Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 13 Journal of Applied Economics and Business Studies (JAEBS) Journal homepage: https://pepri.edu.pk/jaebs ISSN (Print): 2523-2614 ISSN (Online) 2663-693X Socio-Economic and Mental Health Impacts of COVID- 19 Lockdown on Students Learning in Pakistan Mumtaz Ahmed1, Muhammad Zeeshan Younas2 & Raja Waqas Shabbir3 1 Assistant Professor, Department of Economics, COMSATS University Islamabad Pakistan 2 PhD Scholar, School of Economics, Quaid-I-Azam University Islamabad Pakistan 3 M.Phil. Scholar, School of Economics, Quaid-I-Azam University Islamabad Pakistan ABSTRACT Evaluation of the e-learning activities in this crisis period amid COVID-19 has significant importance to propose effective mediations for the smooth running of learning and teaching. Keeping this in mind, the present study takes a lead and identifies the key problems associated with online classes during the COVID- 19 lockdown in Pakistan. In addition, we examine the “Stay at Home” orders of government impacts on the mental health of students. The empirical analysis is based on a cross-sectional survey covering students from all educational groups across Pakistan. A sample of 1,114 students is collected via a structured questionnaire constructed using Google Form and floated online to students in all educational institutions in Pakistan. Results indicate that students living in a city that has “Stay at Home” orders in place at the time of the survey is linked with a decrease in mental health by 0.525 standard deviations (p-value=0.0560), suggesting that “Stay at Home” orders have led to a significant reduction in the mental health of the students. Students who report being stayed at home during lockdown have significantly better mental health scores. Additionally, we provide a comprehensive descriptive statistical analysis of the online classes designed for lockdown on different socio-economic and mental health aspects. Keywords COVID-19, Lockdown, Online Classes, Mental Health, Pakistan JEL Classification A10, A11 Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 14 1. Introduction The COVID-19 pandemic affected all spheres of life and sectors of the economy exacerbating the education crises in the developing world—where large disparities have already reduced the opportunities for vulnerable students. It is responsible for the largest disruption of education systems in modern history, affecting nearly 1.6 billion learners in around 200 countries across the globe. To slow the spread of the disease, lockdown measures have been put in place, limiting people’s ability to leave their homes and interact with other people. A major public health concern relates to how these measures impact the mental health of students. In this study, we attempt to examine the impact of lockdown measures on the mental health of students in Pakistan. The closure of schools, colleges, universities, and other learning spaces has impacted nearly 94% of the world’s student population, and this figure goes up to 99% in low and lower-middle-income countries. There is an estimate that 23.8 million additional children may drop out permanently due to the harsh economic effects of the pandemic (UN, 2020). UNICEF claims that at least 463 million school children have no access to distant learning during the strict lockdown. It is equivalent to one-third of the world's schoolchildren or 31% of the total global student population. Pakistan lies in the South Asian region—where 147 million students have no access to learning, making it the highest concentration of students without schools (UNICEF, 2020). Pandemic compelled education institutions to end in-person instruction and switch to online teaching. Cambridge University in the United Kingdom was the first institution to move all face-to-face teaching online on March 24, 2020 (Castle, 2020). In Pakistan, the education institutes were also forced to replace the traditional approach with online teaching, using technology tools like Google Classroom, Microsoft Teams, WhatsApp, Zoom, etc. Online education, by and large, remains a far distant reality for millions around the world and in Pakistan in particular. The students in under-developed remote areas of Pakistan such as Balochistan, FATA, Khyber Pakhtunkhwa, and Gilgit-Baltistan experienced difficulties due to unavailability and in some cases poor connectivity of internet facilities, with poor students having no access to gadgets necessary to acquire online educations (Tahir, 2020). Pakistan’s Higher Education Commission (HEC) encouraged education institutions to use the learning management system (LMS) to carry out educational activities online across the country via an official notification. Moreover, it instructed the institutions facing technological and spatial limitations to remain closed for any academic activities Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 15 till May 31, 2020 (HEC, 2020). The roadmap is clear that online education is the only alternative in this pandemic and the foreseeable future. Pakistan’s educational infrastructure lacks modern technology except for some reputed varsities. Most of the top- ranked varsities are already working on online teaching programs which facilitated them to accelerate it during the pandemic. The government’s timely decision to lift the complete lockdown and to replace it with the selective smart lockdown carries enormous social and economic implications and possibly, it will have lasting effects on the plight of millions of students (children and youth). The UN estimates that 23.8 million additional pre-primary to tertiary students will drop out and lose access to school next year due to pandemics' economic impact alone (UN, 2020). The shutting of the learning institutions due to the COVID-19 outbreak leads to an unprecedented impact on the educational sector. During the lockdowns (both strict and smart), educators are directed to teach through online learning platforms. Abidah et al. (2020) highlight that, to overcome anxieties and mental stress during the lockdown and for the persistence of educational activities, there is a dire need to adopt innovative teaching. Some other researchers (Strielkowski, 2020; Kumar, 2020) conclude that the COVID-19 pandemic results in the digital revolution in the higher education system via interaction at the virtual environment, online examination, digital open books, teleconferencing, and online lectures. Gonzalez et al. (2020) report a significantly positive influence of this pandemic on learning performances and efficiency by implementing online education schemes. However, the online learning strategies are often discriminatory to poor and marginalized students especially from remote areas in Pakistan like Balochistan, FATA and Gilgit-Baltistan. During the lockdown, shut down of educational institutes badly damaged the teaching-learning process and education system of the country (Sarwar et al., 2020; Farooq et al., 2020). Evaluation of the teaching-learning practices in this crisis period is extremely important to propose effective mediations for the smooth running of learning and teaching. Keeping all this in mind, the fundamental objective of this research is to assess a) the awareness, knowledge, and attitude of the students regarding COVID-19, b) learning status, platforms used for online classes and materials sharing during lockdown period, and c) impact of lockdown on economic, health and educational conditions of students during this lockdown amidst the COVID-19 pandemic. The impact of COVID- 19 on educational activities is analyzed by Kapasia et al. (2020) for Indian graduates and post-graduate students, Bayham & Fenichel, (2020) for the USA and Cao et al. (2020) for Chinese students. However, to the best of our knowledge, no prior study exists for Pakistan on this issue covering wider dimensions of COVID-19 lockdown and its impact Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 16 on students including economic and mental health conditions during the lockdown. The empirical findings of the study are based on a sample of 1,114 students currently enrolled in different educational institutions across Pakistan covering all educational groups, school-going, college students and university undergrad and grad students. The empirical findings yield interesting insights into the issue under study. The rest of the paper is organized as: Section 2 provides the overall evolution of COVID-19 and how it leads to the disruption of educational activities. In addition, some relevant literature is discussed as well. Section 3 discusses the framework of the study along with data details and collection methods and the methodological approach. The empirical results and their discussion is provided in Section 4 while section 5 concludes the study. 2. Evolution of COVID-19 and the Educational Disruption The unexpected and dramatic emergence of novel Coronavirus disease (COVID-19) took the world by storm and sent shock waves all around (Iqbal & Younas, 2021). It started from the Chinese city of Wuhan, in early December 2019, and later on December 31, Wuhan Municipal Health Commission, China, reported a cluster of cases of pneumonia in Wuhan, Hubei Province (WHO, 2020). On January 7, 2020, the Chinese authorities formally identified a new type of virus, later named COVID-19. At first, it was declared an outbreak. The alarming level of spread and severity of the disease, having an unprecedented impact on human life in the post-war era, pushed the World Health Organization (WHO) to characterize the COVID-19, as a pandemic, on March 11, 2020. The role of the government increases manifold to mitigate the disruptive impact of the disease in all spheres of life. The governments around the world followed the Chinese model and locked down the countries, cities, and towns to bring life down to a standstill. After the confirmation from Chinese authorities that the human-to-human transmission had taken place, in Wuhan, the first epic center of the novel COVID-19, went into an unprecedented lockdown on 23 January 2020 which was the beginning of a new norm for the world. From here on, the task was gigantic to stop the spread and restrict it to remain inside Chinese borders. It was too big a task, and fighting an unknown enemy, with little clues, put experts and epidemiologists on the back foot. The world was dependent on China to learn about the disease. The nature of the disease and the inability to contain the disease in today’s globalized world helped it spread. Standard operating procedures (SOP’s), national and local measures, such as smart lockdowns, social distancing, restrictions on Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 17 immigration, use of sanitizers, and use of face-masks, and avoiding face-to-face meetings and teachings, helped avoid a large number of casualties. Nevertheless, fatalities and spread are ceaseless, albeit at a lower rate. By and large, the pandemic has fundamentally changed the way people behave and the world function. It has forced people to adopt a new way of life in post-COVID-19 times. Nevertheless, the denial in some quarters remained high, citing the stories related to fake conspiracy theories and misconceptions. The knowledge, attitudes, and practices (KAP) towards COVID-19 is integral to assess the change in the behavior of the public, to avoid further complexities due to emotional panic and misconceptions about this deadly virus (Zhong et al. 2020). To date, the infectious disease has affected 79.6 million. Among those affected by the disease, 1,744,373 have succumbed to death, and 55.1 million have recovered. As of Dec 24, 2020, Pakistan has reported 465,000 confirmed cases, with recoveries of 417,000, and 9,668 people have died of COVID-19 (WHO, 2020). Pakistan confirmed its first two cases of COVID-19 on February 26, 2020. The situation slowly deteriorated in the country, and at one point in time, Pakistan was ranked among the third- riskiest countries for COVID-19 by the Deep Knowledge group on nations and their measures against the Pandemic (DKG, 2020). In East Asia and the Pacific region, Pakistan is ranked 33 among 36 countries, and only Papua New Guinea, Solomon Islands, and Afghanistan were ranked lower to Pakistan in safety scores. The rampage was real. Pakistan recorded 5,830 cases on average in mid-June, and during the week of June 21, the fatality rate soared to 123 deaths per day (daily average by week). Resilient Pakistan, however, showed a steady decline in the new cases—which baffled analysts, infectious disease experts and remains a mystery to date. Nevertheless, the establishment of the National Command Operation Center (NCOC) was the game changer for Pakistan—which helped to tackle down the surge in infections through awareness campaigns impacting behavioral patterns regarding precautionary measures. Pakistan government’s smart-lockdown policy proved successful, and prompt response after some initial setbacks, the government handled the situation aptly. Even then, it was nothing less than a miracle that was required to avoid a steep spike in infections. Pakistan formulated a National Action Plan (NAP) to serve as a policy document to ensure that all the guiding principles for preparedness, containment, and mitigation are followed to deal with the COVID-19. As a developing country, Pakistan lacks medical infrastructure and hospital admission facilities. According to the NAP, all provinces are urged to identify and prepare the quarantine facilities to meet contingencies, as per the Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 18 SOP’s issued by the National Institute of Health (NIH). Pakistan government ordered to close all educational institutions across the country on March 13, 2020, after deliberation in a meeting of the country’s National Security Committee (NSC). The NAP recommended using the vacant buildings of the educational institutions, including hostel facilities, to retain people for quarantine. To prevent the escalation of the disease through transmission, most of these places accommodated travelers. There are some conflicting views on the consequences of COVID-19 on education. In a systematic review of school closures and management practices during COVID-19, Viner et al. (2020) argue that school closure did not contribute to control the epidemic during the SARS outbreak in China, Hong Kong, and Singapore. On the contrary, however, models based on COVID-19 studies predict that school closures reduce the fatalities rate by 2–4%–which is much less than other SOP’s adapted. For example, a study by Kapasia et al. (2020) on the impact of lockdown on e-learning shows that 70% of the students who participated in online classes, faced multiple problems such as depression, anxiety, poor internet connectivity, and an unfavorable study environment at home. Besides, students from unprivileged backgrounds and remote areas faced acute challenges during online learning. Crawford et al. (2020) conduct a desktop analysis to provide intra-period higher education responses to COVID-19 across 20-countries and find diverse responses across the spectrum. Some education providers did not respond at all, while some redeveloped the online application education platform, and few provided isolation facilities to selected students. The findings show that how agile higher education is to prepare for a pandemic. Some world-class institutions (for example, Cambridge University) showed agility and were already prepared to transfer the whole academic work from the traditional system to online. In another study on the effect of COVID-19 on education, Edeh et al. (2020) conclude that the pandemic caused learning disruptions, decreased access to education, and increased student loans. The research finds that poor infrastructure hindered learning opportunities as network problems, power outages, poor digital skills, and unavailability of the internet adversely affected education. It recommends all stakeholders, including children, youth, and parents to adopt technology and improve their digital skills. Burgess and Seivertsen (2020) assess the impact of online education and studied the Swedish case and argued that the “global lockdown of education institutions is going to cause a major (and likely unequal) interruption in students’ learning, disruptions in internal assessments, and the cancellation of public assessments for qualifications or their replacement by an Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 19 inferior alternative”. Di-Pietro et al. (2020) make use of existing literature as well as international data from sources such as Eurostat, PISA, ICILS, PIRLS, and TALIS to assess the accurate impact of COVID-19 on students learning by employing different methodologies. The study concludes that different methodologies can potentially undermine the children’s achievements and the study further highlights that students will suffer an unequal learning loss, with some students suffering more than others. Secondly, the loss of learning time will influence both cognitive and non-cognitive skills acquisition and will have both short- term and long-term consequences on the students learning. The authors acknowledge that it is a new terrain, and to assess the magnitude of damage, due to COVID-19 interruptions, we can rely on pre-COVID studies. Carlsson et al. (2015) determine that even just ten days of extra schooling significantly raise scores on tests of the use of knowledge ‘crystallized intelligence’ by 1% of a standard deviation. The study conducted in Sweden concludes that there is no significant impact on problem-solving skills (an example of ‘fluid intelligence). If we apply these results to an extraordinary situation in COVID-19 times, there is a huge disparity among the skills of the pre-COVID-19 Students and post-COVID-19 students. Lavy (2015) studies the student groups from two countries, who were subjected to different hours of study in key subjects and concludes that one more hour per week over the school year in the main subjects increases test scores by around 6% of a standard deviation, which is significant differences in test scores. On a positive note, Jena (2020) concludes that the emergence of COVID-19 has worked as a catalyst for the educational institutions of India to grow, forcing the institutes to explore and opt for technology-rich platforms, not used before to ensure that education reaches remote areas. The education institutions in Pakistan faced a complete (and in some rare cases a partial) lockdown and faced an unprecedented challenge to cope to readjust their academic year. In Pakistan, the number of affected students stands at 46,803,407. The breakdown of this figure reveals that the number of students affected at the pre-primary level is 8,636,383, at a secondary level, it is 13,357,618 and at the tertiary level, it is about 1,878,101 (Saeed, 2020). It is a critical juncture for a developing country like Pakistan— which already has a very high number of students out of school. The lack of technology/digitalization, poor internet access (of only 36.8%), inability to use the internet, traditional educational policies and teaching methods, and a cultural hindrance to online learning made it difficult for all the population to have access to online teaching. The present study explores the different dimensions of e-learning in Pakistan and assesses Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 20 how Pakistanis students coped with the impacts of COVID-19 on education at schools, colleges and universities. All the researchers agree on the same point that physically attending the school raises the professional and social skills of students. From the very beginning, it increases the ability of the students, and missing school altogether can have profound consequences for the skill growth of the student. Moreover, in the case of no exams, the inaccuracies in the results can bring forth life-changing differences. 3. Data and Methodology 3.1 Study Design, Research Instruments and Participants A quantitative approach is utilized to evaluate the mode of learning, learning status, effectiveness, and problems related to online classes in Pakistan during lockdown amidst the COVID-19 pandemic. A cross-sectional survey is carried out among the students at different universities across Pakistan. A self-administered questionnaire is designed based on previously published literature. The questionnaire comprises of five sections. The first section deals with the demographic information of the participants; the second section contains questions related to awareness, knowledge, and attitude regarding COVID-19; the third section is related to the information about learning status during the lockdown, online classes material sharing platforms and modes of teaching; the fourth section describes the opinion of students regarding academic decisions; and the last section is associated with the impacts of lockdown on economic, health and educational conditions of students. This survey was conducted from August 20 to September 1, just before the two weeks of the scheduled reopening of educational institutions in Pakistan by the Government of Pakistan. The key participants of the study include schools, colleges, undergraduate and graduate students studying in different educational institutions of Pakistan. 3.2 Data Collection and Analysis Approach An online survey is recognized as the most suitable and convenient tool to collect statistics from a geographically diverse large sample. For that reason, data is collected online by using Google Forms, an online application provided by Google Inc. Participants were called on different social media platforms to willingly participate in this study by using authors’ professional and personal networks, and endorsement by many public and private teachers, professors, student union presidents, and educators of higher education institutes from all over Pakistan. Participants who have Pakistani nationality enrolled in any school, college and university, and have taken and/or taking online classes were asked Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 21 to fill in the survey by clicking on the online survey link. A total of 1,114 students from different educational institutions provided complete information related to the survey. The empirical analysis is exploratory in nature and several tools have been used to analyze the responses received based on the questionnaire. Specifically, the impact of COVID-19 lockdown on students’ learning is examined various frequency tables and percentages have been used to explore the pattern of the responses of the students who participated in the survey. The findings yield interesting results. 3.3 Regression Model To analyze the impact of “Stay at Home” orders on the mental health of the students, we define the following model; Mental Health = f (lockdown, individual characteristics, online classes characteristics) This baseline model can be specified in the regression form to make it estimate able with some econometrical technique: 〖 Y〗_i= α+ βLockdown_i+ γX_i+ δZ_i+ε_i (1) Where 〖 Y〗_i is the dependent variable of the model which represents the mental health of university student i. X_i is a vector that denotes the individual characteristics. Z_(i )represents the online classes characteristics and other control variables. While ε_i is the disturbance term of the model. α is the intercept term and β,γ, and δ are the coefficients of the independent and control variables. 3.4 Chi-Square Distribution The ratio of sample variance and population variance multiply by the degree of freedom is used to obtain the chi-square distribution. This happens when the population follows the normal distribution with population variance. The Chi-square test uses adjusting chi-square significance to factor out the sample size. The following equation is a general representation of the chi-square test. X2 = [(n − 1) × s2] ∂2 The researcher widely uses the chi-square test for the association of attributes. Based on chi-square testing we can accept or reject our pre-defined research hypothesis about the dependence between any two variables. The chi-square testing approach used in this study is based on the following steps. Step 1: Define the Research Hypothesis Null Hypothesis: H0: Two variables are independent Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 22 Alternative Hypothesis: H1: Two variables are not independent Step 2: Construction of Cross Tabs The next step is to construct the cross tabs for each under consideration variable and then find the chi-square test value via using the following equation: 𝑋2 = ∑(∂𝑖 − 𝑒𝑖) 𝑒𝑖 Step 3: Find tabulation value After finding the calculated value of the chi-square test, the next step is to compare this value with the tabulated value which can find with the help of the following equation: 𝑋2Tab = 𝑋2d. f at 𝛼 Where d.f represents the degree of freedom which can be calculated with the following equation: 𝑑𝑓 = (𝑟 − 1)(𝑐 − 1) Step 4: Decision Criteria Reject H_0 if α≥p 4. Empirical Findings and Discussion 4.1 Descriptive Statistical Analysis 4.1.1 Demographic Characteristics The demographic analysis of the participants is provided in Table 1. It can be seen that the majority of the respondents are male (64.4%), aged between 18 to 25 years (83.1%) and having a domicile of Punjab province (58%). The number of students who belonged to urban areas is greater than in rural areas. Additionally, the highest proportion of the respondents is of undergraduate students (65%), day scholars (69.6%), having major in science subjects (79.8%), and with a family income of between PKR 30,000 to PKR 60,000. Table 1: Demographic characteristics of participants Variable Name Characteristics Frequency Percent Student Gender Male 717 64.36 Female 397 35.64 Student Age Below 18 61 5.48 Between 18 to 25 926 83.12 Between 26 to 30 86 7.72 Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 23 Above 30 41 3.68 Student Domicile Azad Jammu and Kashmir 46 4.13 Balochistan 54 4.85 FATA 4 0.36 Gilgit Baltistan 26 2.33 Islamabad (Capital) 164 14.72 Khyber Pakhtunkhwa 126 11.31 Punjab 646 57.99 Sindh 48 4.31 Region Rural 360 32.32 Urban 754 67.68 Stream of Study Art 89 7.99 Commerce 136 12.21 Science 889 79.80 Class Level Matric 38 3.41 Inter & Undergraduate 723 64.9 Masters & above 353 31.69 Residence Day Scholar 775 69.57 Hosteller 339 30.43 Student Family Income Below PKR 30K 318 28.55 Between PKR 30K to PKR 60K 441 39.59 Above PKR 60K 355 31.87 Total 1,114 100 Table 2 presents the educational movement of students across different divisions of Pakistan. The permanent residence of most students included in the survey is Rawalpindi (21.36%), followed by Islamabad (14.54%), Lahore (10.59%), Gujranwala (5.21%), Sargodha (4.58%), Gilgit-Baltistan (4.04%), and Peshawar (4.04%). Furthermore, the highest concentration of students included in the survey is found in Islamabad as an institutional region (49.73%), followed by Lahore (13.64%), Rawalpindi (6.73%), Sargodha (5.66%), Quetta (3.41%), and Mardan (3.05%). Islamabad and Lahore are documented as the educational hubs in Pakistan as first having the largest number of universities in Pakistan and second is known as a city of colleges. A large number of educational institutes constitute a concentration of a substantial proportion of students in these cities. Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 24 Table 2: Movement of students for the education Permanent Residence Frequency Percent Institute Location Frequency Percent Rawalpindi 238 21.36 Islamabad 554 49.73 Islamabad 162 14.54 Lahore 152 13.64 Lahore 118 10.59 Rawalpindi 75 6.73 Gujranwala 58 5.21 Sargodha 63 5.66 Sargodha 51 4.58 Quetta 38 3.41 Gilgit-Baltistan 45 4.04 Mardan 34 3.05 Peshawar 45 4.04 Mirpur 27 2.42 Mardan 41 3.68 Peshawar 25 2.24 Mirpur 36 3.23 Karachi 24 2.15 Quetta 36 3.23 Multan 18 1.62 Faisalabad 35 3.14 Jhelum 17 1.53 Hazara 33 2.96 Gujranwala 16 1.44 Larkana 31 2.78 Faisalabad 15 1.35 Kohat 30 2.69 Larkana 12 1.08 Multan 24 2.15 D G Khan 8 0.72 Dera Ghazi Khan 21 1.89 Chakwal 5 0.45 Karachi 20 1.8 Bahawalpur 4 0.36 Makran 17 1.53 Gilgit-Baltistan 4 0.36 Muzaffarabad 12 1.08 Abbottabad 3 0.27 Bahawalpur 10 0.9 Risalpur 3 0.27 Bannu 9 0.81 Sahiwal 3 0.27 Sahiwal 9 0.81 Taxila 3 0.27 Kalat 6 0.54 Attock 2 0.18 Poonch 6 0.54 D I Khan 2 0.18 Hyderabad 5 0.45 Hazara 2 0.18 Swat 5 0.45 Kohat 2 0.18 Waziristan 5 0.45 Sukkur 2 0.18 Zhob 5 0.45 Hyderabad 1 0.09 Dera Ismail Khan 1 0.09 - - - Total 1,114 100 Total 1,114 100 Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 25 4.1.2 Awareness, knowledge, and attitude regarding COVID-19 The second portion of this survey is designed to evaluate the awareness, knowledge, and attitude of the students regarding COVID-19. Table 3 reports the results. First, we asked the participants “when they heard about this novel COVID-19 virus”. Out of 1,114 respondents, 349 students (31.33%) heard about it in December 2019 and 283 students (25.4%) heard during March 2020. More than half of the students (60.41%) key source of information about COVID-19 is social media. Due to a rapid increase in the COVID-19 reporting cases, the country was put under a nationwide lockdown from April 1 and stretched twice until 9 May. After 9th May 2020, the government of Pakistan introduced an innovative method of lockdown which is named “Smart Lockdown”. It means all educational institutes would remain under strict lockdown till 15th September 2020 and partial lockdown would be implemented in different regions of the country. In other words, an area would be under strict lockdown if the number of newly reported COVID- 19 cases acceded to the normally reporting number of cases. We asked the students about their place of residence during the lockdown. The highest proportion of the respondents (91.74%) reported that they are residing at their own home during this COVID-19 compelling lockdown period. Lastly, we asked the students about the difficulties they faced during the lockdown period. The majority of the participants (37.07%) reported that access to finance is the key problem during the lockdown, followed by access to transport (26.84%), access to health facilities (18.13%) and access to food difficulties (17.95%). Table 3: Awareness, knowledge, and attitude regarding COVID-19 Description Frequency Percent The time when heard about COVID-19 During December 2019 349 31.33 During January 2020 247 22.17 During February 2020 235 21.1 During March 2020 283 25.4 Source of information about COVID-19 Friends & Family 112 10.05 Social Media 673 60.41 Print Media 20 1.8 Television 309 27.74 Place residing during the lockdown At own home 1022 91.74 At relatives or other places* 92 8.26 Problems during lockdown Access to finance 413 37.07 Access to food 200 17.95 Access to health facilities 202 18.13 Access to transport 299 26.84 Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 26 Total 1,114 100 Note: * Other places including rented house, hostel, friends’ home, etc 4.1.3 Learning status during the lockdown A series of questions were asked from the students to analyze the learning status and academic sphere during the lockdown period for instance, online lecture format, syllabus coverage, study time and availability of gadgets for online classes. Table 4 reports our findings where 51.71% stated that the format of the online lecture was video in nature and the remaining reported it as an audio format. According to respondents, the Higher Education of Pakistan failed to implement the plans about syllabus coverage during online classes. The highest number of students (57.81%) revealed that below 25% syllabus was covered during online classes while 27.2 % of students reported that 25% to 50% syllabus was covered during the lockdown period. The lockdown period also damaged the study hours as a high number of respondents (65.53%) reported that they did not study regularly during the lockdown period. Among the surveyed students who were attending online classes, 61.85% used smart phones to attend the online classes followed by laptop users (35.19%) and desktop computer users (2.96%). When we asked about the possession of gadgets used for online classes, the majority of them (66.79%) claimed that they had their own gadget. 21.27% reported that they borrowed it from family or relatives and the rest of them borrowed from friends, neighbors, rented out, and other sources. To assess the learning status, we asked whether they had any experience of online class before the COVID-19 lockdown where 80.25% answered with No option. Table 4: Learning status during the lockdown Variable Name Description Frequency Percent Format of lecture Audio Lecture 538 48.29 Video Lecture 576 51.71 Syllabus covered Below 25% 644 57.81 Between 25% to 50% 303 27.2 Above 50% 167 14.99 Studied Regularly Yes 350 31.42 No 730 65.53 Don't want to disclose 34 3.05 Gadget for online classes Desktop computer 33 2.96 Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 27 Laptop 392 35.19 Smart Phone 689 61.85 Possess of Gadgets for online classes I have my own 744 66.79 Family or Relatives 237 21.27 Friends 73 6.55 Rented Out 26 2.33 Neighbours 20 1.8 Others 14 1.26 Experience of Online Class before COVID-19 lockdown Yes 220 19.75 No 894 80.25 Total 1,114 100 4.1.4 Platforms for online classes, material sharing, and evaluation Reliable and quality platforms for online classes remained a key concern since the Corona virus disease emerged. We asked several questions related to the platform used and/or recommended by the Higher Education Commission for online classes in Pakistan. It is found that students were using different platforms for online classes, e-lectures, material sharing, and learning evaluation such as YouTube, Google Classroom, WhatsApp, MS Team, Zoom App and other digital platforms like Skype and Face book. Survey responses revealed that the majority of the students (39.68%) used Zoom App for sharing material and attending online classes followed by MS Team (31.87%), WhatsApp Group (7.01%), Google Classroom (3.32%) and YouTube (1.97%). While 16.16% of students used other platforms including Skype, Face book and LMS university software (see Table 5). WhatsApp groups remained convenient for the respondents to share material related to online classes as the majority of them had their own smart phones. As far as the evaluation of online classes is concerned, more than half of the students show disagreement about the regular evaluation of understanding by the respective educational institute. Assignment and projects were the key criteria of course evaluation in the majority of Pakistani educational institutes. When we asked the respondents about satisfaction with the evaluation method then almost 53% of students showed no satisfaction with this evaluation system. A sub-portion of our survey was related to the sensitivity of information and comfort ability with the online classes. A bigger portion of students (74.51%) did not feel comfortable with using online learning websites like Edx, Coursera and Udemy etc. to cover the missing syllabus during the lockdown period. Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 28 Almost 52% of students showed fear related to misuse of personal information during online learning activities and profile making of online learning applications. When we asked about the overall satisfaction from online learning apps, 45.96% of students were not satisfied with the applications suggested by HEC Pakistan for online classes like Zoom, Team and Google Classroom. While 27.38% reported that they are just satisfied with these learning applications. Table 5: Platforms for online classes, materials sharing, and evaluation Various platforms Description Frequency Percent Platforms of online classes Zoom App 442 39.68 MS Team 355 31.87 WhatsApp 78 7 Google Classroom 37 3.32 YouTube 22 1.97 Others 180 16.16 Platforms of materials sharing WhatsApp Groups 379 34.02 MS Team 257 23.07 Zoom App 137 12.31 Email 132 11.65 Google Classroom 119 10.68 LMS 25 2.44 Others 65 5.84 Regular evaluation of understanding by the institute Yes 525 47.13 No 589 52.87 Course evaluation No exam 125 11.22 Online viva 177 15.89 Quizzes 362 32.5 Assignments/Projects 450 40.39 Satisfaction with the evaluation Yes 403 36.18 No 589 52.87 Don't Know 122 10.95 Comfortable with using online learning websites Yes 284 25.49 No 830 74.51 Fear related to the misuse of personal information Yes 575 51.62 No 539 48.38 Overall satisfaction from online learning apps Not satisfied at all 512 45.96 Just Satisfied 305 27.38 Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 29 Moderately satisfied 241 21.63 Highly satisfied 28 2.51 Don't Know 28 2.51 Total 1,114 100 4.1.5 Opinion of students regarding academic decisions Table 6 describes the opinion of respondents about different announcements and policies of government regarding academic activities. Out of 1114 respondents, 80.61% thought that the lockdown decision and shut down of educational institutes by the Government of Pakistan was a good decision. While the highest number of students (81.24%) are in favor of the HEC announcement about the opening of educational institutions on 15th Sep 2020. When we asked about the Ministry of Education role played in online classes during the lockdown, they showed mixed opinions as 43.81% said yes and 43.9% said no to the question. Table 6: Opinion of students regarding academic decisions Academic decisions and HEC recommendations Description Frequency Percent Do you think, the lockdown decision by the government was good? Yes 898 80.61 No 216 19.39 Are you in favor of the opening of educational institutions on 15th Sep 2020 as announced by HEC? Yes 905 81.24 No 140 12.57 Don't know 69 6.19 Do you think the Ministry of Education Pakistan played its role well during a lockdown? Yes 488 43.81 No 489 43.9 Don't know 137 12.3 Total 1,114 100 4.1.6 Impact of COVID-19 lockdown on students’ life The last segment of our study is associated with the impact of the COVID-19 lockdown impact on student life. We divide these analyses into three sub-segments; economic impacts, health impacts, and educational impacts. Table 7 reports that a bulk of students (71.01%) were suffering from psychological problems like stress, depression, and anxieties during the lockdown period. When we questioned “Did you get any personal coaching to keep you calm during a lockdown?” then only 15.26% of students reported a yes answer. As far as economic impacts are concerned, 70.65% of students said that the lockdown policy badly damaged their family income and 44% reported that their financial Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 30 needs were not fully met during the lockdown. While 40.75% revealed that they need financial support due to low family income effects during the lockdown. According to 47.85% of respondents, financial support in terms of 50% off in educational fees should be given to students due to no on-campus activities. While 26.66% asked for the full fee concession support, followed by 10 to 25% fee waive (13.82%) and no fee reduction (11.67%). A large number of students (47.94%) claimed that they were studying 3 to 6 hours daily before lockdown and 88.42% reported that the lockdown severely affected their study routines. 71.36% said that their study hours significantly decreased during the lockdown period. When we questioned about the enthusiasm level of study, 76.12% described that the lockdown negatively damaged their enthusiasm level of study. As mentioned earlier, internet connectivity was a major issue that students faced during online classes. Out of 1114 students, only 46.59% had internet access. While 45.87% claimed that they had not a very good but an average kind of internet connectivity. Separate room availability for online classes during the lockdown period was also a serious educational problem faced by the students as 50.54% of respondents said that they had no separate room available for online classes. Table 7: Impact of lockdown on economic, health, and educational conditions of students Opinion Description Frequency Percent Economic Impacts Do you think the lockdown affected your family income? Yes 787 70.65 No 244 21.9 Don't Know 83 7.45 Your financial needs are fully met during the lockdown? Yes 471 42.28 No 490 43.99 Don't Know 153 13.73 Do you need financial support due to low family income effects during a lockdown? Yes 454 40.75 No 499 44.79 Don't Know 161 14.45 What financial support should be given to students due to no on-campus activities? Full fee waiver 297 26.66 Half fee waiver 533 47.85 10-25% fee waiver 154 13.82 No fee reduction 130 11.67 Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 31 Health Impacts Feeling of stress, depression, and anxieties during the lockdown Yes 791 71.01 No 235 21.1 Don't Know 88 7.9 Did you get any personal coaching to keep you calm during a lockdown? Yes 170 15.26 No 873 78.37 Don't Know 71 6.37 Educational Impacts Study hours before lockdown Less than 3 hours 429 38.51 3 to 6 hours 534 47.94 More than 6 hours 151 13.55 Did lockdown affect your study routine? Yes 985 88.42 No 104 9.34 Don't know 25 2.24 Did your study hours decrease during a lockdown? Yes 795 71.36 No 259 23.25 Don't know 60 5.39 Did lockdown damage your enthusiasm level of study? Yes 848 76.12 No 170 15.26 Don't know 96 8.62 Internet access Yes 519 46.59 No 595 53.41 Internet connectivity Average 511 45.87 Excellent 103 9.25 Good 277 24.87 No internet access 21 1.89 Very Poor 202 18.13 Separate room available for classes during the lockdown Yes 551 49.46 No 563 50.54 Total 1,114 100 4.2 Regression and Chi-Square Analysis In regression analysis, we examine the impact of “Stay at Home” orders on the mental health of the students in Pakistan. The dependent variable of our regression analysis is the mental health score which is measured by the use of the WHO 5-question module. It has been extensively used by researchers in different perspectives (Krieger et al., 2014; Downs et al., 2017). WHO 5-Question Module: “Over the last two weeks ... [Answers on Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 32 a scale from 0 - “At no time” to 5 - “All of the time”.] 1) I have felt cheerful and in good spirits, 2) I have felt calm and relaxed, 3) I have felt active and vigorous, 4) I woke up feeling fresh and rested, and 5) My daily life has been filled with things that interest me”. An overall mental health score is obtained by summing answers to the 5 questions, with a higher score indicating better mental health. More explicitly, we regress mental health on a dummy variable indicating whether a lockdown was in place as well as a range of individual background characteristics of the students. Cronbach’s alpha coefficient is used to check the internal consistency or reliability. The Cronbach’s alpha of mental health is 0.725 which is in an acceptable range. The OLS estimation-based results are reported in Table 8. The lockdown coefficient is estimated to be negative and significant. It indicates that students living in a city that has “Stay at Home” orders in place at the time of the survey is linked with a decrease in mental health by 0.525 standard deviations (p-value=0.0560), suggesting that “Stay at Home” orders have led to a significant reduction in the mental health of the students. Table 8: Results of Baseline Model Dependent Variable= Mental Health Score Variables Name Coefficient S.E P-Value Lockdown -0.5257** 0.2746 0.0560 Age 0.0088 0.0401 0.8260 Gender Male 0.0402* 0.3158 0.0990 Urban Region -0.1562 0.3108 0.6150 BS Student 0.7013* 0.3983 0.0790 FA/FSc Student 0.4974 0.8150 0.5420 Master Student 0.9428** 0.4533 0.0380 Hostelite 0.3350 0.3167 0.2900 Lockdown Stay at Home 1.0359** 0.5062 0.0410 Online Video Lectures -0.1036 0.2856 0.7170 Internet Facility 0.1326 0.2849 0.6420 Constant 5.8798*** 1.3684 0.0000 No. of observations 1114 --- --- Adjusted R-Squared 0.15 --- --- Note: * indicates that variable is significant at 10% level of significance, ** at 5% level of significance, and *** at 1% level of significance. In Table 8, several other patterns are worth mentioning. In line with previous literature (Astbury, 2001; Seedat et al., 2009; Stevenson & Wolfers, 2009; Adams-Prassl et al., Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 33 2020), our results reveal that being male is associated with significantly higher and better mental health. Likewise, being a BS and Master Student of the university is allied with significantly better mental health. However, there is no significant association is observed between mental health and intermediate students. Moreover, students who report being stayed at home during lockdown have significantly better mental health scores. It suggests that staying at home helps the students to improve mental health and cope up better with the COVID-19 pandemic. The other characteristics like age, urban region, being a hostel student, online video lectures, and internet facilities have no statistically significant relationship with the mental health score. There is a strand of literature available (Chang et al., 2013; Dagher et al., 2015) which postulates that economic downturns or recessions can influence the mental health of males and females differently. In this study, we further examine whether the mental health impact of the “Stay at Home” orders varies by gender. For this objective, we re-estimate our baseline model of Table 8 by introducing an additional interaction term between gender and dummy variable indicating whether the city was in lockdown. The OLS-based estimated results are presented in Table 9. Again, the lockdown coefficient is estimated to be negative and significant. It indicates that students living in a city that has “Stay at Home” orders in place at the time of the survey is linked with a decrease in mental health by 0.8192 standard deviations (p-value=0.0160), suggesting that “Stay at Home” orders have led to a significant reduction in the mental health of the students. As indicated by the significant interaction coefficient, the gender gap is significantly higher in cities that introduced lockdown measures. The estimated gender gap is 0.860 standard deviations larger in cities that had a lockdown in place (p-value=0.0133). The rest of the results of Table 9 are almost in line with the results of Table 8. Table 9: Results after Incorporating Gender Role Dependent Variable= Mental Health Score Variables Name Coefficient S.E P-Value Lockdown -0.8192** 0.3408 0.0160 Age 0.0078 0.0399 0.8450 Gender Male 0.4255* 0.4261 0.0980 Lockdown * Male 0.8604** 0.5726 0.0133 Urban Region -0.1526 0.3098 0.6220 BS Student 0.7038* 0.3972 0.0770 FA/FSc Student 0.6260 0.8116 0.4410 Master Student 0.9477** 0.4521 0.0360 Hostelite 0.3492 0.3161 0.2700 Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 34 Lockdown Stay at Home 0.9598** 0.5029 0.0570 Online Video Lectures -0.0904 0.2846 0.7510 Internet Facility 0.1517 0.2830 0.5920 Constant 6.3874*** 1.3167 0.0000 No. of observations 1114 --- --- Adjusted R-Squared 0.15 --- --- Note: * indicates that variable is significant at 10% level of significance, ** at 5% level of significance, and *** at 1% level of significance. For the robustness checking of our baseline estimates, we introduced a family of dummy variables related to provinces i.e. Punjab, Sindh, KPK, and Balochistan. Table 10 presented the results of this incorporation. It reports that our baseline findings are not sensitive to the inclusion or exclusion of province-related variables except gender. In other words, all variables report the same results as reported in Table 8 with the gender male variable as insignificant. Table 10: Results after Incorporating Province Variables Dependent Variable= Mental Health Variables Name Coefficient S.E P-Value Lockdown -0.5275** 0.2748 0.0550 Age 0.0086 0.0401 0.8300 Gender Male 0.0272 0.3187 0.9320 Urban Region -0.1446 0.3132 0.6440 BS Student 0.7076* 0.3990 0.0760 FA/FSc Student 0.4947 0.8154 0.5440 Master Student 0.9535** 0.4548 0.0360 Hostelite 0.3322 0.3169 0.2950 Lockdown Stay at Home 1.0356** 0.5064 0.0410 Online Video Lectures -0.0987 0.2862 0.7300 Internet Facility 0.1344 0.2851 0.6370 Punjab 0.4018 0.3514 0.2530 Sindh 0.6773 0.7367 0.3580 KPK 0.1606 0.5154 0.7550 Balochistan -0.1118 0.7196 0.8770 Constant 5.8485*** 1.3681 0.0000 No. of observations 1114 --- --- Adjusted R-Squared 0.15 --- --- Note: * indicates that variable is significant at 10% level of significance, ** at 5% level of significance, Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 35 and *** at 1% level of significance. Table 11 provides the chi-square analysis of our study. It reports the dependence of selective variables with lockdown variables. Some independence-related null hypotheses are rejected and some are accepted. This table helps us to understand how the government decision “Stay at Home” influences the daily lives of students. Table 11: Chi-Square Analysis Null Hypothesis Chi- Square P- Value Decision Feeling of stress/depression and lockdown are independent 3.8765 0.099 Null Rejected Family income and lockdown are independent 1.2804 0.572 Null Accepted Difficulty in internet access and lockdown are independent 0.0806 0.776 Null Accepted Study routine and lockdown are independent 5.7563 0.056 Null Rejected Enthusiasm to study and lockdown are independent 3.2877 0.193 Null Accepted Study environment at home and lockdown are independent 0.6029 0.437 Null Accepted Access to transport and lockdown are independent 7.1759 0.028 Null Rejected Access to food and lockdown are independent 3.8689 0.049 Null Rejected Access to finance and lockdown are independent 3.4208 0.181 Null Accepted 5. Concluding Remarks and Policy Implications This study takes a lead and figures out the key challenges and issues that students across all over Pakistan are facing. In particular, it digs deeps and explores the ways that how COVID-19 lockdown impacted the economic, health and educational conditions of the students. The empirical analysis is carried out based on the survey data collected through a structured questionnaire distributed online to students across Pakistan through different social media platforms. A total of 1,114 responses were received providing information on various aspects of online learning and demographics. In regression analysis, we examine the impact of “Stay at Home” orders on the mental health of the students where mental health is a dependent variable measured by the use of the WHO 5- Mumtaz Ahmed, Muhammad Zeeshan Younas & Raja Waqas Shabbir 36 question module. The lockdown coefficient has a negative and statistically significant impact on the mental health of students. It indicates that students living in a city that has “Stay at Home” orders in place at the time of the survey is linked with a decrease in mental health which infers that lockdown orders have led to a substantial decline in the mental health of the students. Our results also conclude that being a BS and Master student of the university and being male is associated with significantly higher and better mental health. Another important finding of the study is that students who report being stayed at home during lockdown have significantly better mental health scores. It proposes that staying at home during lockdown helps the students to improve mental health and cope up better with the COVID-19 pandemic. Robustness analysis indicates that these findings are not sensitive to the inclusion or exclusion of province related variables except gender Similarly, the key findings of descriptive statistical analysis can be summarized as follows. In more than 48% of cases, the format of the lecture was audio rather than a video lecture, implying that the internet connectivity was poor and thus the audio mode of the lecture was preferred over the video. More than 65% of students said that they are no longer studying regularly. There can be several reasons, one of them can be that 33% of the students do not own the learning gadgets. They either rented out or borrowed from friends and family and since the family income of more than 68% of the students included in the sample is below 60,000 PKR, so it is highly unlikely to afford to buy a new one. Another reason can be that more than 80% of the students don't have any prior experience of online learning. As far as economic impacts of COVID-19 lockdown are concerned, more than 70% of the students reported that the lockdown affected their family income and 44% of them that their financial needs are not being fully met and more than 40% asked for financial support. Around 88% of the respondents are in favor of providing a fee concession to the students with 48% recommending waving off half of the tuition fee while 27% are in favor of giving a full fee waiver to the students. The COVID-19 lockdown has imparted severe health impacts on students’ lives with more than 71% responded said that they are in stress, anxiety and depression due to lockdown and the alarming situation is that only 15.26% received any personal coaching. The unprecedented scale and magnitude of online teaching is an experiment and a learning curve for educational institutions. The closure of educational institutions, schools, colleges, and universities not only interrupt the teaching but also creates massive issues of exams and assessments. The wrong assessment delays the recognition Journal of Applied Economics and Business Studies, Volume. 5, Issue 4 (2021) 13-40 https://doi.org/10.34260/jaebs.542 37 of both the extraordinary potential and learning difficulties and its damaging consequences for the future of the students (Burgess, 2020). As almost all universities and colleges replaced the traditional exams with online assessments or some other methods, there was a chance of measurement error. Our study examines the impact of COVID-19 on student education in Pakistan further consolidates the facts established in the literature review section. It shows that educational institute closures caused by the pandemic exacerbated previously existing inequalities and those children who were already most at risk of being excluded from a quality education in Pakistan have been most affected. 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