the COVID 19 pandemic.
Education inequality: The findings from this study will show whether there are disparities
in educational opportunities based on variables such as gender, age, geographical location and
household income. Understanding these challenges is key in implementing policies that will
promote educational equality.
Long term impact analysis: By understanding the challenges that were brought about by
the pandemic, stakeholders in the education sector will be able to anticipate future challenges
that might be posed by such situation and develop resilient strategies for the education system so
that it can be able to cope with different challenges.

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Literature review
The Covid-19 pandemic which disrupted almost all sectors of the word economy
prompted many studies that tried to establish its impact on various sector such as education. This
section will review and explore some of the key findings from the studies conducted recently in
this area that provide a multidimensional impact of the Covid-19 pandemic on students, teachers,
education institutions, parents and the other broader education stakeholders like the government.
Access to remote learning
Various research showed a disparity in the access o remote learning resources and
technologies which was made worse with the emergence of the Covid-19 pandemic. A study
conducted by Abidah et al (2022) uncovered that there was a significance difference in the
access to the computers and high speed internet needed to support remote learning among
students from low-income households and marginalized communities which hindered them from
fully participating in remote learning. A study conducted by UNESCO (2020) showed that
students who come from developing countries were disproportionately affected by the pandemic
due to the closer of schools as a majority of those areas do not have stable internet connections
and technology to support remote learning.
Learning outcome
There are various studies that have investigated the impact of Covid-19 pandemic on the
education outcome. There have been mixed findings on the impact of the pandemic on learning
outcomes. A study conducted by Drane et al (2020) showed that the prolonged closure of the
prolonged closure of the traditional instruction centers widened the achievement gaps between
the valuable students and less vulnerable students as it resulted in learning loss. The student by

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Kumar et al (2020) found out that some students performed better in remote learning
environment as they benefited from increased study flexibility and personal pacing. There are
still many concerns regarding the equality and quality of remote learning with regards to the
marginalized groups who in most times face greater challenges accessing internet and engaging
with the instructions given online (Gallagher-Mackay et al., 2021).
Professional challenges
The pandemic placed huge strain on the teaching fraternity who had to adapt to the new
ways of giving out instructions and examinations while also navigating their own personal lives
which also had been affected by the pandemic just like everyone else. A study by Chakraborty
& Kar (2021) established that there was increased stress levels of teachers and instructors during
the pandemic due to their concerns of student’s health, learning loss and workload pressure. The
instant shift from physical way of giving instructions to online method exposed the disparity in
the digital literacy levels of the teachers (Espino-Díaz et al., 2020). Some teachers had
challenges using the remote learning tools and addressing these challenges is key for supporting
the wellbeing of the teaching workforce and improving the quality of instructions given by them
in the long run.
Emotional and social impact
The Covid-19 prevention measures like wearing masks, social distancing and lockdown
of some areas have had profound social and emotional impact on the students and the teachers. A
study conducted by Gavriluță (2022) showed that there was elevated rates of depression, social
isolation, and anxiety among school going children during remote learning that was caused by
the pandemic. The heighted stress and anxiety level during the pandemic were caused by the

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disruption of the normal student’s routine, uncertainty about the future, and loss of the social
interaction and connection.
During the COVID-19 pandemic, depression symptoms rose sharply, affecting 27.8% of
people compared to 8.5% before the pandemic. Symptoms were more severe during this time,
especially for those with lower income, minimal savings, or facing COVID-19-related stress.
Adding graphs to this section will improve data presentation and visually reinforce
findings about the frequency and intensity of depression symptoms amid the pandemic.
Information on depression symptoms was collected from a survey of 1,441 US adults
between March 31 and April 13, 2020, and compared to data from the 2017-2018 National

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Health and Nutrition Examination Survey. Both surveys used the PHQ-9 to gauge depression
symptoms.
Innovation in education
Many countries and education institutions implemented the policies and measures and
innovated methods to mitigate the impact of Covid-19 pandemic on education. Some of the
countries used the hybrid learning method where in-person and online classes were conducted in
order to adhere to public regulation but also to ensure there is continuity of education (Scavarda,
2021). Some countries priorities the distribution of technological equipment’s that aids remote
learning to marginalized communities (Gyimah, 2022). Studying how there innovation is
education sector brought about by the pandemic on effectiveness and equality implications is key
in informing future practices and policies in the education sector.

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Methods and Materials
Data
This study used the COVID-19 Education Impact Survey dataset. The dataset can be
accessed online using the URL:
https://data.humdata.org/dataset/open_one_time_covid_education_impact. The dataset contains
data crowdsourced from Venezuelans through the Premise Data mobile application. The survey
is presented only once to users and aims to capture the impact of COVID-19 on children's
education. The data was collected between March 2021 and December 2021. The data contains
27 variables and 4765 observations.
Some of the variables in the data include, the gender of the respondent, age category,
financial situation, education level, place of residence, whether the kid they live with has
enrolled in school or not and whether the kid they live with is attending classes or not.
Data analysis method
This study used data visualization to understand the distribution of variables in the data
and the nature of the relationship that exist in the data. Data visualization was also appropriate
since it displayed results in a manner that is easier to interpret even for people with less to no
statistical knowledge.
A chi-square test of independence will be used to determine the association between the
children missing classes and a severe deficit of internet connection at home and association
between the household financial situation and the children’s enrolment in school. This was the
most appropriate method since both pairwise comparison involved two categorical variables.

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Data preparation
This study checked for presence of duplicated rows and missing values from the data.
Duplicated rows enlarge the sample size and overestimates some features in the data leading to
unreliable findings during analysis. This study eliminated missing values from the data as the
dataset was huge enough and eliminating the missing values would not significantly affect the
sample size of the data.
Evaluation metric
This study used specificity, sensitivity and accuracy to determine the best performing
model. A model with a higher sensitivity, specificity and accuracy will be picked as it would
have shown a higher performance level. The p value will be used to determine whether the
results from the Chi-square test are significant or not.
Results
Summary statistics
Frequency Percent
Gender Male 2130 44.8%
Female 2576 54.2%
Non-binary 5 0.11%
NA 1 0.02%
Prefer not to say 38 0.8%
Age Under 18 103 2.17%
18-25 1265 26.6%
26-35 1399 29.5%
36-45 1170 24.6%

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Over 45 798 16.8%
Location City 2091 44.0%
Rural 1207 25.4%
Suburban 1451 30.5%
Table 1
Based on the results from table 1 above, a majority of the participants in the study were
female (54.2%, n=2576) followed by male (44.8%, n=2130). The population that identified
themselves as non-binary were 0.11% (n=5) while 0.02% (n=1) did not indicate their gender
identity. The results also show that 29.5% (n=1399) who are the majority were between the age
of 26 and 35. The table shows that 2.17% (n=103) identified themselves as under 18, 26.6%
(n=1265) as being between 18 and 25 years, 24.6% (n=1170) as being between 36 and 45 years
and 16.8% (n=798) as being above 45 years. A majority of the respondents came from the city
(44.0%, n=2091) and rural area (25.4%, n=1451). There were 25.4% (n=1207) participants who
came from rural areas.
Figure showing frequency distribution of home by electricity
Figure 1: distribution of Electricity Access in Homes

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Based on the results from figure 1 above, most of the houses of the respondents involved
in the study had been connected to steady electricity (71.68%, n=3405) compared to those that
lacked electricity (28.31%, n=1345)
Figure showing frequency distribution of home by internet connectivity
Figure 2
Based on the results from figure 1 above, a majority of the houses of the respondents
involved in the study had not been connected to internet (58.34%, n=2771) compared to those
that lacked internet (41.66%, n=1979).
Fig: Frequency Distribution of Homes by internet Connectivity.

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Figure 3: Relation between missing class and lack of internet
Based on the results from figure 3 above, most of the students who missed school were
from the households where there was no internet connectivity. This indicates that internet
connectivity affected the rate at which students missed classes. We will conduct a Chi-square test
of independence to determine whether the relationship between missing school and internet
access is significant.
Hypothesis testing
Household financial situation and the children’s enrolment in school

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Table 2
A chi-square test was used to check whether there was a significant association between
household financial situation and the children’s enrolment in school. Household financial
situation and the children’s enrolment in school were categorized into two groups. The
contingency table analysis showed a significant association between household financial
situation and the children’s enrolment in school, χ² (1, N=4750) = 26.81, p < 0.05. The
association indicates that the probability of children being enrolled in school during Covid-19
was dependent on the household financial situation.
Association between the children missing classes and a severe deficit of internet connection
at home
Table 3
A chi-square test was used to check whether there was a significant association between
children missing class and internet deficit. Children missing classes and internet deficit was

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categorized into two groups. The contingency table analysis showed a significant association
between the association between children missing class and internet deficit, χ² (1, N=4750) =
182.51, p < 0.05. The association indicates that the probability of children missing classes during
Covid was dependent on their access to internet.
Conclusion
This study aimed to enrich the knowledge in this sector by investigating the effect of the
pandemic on education. This study used a Chi-square test of independence to check for the
significance of the association between the children missing classes and a severe deficit of
internet connection at home and between the household financial situation and the children’s
enrolment in school.
Based on the results from the Chi-square test, there was a significant association between
the children missing classes and a severe deficit of internet connection at home. The results
indicate that children who were living in households with a severe deficit of internet were more
likely to miss classes during the pandemic than kids from households with better internet
connectivity.
It was also evident that there was a meaningful relationship between the household
financial situation and the children’s enrolment in school. Children from homes in a better
financial situation were more likely to enroll in school during the pandemic than children from
poorer backgrounds. These results are consistent with the results by Kamssu & Kouam (2021)
which indicated that the Covid-19 pandemic had a significant strain on the economic situation of
parents in the lower pay category which contributed to poor enrollment of their kids in school.

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Internet access, electricity access, financial status of the guardian, and geographical
location have a significant impact on students enrolling for classes during the pandemic.
Children from urban areas and cities were more likely to enroll in classes during the pandemic
than children from rural areas. These results are like the findings by Hoover (2020) which
showed a positive association between place of residence and student enrollment during Covid-
19.
This study sheds light on the profound impact of the COVID-19 pandemic on education,
particularly regarding enrollment trends and access to resources. Our findings underscore the
critical need for targeted interventions to address disparities in internet connectivity, household
finances, and geographical location, which significantly influence student participation and
engagement during remote learning. Moving forward, policymakers, educators, and communities
must prioritize investment in equitable education infrastructure and support mechanisms to
ensure that all students have equal access to quality learning opportunities. By fostering
resilience, promoting innovation, and fostering collaboration, we can build a more inclusive and
resilient education system that meets the diverse needs of learners and prepares them for success
in the post-pandemic world.
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