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Research article
Students’experiences with remote learning during the COVID-19 school
closure: implications for mathematics education
Angel Mukuka
a
,
b
,
*
, Overson Shumba
c
, Henry M. Mulenga
c
a
African Centre of Excellence for Innovative Teaching and Learning Mathematics and Science, University of Rwanda-College of Education, Rwanda
b
Department of Mathematics, Science, and Technology Education, Mukuba University, Kitwe, Zambia
c
School of Mathematics and Natural Sciences, Copperbelt University, Kitwe, Zambia
ARTICLE INFO
Keywords:
COVID-19
Remote learning
Mathematics education
ICT
ABSTRACT
This paper reports the findings of a descriptive survey research that explored secondary school students' expe-
riences with mathematics remote learning during the Corona Virus Disease 2019 (COVID-19) school closure. The
study involved 367 students of ages 13 to 21 selected from six secondary schools in Kitwe district of Zambia using
the cluster random sampling method. Using a mixed-methods research approach, quantitative and qualitative
data were merged to provide a comprehensive analysis of the main findings in the context of the existing liter-
ature, the government's response to COVID-19 school closure, and the challenges associated with remote learning
during that time. Research findings show that more than 56% of the respondents did not have sufficient access to
Information and Communication Technologies (ICT), electricity, and internet services. Most of these respondents
also held a belief that mathematics is a subject that is best learned with face-to-face interactions between the
teacher and students, and among students. These results suggest a need for the education systems in Zambia and
other similar contexts to put up infrastructure that supports the blended and online learning models during and
after the COVID-19 pandemic.
1. Introduction
The coronavirus disease 2019 (COVID-19) has been considered one of
the greatest health threats to humanity worldwide. As of March 8, 2021,
the World Health Organisation (WHO) had recorded a cumulative total of
116,521,281 confirmed cases of COVID-19 with 2,589,548 as a cumu-
lative total of deaths from over 215 countries or territories globally
(World Health Organisation, 2021). It all started on December 31, 2019,
when the Wuhan Municipal Health Commission in China, reported a
cluster of cases of pneumonia after which a novel coronavirus was
identified. As the disease continued to spread across the globe at an
alarming rate it became recognized by WHO as a pandemic on March 11,
2020 (World Health Organisation, 2020). Consequently, many countries
decided to close schools and universities as one of the measures to
minimize person-to-person transmission. This closure posed a serious
threat to educational provision worldwide.
According to the Global Education Coalition launched by United
Nations Educational, Scientific, and Cultural Organization (UNESCO),
over 186 countries worldwide faced nationwide or partial closures of
educational institutions including schools, colleges, and universities.
More than 1.6 billion learners, representing nearly 80% of the world's
student population in primary and secondary schools were affected by
the school closures (UNESCO, 2020). The school closures led to chal-
lenges that included interrupted learning, lack of proper nutrition among
some learners, higher drop-out rates, and lowered academic achievement
levels, among others (Ahedor, 2020;Lancker and Parolin, 2020;Sintema,
2020;UNESCO, 2020). The closure of schools inspired many education
systems world-over to adopt remote teaching and learning.
According to Ray (2020), remote learning provides an opportunity for
students and teachers to remain connected and engaged with the content
while working from their homes. In the context of this study, all forms of
learning that students' experienced during the COVID-19 school closure
are referred to as remote learning opportunities. From the Zambian
experience, these include students' self-study using both electronic and
hard copy learning materials, online learning (e.g., the smart revision,
and e-learning portals, social media, etc.), lessons broadcasted by radio
or television, and private tuitions provided by teachers. However, it had
been anticipated that remote teaching and learning had added to the
challenge of learning mathematics, a subject perceived to be difficult by
many learners at the secondary level of education in Zambia. As a result,
* Corresponding author.
E-mail address: mukukaangel@yahoo.com (A. Mukuka).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2021.e07523
Received 10 March 2021; Received in revised form 2 June 2021; Accepted 6 June 2021
2405-8440/©2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Heliyon 7 (2021) e07523
it became important to explore secondary school students’experiences
with mathematics remote learning during the COVID-19 school closure.
While recognizing the fact that the entire education system is
affected, special attention in this study has been given to mathematics.
This is because students’performance in mathematics in Zambia has
been extremely low even before the COVID-19 outbreak (Examinations
Council of Zambia, 2012;2015;2016;2018;Mukuka et al., 2019). In that
regard, questions about the type of teaching practices that would be
useful during and after the COVID-19 pandemic are worth exploring.
While there might be no straightforward answers to such questions, this
paper brings out some suggestions (based on the data collected, existing
literature, and personal experiences) on some potentially effective
mathematics teaching and learning practices during the current situation
and beyond.
2. Context of the study
Zambia and many other countries/regions worldwide have witnessed
tremendous shocks resulting from the COVID-19 induced crisis. Since its
inception in Zambia, the COVID-19 pandemic was anticipated to worsen
the problem of students’low achievement levels especially in STEM
subjects (Sintema, 2020). The first two positive cases of COVID-19 in
Zambia were announced on March 18, 2020, by the Minister of Health
during the daily updates on the COVID-19 situation in the country. This
announcement was preceded by a press statement a day earlier in which
the government through the Minister of Health ordered the closure of all
schools and universities by March 20, 2020, in a bid to combat the spread
of the disease. The cumulative total of COVID-19 positive cases in Zambia
had risen to 82,655 with 78,721 recoveries and 1,132 deaths as of March
9, 2021 (Worldometer, 2021).
At the onset of school closures, this outbreak reminded us of the need
for alternative mathematics teaching practices outside the classroom
environment. The COVID-19 pandemic forced an immediate switch to
emergency remote learning mode. In conjunction with the Ministry of
General Education (MOGE), an interactive e-learning portal and smart
revision platform was launched by the Zambia Telecommunications
Company (ZAMTEL) in partnership with the Examinations Council of
Zambia (ECZ). The e-learning portal can be accessed at www.elearnin
g.co.zm while smart revision is accessible at www.smartrevision.co.zm.
Access to these platforms has been made free of charge during the current
COVID-19 outbreak period. The national e-learning portal hosts various
teaching and learning materials including e-books, links for specialized
services, and a virtual library that can be useful to both teachers and
students. The smart revision portal, on the other hand, hosts ECZ past
examination papers alongside sample answers and revision tips for
grades 7, 9, and 12. Besides that, the ministry of general education in
partnership with the Zambia National Broadcasting Corporation (ZNBC)
had established a television (TV) channel dedicated to broadcasting both
primary and secondary school lessons in all subjects. These lessons are
being broadcasted even after the re-opening of schools.
Being aware that a larger proportion of the school-going children
did not have access to these platforms, MOGE had also engaged
various local radio stations in broadcasting these lessons. This was also
done as part of the measures for attaining one of the most ambitious
Sustainable Development Goals (SDGs) –“Inclusive and equitable quality
education”. The Ministry of General Education had also partnered with
UNICEF on the printing of educational materials for learners. Some
teachers especially those from urban schools had been collaborating
with parents to form Whatsapp groups through which they could reach
out to the students by giving them assignments, providing feedback,
and attending to individual learners’needs. It was expected that a
successful implementation of the measures highlighted above was
bound to yield positive results not only for the present situation but
also for the future.
With this background, it was necessary to undertake an empirical
investigation whose aim was to find out students’experiences with
remote learning of mathematics during the COVID-19 school closure.
This study was guided by three research questions:
i. How did students access mathematics lessons during the COVID-
19 school closure in selected secondary schools of Kitwe district,
Zambia?
ii. What benefits were associated with the mathematical learning
options that were used by secondary school students during the
COVID-19 school closure?
iii. What challenges did students face with mathematics remote
learning during the COVID-19 school closure?
Answering these questions provided insights into what ought to be
done to improve mathematics remote learning in times of the COVID-19
outbreak and beyond.
3. Method
3.1. Research design
A descriptive survey research design was employed. This design was
appropriate for the study because it enabled the researchers to collect both
qualitative and quantitative data at once without close or prolonged con-
tact with respondents in adherence to COVID-19 social distancing mea-
sures. It was further assumed that this design would enable the researchers
to get detailed views from respondents regarding their experiences with
mathematics remote learning during the COVID-19 school closure. Data to
address the research questions were collected from September 28, 2020, to
October 23, 2020. This was soon after the presidential directive to re-open
schools at all levels of education, with much emphasis on strict adherence
to COVID-19 preventive measures as stipulated by the World Health
Organisation and the country's Ministry of Health.
3.2. Study participants
A cluster random sampling method was used to select the research
participants from the target population involving grade 10 and grade 11
students from public secondary schools within Kitwe district. To ensure
that both the urban and peri-urban students were included in the sample,
cluster sampling was the most appropriate for the study. Fraenkel et al.
(2006, p. 95) also justified that this type of sampling is one of the easiest
to implement in schools, and it consumes less time. Based on the infor-
mation obtained from the district education office, these schools were
categorized into two clusters of their geographical location (urban versus
peri-urban). In our classification, we considered a school to be urban if it
is located within a 10km-radius from the central business district (CBD).
1
This implies that all the schools located outside the 10km radius of the
CBD were classified as peri-urban.
Thereafter, three schools were randomly selected from each cluster
bringing the total number of participating schools to 6. From each
selected school, two classes (one grade 10, and one grade 11) were
randomly selected. This means that a total of 12 classes (6 grade 10, and 6
grade 11) participated in the study. Finally, all the students from each
selected class were included in the sample bringing the total number of
respondents to 367 of which 172 were from urban schools while 191
came from peri-urban schools. In terms of gender, 178 (48.5%) were
male while 189 (51.5%) were female. The ages of respondents ranged
from 13 to 21 (M¼16.92, SD ¼1.47). It was further noted that 174
(47.4%) respondents were in their 10
th
grade while 193 (52.6%) were
doing grade 11. Grade 10 and 11 students were targeted because they
were non-examination classes and they stayed at home during the lock-
down longer than the examination classes (grades 9 and 12). Grade 8
1
Central business district (CBD) refers to commercial and business centre of
Kitwe city.
A. Mukuka et al. Heliyon 7 (2021) e07523
2
students were excluded because they only had less than 3 months of
secondary school experience at the time of the school closure.
3.3. Instrumentation
A semi-structured questionnaire, involving both closed-ended and
open-ended questions was administered to the respondents. The ques-
tionnaire was the only data collection instrument used as it was deemed
appropriate for avoiding researchers' close and/or prolonged contact
with respondents for strict adherence to the “social distancing”COVID-
19 preventive measure. The formulation of the questionnaire items was
done in line with the existing literature on prospects of mathematics
education during the COVID-19 pandemic (Bakker and Wagner, 2020;
Engelbrecht et al., 2020a,2020b;Olivier, 2020). For instance, the
above-cited studies had raised some concerns about online lesson de-
livery, the associated benefits as well as the challenges that may arise due
to the lack of ICT services in some settings. The formulation of ques-
tionnaire items for this study was also inspired by the government's
response to COVID-19 school closure and the anticipated challenges
associated with remote learning in Zambia.
Prior to the main data collection, a draft questionnaire was sent to the
experts for validation. These experts comprised 2 Ph.D. students in
mathematics education, 2 master's students in mathematics education, 6
college/university lecturers in mathematics and science education, and 5
secondary school teachers of mathematics. These validators were selected
because of their vast experience with mathematics education research,
and/or their vast experience with the Zambian secondary school mathe-
matics curriculum. They were asked to comment on the quality of the
included items in terms of sufficiency, relevance, clarity, and coherence.
After getting feedback from these validators, their suggestions and com-
ments were analyzed and the final questionnaire was developed.
The questionnaire comprised three sections namely, demographic
information, students’access to mathematics learning during the COVID-
19 school closure, and the challenges associated with the available
mathematics learning options during that time. After questionnaire
refinement, data collection in all the sampled schools/classrooms
commenced. The questionnaire and the associated datasets are openly
available at https://doi.org/10.17632/mb8sdf576c.1.
3.4. Data analysis
Descriptive statistics such as frequency distributions were used to
analyze data. This gave a provision for quantifying the responses for the
closed-ended questionnaire items. Since the respondents came from two
different clusters, a Chi-square test was used to determine whether
certain factors affecting remote learning during that period could be
associated with the schools’geographical location. Both the frequency
distributions and Chi-square tests were generated using the Statistical
Package for Social Sciences (SPSS) version 21. The analysis of data from
open-ended questionnaire items did not strictly adhere to all procedures
of qualitative data analysis entailing coding, categorizing, and thema-
tizing (Nowell et al., 2017). Instead, excerpts from open-ended responses
were selected that were judged to be consistent and illustrative of
closed-ended questionnaire responses.
3.5. Ethical considerations
Research ethics were upheld at all stages of the study. First of all,
permission from the district education office was sought and granted.
Before distributing the questionnaires to the students, the headteacher or
deputy headteacher for each participating school had to provide advice
on the appropriate time to engage with selected students, while adhering
to COVID-19 preventive measures. Before distributing the questionnaires
to the students, the purpose of the study was explained to them and they
were free to participate or not. Besides that, no name of the school, name
of a class, or name of a respondent has been disclosed in any publication
except for the name of the district/city where the research was
conducted.
4. Results
4.1. Mathematics learning options during the COVID-19 school closure
Students were asked to select the learning options that were acces-
sible to them during the COVID-19 school closure, to indicate the most
used, and to justify their preference. Table 1 displays their choices. Dif-
ferences in row totals (N) are attributed to the fact that not all the 367
students responded to all the questionnaire items.
Results displayed in Table 1 reflect that self-study using hard copies of
various learning resources was the most used (78.1%) mathematics
learning option among all the respondents. This was followed by the
televised mathematics lessons that were used by 43.3% of the re-
spondents, while private lessons provided by mathematics teachers at
home (34.2%) were the third most used learning mode.
Results further revealed that 21.8% of the respondents (25.9% urban
and 18.2% peri-urban students) used the recently launched e-learning
and smart revision portals, while only 19.7% were able to learn mathe-
matics through lessons provided by their teachers online. The least used
learning option for both urban (5.8%) and peri-urban (4.3%) was
through the lessons broadcasted by the radio. Based on findings dis-
played in Table 1, it appears that more urban students had access to
digitalized learning options such as lessons broadcasted on TV, e-learning
and smart revision portals, and online learning through Whatsapp, and
Facebook, than their counterparts in the peri-urban areas.
Self-study using hard copies of various learning resources was not
only the most accessible but was also rated as the most used mathematics
learning option during the COVID-19 school closure. Results showed that
48.3% of the urban students and 46.6% of the peri-urban students rated
this mode of learning as the most used during the said period. When
students were asked to justify their preferences, it was revealed that this
learning option was not only the cheapest way to learn mathematics but
was also the most convenient one since students were able to study at any
time they felt a need to do so. Besides that, access to this learning option
was not affected by the geographical location of the respondent's school,
neither was it affected by most of the factors itemized in Table 2. Below
we quote some of the actual reasons within this category of respondents:
Respondent 39: Since my parents cannot afford to buy a TV set or pay for
extra lessons, studying on my own was a better and easier way to learn
mathematics
Respondent 44: Because the more you do things on your own the more
you know
Respondent 305: Because I did not have a chance to learn mathematics
using any other way apart from studying on my own using textbooks and
my class notes.
On the other hand, some students did not use this mode of learning
indicating that they had challenges whenever they failed to understand
certain concepts since there was no one to ask for clarifications. They
indicated that this learning option was only used when revising previ-
ously understood mathematical concepts. One of the respondents gave
the following reason:
Respondent 63: Studying mathematics on my own was not good. I was
separated from my friends and my teacher because of social distancing and
I had no one to ask about things I did not understand
Most respondents who held this belief emphasized that mathematics
is a subject that is best learned with face-to-face interactions between the
teacher and students, and among students.
Concerning mathematics lessons broadcasted on TV, 19.3% of the
urban students and 13.1% of the peri-urban students indicated that it was
A. Mukuka et al. Heliyon 7 (2021) e07523
3
the most used learning mode during the COVID-19 school closure. This
group of respondents stressed that this learning mode needed to continue
even after the COVID-19 imposed lockdown because it helped them to
fully understand mathematical concepts that they did not understand
during their physical class sessions with their teachers. Nevertheless, this
learning option was less popular among the peri-urban students
compared to their counterparts from urban schools. Another shortcoming
associated with the lessons broadcasted on TV was that students did not
have a chance to ask for clarifications. This view is reflected in the
following submission by one of the respondents:
Respondent 114: Although it was good to learn on TV during the COVID-
19 lockdown, I would like to learn at school, where I can ask for clarifi-
cations when I fail to understand something.
Private lessons provided by mathematics teachers to students in their
respective homes was another learning option that was preferred by a
substantial number of students from both urban schools (15.4%) and
peri-urban schools (9.4%). Unlike the ‘self-study, and the televised les-
sons’learning options, the majority of students who preferred private
lessons indicated that a teacher needed to be around to provide clarifi-
cations whenever students faced some difficulties in understanding
certain concepts. The following quotes of students provided the reasons
regarding their preference of this learning option:
Respondent 293: I understand mathematics more when there is someone
to explain and correct me where I go wrong.
Respondent 358: Private lessons provided by mathematics teachers at
home were beneficial to me because I was able to ask where I was wrong
and where I did not understand.
These responses suggest that some students still believe that learning
mathematics can only be possible when there is someone around to guide
and correct them. Over-dependence on teachers as the sole providers of
mathematical knowledge could also be attributed to students’lack of self-
confidence.
The least used mode of learning among both the urban (1.1%) and the
peri-urban (0.5%) students was learning by listening to the lessons
broadcasted by the radio. This confirms our earlier findings in Table 1
that only 5% of all the respondents reported having used this mode of
learning. Finally, 2.2% of the urban students and 20.9% of the peri-urban
students reported that none of the learning options itemized in Table 1
was useful to them. The number appears to be quite high among the peri-
urban students due to the lack or limited access to some of the learning
options that were available to their counterparts from the urban com-
munities. The majority of these respondents indicated that they found
none of those learning methods useful because mathematics was gener-
ally difficult for them. The following were written by these students to
justify why none of those learning options was useful to them:
Respondent 262:None of the above because I don't even like maths. So I
was not doing anything in mathematics.
Respondent 339:I enjoyed none because I can't understand many things
on my own. I need some teachers to help me and I can't even concentrate
when I am studying mathematics alone.
The above narrations appear to indicate that students’negative atti-
tude towards mathematics and dependency on the teacher as the major
source of knowledge might have hampered their mathematics remote
learning experiences.
4.2. Challenges associated with remote learning during the COVID-19
school closure
Students’choices of the most useful learning options could have been
influenced by many factors. To that effect, students were asked to indi-
cate whether, or not each of the itemized factors (Table 2) affected their
mathematical learning during the COVID-19 school closure. Since not all
students responded to all the questionnaire items, the role totals in
Table 2 are not the same.
It has been observed, from Table 2 results that the number of students
who were affected by 8 of the 10 factors was more than the number of
students who indicated that they were not affected. Only the lack of a
television set and lack of radio seemed to have affected a smaller number
of students compared to those who were not affected. In terms of the
geographical location of the sampled schools, results in Table 2 indicate
that more students from peri-urban schools were affected by each of the
Table 1. Accessible mathematics learning options during the COVID-19 school closure.
How were you learning mathematics during the COVID-19 school closure? School Type Number of Learners (N) Response
Yes
N (%)
No
N (%)
1. Self-study using hard copies of mathematics textbooks, notebooks, etc. Urban 175 145 (82.9) 30 (17.1)
Peri-urban 191 141 (73.8) 50 (26.2)
Total 366 286 (78.1) 80 (21.9)
2. Self-study using e-Learning and Smart Revision portals Urban 170 44 (25.9) 126 (74.1)
Peri-urban 187 34 (18.2) 153 (81.8)
Total 357 78 (21.8) 279 (78.2)
3. Televised mathematics lessons on ZNBC's TV4 channel Urban 176 88 (50.0) 88 (50.0)
Peri-urban 191 71 (37.2) 120 (62.8)
Total 367 159 (43.3) 208 (56.7)
4. Mathematics lessons aired on the radio Urban 172 10 (5.8) 162 (94.2)
Peri-urban 185 8 (4.3) 177 (95.7)
Total 357 18 (5.0) 339 (95.0)
5. Private lessons provided by a mathematics teacher at home Urban 174 70 (40.2) 104 (59.8)
Peri-urban 189 54 (28.6) 135 (71.4)
Total 363 124 (34.2) 239 (65.8)
6. Online lessons that were provided by mathematics teachers. Urban 174 37 (21.3) 137 (78.7)
Peri-urban 191 35 (18.3) 156 (81.7)
Total 365 72 (19.7) 293 (80.3)
Note. The numbers indicated in brackets are the corresponding percentages based on the sample size, N, or the row totals.
A. Mukuka et al. Heliyon 7 (2021) e07523
4
10 factors compared to their counterparts from urban schools. This could
be attributed to the fact that urban students had more access to various
learning options than their counterparts from peri-urban schools.
To establish whether this association was significant or not, a Pearson
Chi-square test was conducted for each of the factors listed in Table 2.
The Pearson Chi-square results are displayed in Table 3.
Based on the results displayed in Table 3, there were no statistically
significant associations between each of the factors (5), (6), (7), and (8),
and the schools’geographical location. This may imply that while more
peri-urban students were affected by lack of ICT gadgets, irregular TV
channel subscriptions, lack of mathematics textbooks, and lack of
someone to explain certain mathematical concepts, results show that this
association was not significant. This may also imply that the way these
factors affected the peri-urban schools was not significantly different
from the way they affected the urban students. This suggests that while a
substantial number of students from all the sampled schools were
affected by these factors, not many differences were spotted based on the
geographical location of schools to which these students belonged.
On the other hand, there were statistically significant associations
between students’school geographical location, and each of the factors
such as lack of electricity [
χ
2
(1) ¼4.951, p¼.026], irregular supply of
electricity [
χ
2
(1) ¼5.557, p¼.018], lack of TV [
χ
2
(1) ¼12.191, p<
.0001], lack of a radio [
χ
2
(1) ¼5.240, p¼.022], lack of access to the
internet [
χ
2
(1) ¼5.504, p¼.019], and limited access to the internet [
χ
2
(1) ¼4.032, p<.045]. This may imply that each of these factors had
affected the peri-urban students more than the urban students.
5. Discussion
This study explored secondary school students’experiences with
mathematics remote learning during the COVID-19 school closure. A
switch to a remote learning option during the COVID-19 school closure
was good for the continuous provision of education to all learners of
school mathematics and other subjects. However, the findings of this
study have provided evidence that the implementation of such a measure
might have been hampered by some challenges. Besides, the reported
challenges do not seem to be unique to the Zambian context. For
instance, a study conducted in Jordan by Abuhammad (2020) also cited
personal, logistical, and technical barriers regarding the distance
learning mode during the COVID-19 lockdown. Another study conducted
in Bangladesh by Al-Amin et al. (2021) reported that limited access to the
internet and electricity were among the major impediments to remote
learning in most developing countries.
While educators from some technologically advanced countries might
be managing to reach out to their learners through an online mode of
lesson delivery, some low-income countries may find remote learning
quite difficult (Ahedor, 2020;Camacho-Zu~
niga et al., 2021;Oyediran
et al., 2020). This could be attributed to limited resources by most
schools and a lack of experience by the vast majority of teachers with
online teaching modes. Similarly, Olivier (2020) indicated that an online
mode of lesson delivery may not favour schools with limited resources
whose teachers may not be sufficiently skilled and motivated. While
acknowledging that students with access to ICT gadgets and internet
Table 2. Factors affecting students mathematical learning during the COVID-19 school closure.
Factors School Type Number of Learners (N) Response
Affected Not Affected
1. Lack of electricity Urban 176 100 (56.8) 76 (43.2)
Peri-urban 191 130 (68.1) 61 (31.9)
Total 367 230 (62.7) 137 (37.3)
2. Irregular supply of electricity Urban 175 131 (74.9) 44 (25.1)
Peri-urban 190 161 (84.7) 29 (15.3)
Total 365 292 (80.0) 73 (20.0)
3. Lack of television (TV) set Urban 173 54 (31.2) 119 (68.8)
Peri-urban 191 94 (49.2) 97 (50.8)
Total 364 148 (40.7) 216 (59.3)
4. Lack of a radio Urban 173 54 (31.2) 119 (68.8)
Peri-urban 184 79 (42.9) 105 (57.1)
Total 357 133 (37.3) 224 (62.7)
5. Lack of ICT gadgets like smartphones, computers, etc. Urban 169 114 (67.5) 55 (32.5)
Peri-urban 190 131 (68.9) 59 (31.1)
Total 359 245 (68.2) 114 (31.8)
6. Irregular TV channel subscriptions Urban 173 94 (54.3) 79 (45.7)
Peri-urban 185 114 (61.6) 71 (38.4)
Total 358 208 (58.1) 150 (41.9)
7. Lack of mathematics textbooks and other learning materials Urban 173 140 (80.9) 33 (19.1)
Peri-urban 190 146 (76.8) 44 (23.2)
Total 363 286 (78.8) 77 (21.2)
8. Lack of a more knowledgeable person to explain certain mathematical concepts Urban 175 137 (78.3) 38 (21.7)
Peri-urban 191 150 (78.5) 41 (25.5)
Total 366 287 (78.4) 79 (21.6)
9. Lack of internet access Urban 174 110 (63.2) 64 (38.8)
Peri-urban 189 141 (74.6) 48 (25.4)
Total 363 251 (69.1) 112 (30.9)
10. Limited access to the internet Urban 173 124 (71.7) 49 (28.3)
Peri-urban 191 154 (80.6) 37 (19.4)
Total 364 278 (76.4) 86 (23.6)
Note. The numbers indicated in brackets are the corresponding percentages based on the total number of responses for each factor (row total or sample size).
A. Mukuka et al. Heliyon 7 (2021) e07523
5
services may not be the majority we argue that COVID-19 school closure
in Zambia, and elsewhere could be a wake-up call for education systems
to put up infrastructure that supports the blended and online learning
modes. The provision of ICT products and services is bound to make the
teaching of mathematics easier, both remotely and during physical
classroom interactions.
In line with the foregoing, the big question that requires an answer is
how we can ensure that our students continue learning mathematics
amidst the COVID-19 school closures and other future calamities. Based
on the challenges associated with the effective and successful imple-
mentation of the measures discussed in this paper, it seems almost
impossible to reach out to all learners of school mathematics especially
those in rural areas and other underprivileged communities. Neverthe-
less, suggestions on the possible solutions to some of the highlighted
challenges are given:
First, education providers should always consider the social and
economic status of learners when designing instructional strategies. Here
we concur with Sehoole (2020) who has challenged the education sys-
tems worldwide to take advantage of the COVID-19 outbreak to bridge
the gap between the rich and the poor in terms of access to quality ed-
ucation. It is also worth noting that most of the challenges highlighted
here are not unique to the Zambian context. For instance, Zhang et al.
(2020) also report that “the weakness of the online teaching infrastruc-
ture, the inexperience of teachers (including unequal learning outcomes
caused by teachers’varied experience), the information gap, and the
complex home environment”hurt student learning during the COVID-19
lockdown.
Second is a need to provide ICT products and services to all learners
regardless of their socio-cultural and economic status. If such products
and services are not provided to all then our students in the rural and
other underprivileged communities will lag. This means that the gap
between those who might have access to these services and those who do
not have access will widen, yet all students will be subjected to the same
examinations and later on compete for the same jobs on the labour
market. In their systematic review of 22 studies, Verschaffel et al. (2019),
also found that multimedia and computer-assisted collaborative learning
environments showed positive effects on mathematical and meta-
cognitive learning outcomes. Nevertheless, we are aware that providing
access to ICT services to all students is not attainable within a short
period because it requires a lot of resources from the government and
other stakeholders. Because of this, schools that are unable to provide
e-learning services to their students may scale up the printing of study
materials and devise a mechanism for the distribution of such materials
to their students. Despite being a good alternative as it is sustainable,
printing, and distribution of these materials may also come at a great
cost. The other challenge that comes with this undertaking is ensuring
that the printed materials are easy for students to understand. There may
be no immediate solutions to this but there is a need to consider training
teachers at different levels of mathematics education on how to prepare
mathematics teaching and learning materials that can easily be under-
stood by all the learners.
The third point is a need for each school to design its virtual and/or a
physical mathematics laboratory that is fully equipped with learning
materials, mathematical games, and various teaching and learning aids.
Social media platforms such as Facebook, Whatsapp, Twitter, and so
forth where teachers and students can interact could be established in all
schools. Mathematical games and higher-order thinking questions that
require students to conjecture, justify, and mathematize (Mukuka et al.,
2020a;2020b;Ukobizaba et al., 2021) could be posted on such platforms
to enhance students’understanding of various mathematical concepts,
and problem-solving skills.
Fourth, effective implementation of the highlighted interventions
requires a reasonable level of expertise by teachers. In this vein, we
concur with Zhang et al. (2020) that “equipping teachers with relevant
skills on e-learning platforms, through professional development, with
legal, financial, and administrative support from the government, be-
comes crucial”(p.5). Similarly, Barakabitze et al. (2019) have stressed
the need for African countries to engage in intensive ICT skills training
for teachers to achieve the United Nations Sustainable Development Goal
(SDG) of “ensuring inclusive and quality education for all and promote
lifelong learning”on top of improving the quality of teaching and
learning STEM subjects. This could be attributed to the fact that teacher
effects on students’mathematical achievement account for approxi-
mately 34% (Kyriakides and Creemers, 2009). Additionally, Kyriakides
et al. (2013) argued that “without effective teacher guidance and in-
struction in the classroom, learning cannot be achieved”(p.143). This
suggests that a teacher is one of the significant determinants of student
learning. This is why it is important to orient teachers on lesson planning
and delivery as schools transition to remote learning during the
COVID-19 pandemic and beyond.
Last, students' negative attitudes, low self-confidence, and low moti-
vation towards mathematics have been stated by some of the students in
this research. It has also been established that most students hold a belief
that they cannot learn mathematics effectively without teacher guidance
in a face-to-face environment. This demonstrates a need for interventions
that are aimed at boosting students’confidence and motivation to learn
mathematics even beyond the physical classroom environment. Mathe-
matics has always been offered as a compulsory subject for all learners
from kindergarten to upper secondary levels of the Zambian education
system. This is because, by the time these students leave school, they
should be able to demonstrate clear mathematical thinking and mathe-
matical knowledge in solving real-world problems (Curriculum Devel-
opment Centre, 2013). This leaves teachers and other stakeholders in
mathematics education with no other option than to ensure that students
develop a positive attitude towards mathematics as it is one of the key
attributes for meaningful mathematical learning.
Table 3. Pearson Chi-square tests of Association between School Type and each of the Factors.
Factors Chi-square Value (
χ
2
) df Asymp. Sig. (2-sided)
1. Lack of electricity 4.951
a
1 .026
2. Irregular supply of electricity 5.557
a
1 .018
3. Lack of television (TV) set 12.191
a
1 .000
4. Lack of a radio 5.240
a
1 .022
5. Lack of ICT gadgets like smartphones, computers, etc. .092
a
1 .762
6. Irregular TV channel subscriptions 1.950
a
1 .163
7. Lack of mathematics textbooks and other learning materials .903
a
1 .342
8. Lack of someone to explain certain mathematical concepts .003
a
1 .954
9. Lack of internet access 5.504
a
1 .019
10. Limited access to the internet 4.032
a
1 .045
a
0 cells (0.0%) have an expected count less than 5. The minimum expected count is 36.70.
A. Mukuka et al. Heliyon 7 (2021) e07523
6
5.1. Study limitations
One major limitation of this study is that the questionnaire was the
only research instrument used. While an explanation to this methodo-
logical limitation has been given, it suffices to point out that not all the
required information might have been gathered as some responses
needed some follow-up questions through interviews or other forms of
data collection. Another limitation of the study was that only one district
was involved. While the contexts of other districts in Zambia may not
differ significantly from that of Kitwe, this methodological limitation
makes it difficult to generalize the research findings to other contexts
especially those that are completely rural.
Given these limitations, it is recommended that future studies on this
subject should increase the number of research participants by increasing
the number of districts and secondary schools. Mixed methods studies
may provide further insights that might have not been captured in the
present study. There is also a need for future studies to provide further
insights on how ICT can promote the teaching of mathematics during and
after the COVID-19 pandemic.
6. Conclusion
One of the key findings of this study is that although peri-urban stu-
dents experienced more difficulties in accessing remote learning during the
COVID-19 school closure, urban students equally experienced some chal-
lenges including lack of access to ICT services, irregular supply of elec-
tricity, and lack of motivation to learn without physical interaction with
the teacher and fellow students and their lack of self-confidence. There is,
therefore, a need for secondary schools, with the help of the government
and other stakeholders to promote the establishment of e-learning facilities
countrywide. It is also important to note that the suggestions given in this
paper are just the tip of the iceberg. There is a need for concerted efforts
among the teachers, the Zambia Association for Mathematics Education
(ZAME), MOGE, ECZ, parents, and other stakeholders to ensure that all
school-going children are provided with quality mathematics education
during and after the COVID-19 pandemic. To ensure that systematic and
sustainable solutions are provided, all factors that affect access to educa-
tion during a crisis like the COVID-19 pandemic should be explored
empirically and documented to provide a basis for further actions, in
policy, theory, and practice. Since one of the important findings of this
study refers to the students’dependence on the teacher, they should be
encouraged to learn mathematics on their own through various platforms
such as the ones that have been highlighted in this paper.
Declarations
Author contribution statement
Angel Mukuka, Overson Shumba, Henry M. Mulenga: Conceived and
designed the experiments; Performed the experiments; Analyzed and
interpreted the data; Contributed reagents, materials, analysis tools or
data; Wrote the paper.
Funding statement
This research did not receive any specific grant from funding agencies
in the public, commercial, or not-for-profit sectors.
Data availability statement
Data associated with this study has been deposited at Mendeley Data
https://doi.org/10.17632/mb8sdf576c.1.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
Supplementary content related to this article has been published
online at Data In Brief.
Acknowledgements
The authors wish to thank the District Education Board Secretary's
Office and all the headteachers of the participating schools for facilitating
our engagement with their students who provided the necessary infor-
mation for answering the research questions.
References
Abuhammad, S., 2020. Barriers to distance learning during the COVID-19 outbreak: a
qualitative review from parents’perspective. Heliyon 6, e05482.
Ahedor, J., 2020. Can Teaching in Ghana Carry on Virtually as the Pandemic Rages?
Scientific African Magazine. https://sciafmag.com/2020/04/11/can-teaching-in-gha
na-carry-on-virtually-as-the-pandemic-rages/.
Al-Amin, M., Zubayer, A. Al, Deb, B., Hasan, M., 2021. Status of tertiary level online class
in Bangladesh: students’response on preparedness, participation and classroom
activities. Heliyon 7, e05943.
Bakker, A., Wagner, D., 2020. Pandemic: lessons for today and tomorrow? Educ. Stud. Math.
Barakabitze, A.A., Lazaro, A.W.-A., Ainea, N., Mkwizu, M.H., Maziku, H., Matofali, A.X.,
Iddi, A., Sanga, C., 2019. Transforming African education systems in science,
technology, engineering, and mathematics (STEM) using ICTs: challenges and
opportunities. Educ. Res. Int. 2019, Article 6946809.
Camacho-Zu~
niga, C., Pego, L., Escamilla, J., Hosseini, S., 2021. The impact of the COVID-
19 pandemic on students’feelings at high school, undergraduate, and postgraduate
levels. Heliyon 7.
Curriculum Development Centre, 2013. O Level Secondary School Mathematics Syllabus
Grade 10-12. Ministry of General Education.
Engelbrecht, J., Borba, M.C., Llinares, S., Kaiser, G., 2020a. Will 2020 be remembered as
the year in which education was changed? ZDM - Mathemat. Educat. 52, 821–824.
Engelbrecht, J., Llinares, S., Borba, M.C., 2020b. Transformation of the mathematics
classroom with the internet. ZDM - Mathemat. Educat. 52, 825–841.
Examinations Council of Zambia, 2012. Chief Examiner’s Report. https://www.exams
-council.org.zm/request-for-statistics.
Examinations Council of Zambia, 2015. 2014 Examinations Performance Report in
Natural Sciences. https://www.exams-council.org.zm/request-for-statistics.
Examinations Council of Zambia, 2016. Examinations Performance Report for 2015 in
Natural Sciences. https://www.exams-council.org.zm/request-for-statistics.
Examinations Council of Zambia, 2018. 2017 Examinations Review Booklet: School
Certificate Ordinary Level Chief Examiner’s Reports. https://www.exams-council.
org.zm/request-for-statistics.
Fraenkel, J.R., Wallen, N.E., Hyun, H.H., 2006. How to Design and Evaluate Research in
Education. McGraw-Hill.
Kyriakides, L., Christoforou, C., Charalambous, C.Y., 2013. What matters for student
learning outcomes: a meta-analysis of studies exploring factors of effective teaching.
Teach. Teach. Educ. 36, 143–152, 2013.
Kyriakides, L., Creemers, B.P.M., 2009. The effects of teacher factors on different outcomes:
two studies testing the validity of the dynamic model. Effect Educ. 1 (1), 61–85.
Lancker, W. Van, Parolin, Z., 2020. COVID-19, school closures, and child poverty: a social
crisis in the making. Lancet Publ. Health 2020.
Mukuka, A., Balimuttajjo, S., Mutarutinya, V., 2020a. Applying the SOLO taxonomy in
assessing and fostering students’mathematical problem-solving abilities. In:
Vale, I.S.P., Westaway, L., Nhase, Z. (Eds.), Proceedings of the 28th Annual
Conference of the Southern African Association for Research in Mathematics, Science
and Technology Education. SAARMSTE, pp. 104–112.
Mukuka, A., Mutarutinya, V., Balimuttajjo, S., 2019. Exploring the barriers to effective
cooperative learning implementation in school mathematics classrooms. Probl. Educ.
21st Century 77 (6), 745–757.
Mukuka, A., Mutarutinya, V., Balimuttajjo, S., 2020b. Data on students’mathematical
reasoning test scores: a quasi-experiment. Data in Brief 30. Article 105546.
Nowell, L.S., Norris, J.M., White, D.E., Moules, N.J., 2017. Thematic analysis: striving to
meet the trustworthiness criteria. Int. J. Qual. Methods 16 (1), 1–13.
Olivier, W., 2020. Education post-COVID-19: Customised Blended Learning is Urgently
Needed. The Conversation. https://theconversation.com/education-post-covid-19-
customised-blen.
Oyediran, W.O., Omoare, A.M., Owoyemi, M.A., Adejobi, A.O., Fasasi, R.B., 2020.
Prospects and limitations of e-learning application in private tertiary institutions
amidst COVID-19 lockdown in Nigeria. Heliyon 6 (11).
Ray, K., 2020. What is remote learning? Technol. Learn. https://www.techlear
ning.com/how-to/what-is-remote-learning.
Sehoole, C., 2020. Marching on to a new way of learning and working. Tuition: Newsl.
Facult. Educat. Univ. Pretoria 14 (2), 2. https://www.up.ac.za/media/shared/6/Z
P_Files/up-education-in-tuition-april-2020-web.zp191180.pdf.
Sintema, E.J., 2020. Effect of COVID-19 on the performance of grade 12 students:
implications for STEM education. Eurasia J. Math. Sci. Technol. Educ. 16 (7), 1–6.
Ukobizaba, F., Nizeyimana, G., Mukuka, A., 2021. Assessment strategies for enhancing
students’mathematical problem-solving skills: a review of literature. Eurasia J. Math.
Sci. Technol. Educ. 17 (3), em1945.
A. Mukuka et al. Heliyon 7 (2021) e07523
7
UNESCO, 2020. Empowering students with disabilities during the COVID-19 crisis. Glob.
Educ. Coalition. https://en.unesco.org/covid19/educationresponse/globalcoalition.
Verschaffel, L., Depaepe, F., Mevarech, Z., 2019. Learning mathematics in
metacognitively oriented ICT-based learning environments: a systematic review of
literature. Educ. Res. Int. 2019. Article 3402035.
World Health Organisation, 2020. Coronavirus Disease (COVID-19) Pandemic. https:
//www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-h
appen.
World Health Organisation, 2021. Coronavirus Disease (COVID-19) Dashboard. World
Health Orgnisation. https://covid19.who.int/table.
Worldometer, 2021. COVID-19 Reported Cases and Deaths by Country or territory.
Worldometer’s COVID-19 Data.
https://www.worldometers.info/coronavirus/#countries.
Zhang, W., Wang, Y., Yang, L., Wang, C., 2020. Suspending classes without stopping
learning: China’s education emergency management policy in the COVID-19
outbreak. J. Risk Financ. Manag. 13 (55), 1–6.
A. Mukuka et al. Heliyon 7 (2021) e07523
8
