1 Introduction

The Coronavirus SARs CoV-2 greatly influenced the students’ learning in higher education institutions (HEIs) across the globe (Agormedah et al. 2020; Rizun and Strzelecki 2020; Sá and Serpa 2020). As a result of COVID-19 urgency, the HEIs primarily suspended the educational activities on campus to avoid the spread of novel virus (Armoed 2021; Lukong et al. 2020). It is pertinent to mention here that it was not possible for HEIs to keep the educational activities suspended for long (Budur et al. 2021; Leal Filho et al. 2021). The internet-based learning [online] was adopted an alternative solution to continue the educational activities (Kohli et al. 2021; Zai and Akhunzada 2020). Thus, governments took measures to contain pandemic by introducing online educational activities the world over (de Boer 2021; Rasheed et al. 2021). Consequently, Agormedah et al. (2020) in line with other researchers argued that educational activities shifted to online mode at massive level (Cecilio-Fernandes et al. 2020). This paradigm shift although brought smoothness in educational activities among developed nations (Aumjaud 2020). As developed countries have common usage of advance technology in universities (Muthuprasad et al. 2021). However, Adnan and Anwar (2020) asserted that majority of developing countries deficient in technology experienced it differently.

A substantial body of research work highlighted the problems of students during pandemic in developing countries (Almaiah et al. 2020). Traditional methods of teaching are generally used in the universities of developing countries (Irfan et al. 2020). Thus, students were less likely familiar with the e-learning mode before pandemic (Wargadinata et al. 2020). At the onset of pandemic’ effects, the decision to initiate teaching activities online was dealt at different levels (Dwivedi et al. 2020; Murphy 2020). As governments in general and universities in particular took time to devise mechanism to shift teaching activities online (Ali 2020; Mishra et al. 2020). Jena (2020) analysed that online teaching affected learning of the students. Similar assertions are given by Onyema et al. (2020). They asserted that pandemic badly affected the performance of the students in higher education. They, like other researchers, further identified different factors that affect the student’ performance. These factors include grades/CGPA issues (Fatonia et al. 2020), mental growth (Khattar et al. 2020), marks criteria (Mukhtar et al. 2020), and internet issues (Tanveer et al. 2020). By the same token, Fatonia et al. (2020) revealed that online learning affected scores/grades of the students. In the similar way, Zai and Akhunzada (2020) unveiled that students questioned the marking criteria while receiving the same answer sheet (Bączek et al. 2021). Baticulon et al. (2021) noted that students are unable to learn the skills. They also found that performance of the students is affected. As a result, students suffered from anxiety, stress, tension, and fear of infection (Agormedah et al. 2020; Farooq et al. 2020; Jena 2020). Chung et al. (2020) revealed students’ issues of internet connectivity while Camara (2020) identified inefficient technology resulted into the distorted communication during the classes (Sheerman et al. 2020).

2 Study context

Like other developing countries, Pakistan is also deficient in technology (Farooq et al. 2020). Most of the educational activities are carried out traditionally on campus. It is worth mentioning that online educational activities were previously, before pandemic, limited to distance learning educational institutions in Pakistan. Although teachers and students were aware of online educational activities. However, they were neither trained nor provided equipment and environment to use online mode. Similar situation is found in HEIs of AJK. Therefore, this research is attempted in HEIs of Azad Jammu and Kashmir to know the students’ perspective regarding online learning during pandemic.

3 Organization of the study

In this article, introduction section is followed by a detailed empirical literature discussed in the context of developed, developing and Pakistan. At the end of literature, a comprehensive conceptual framework is provided for the readers with hypotheses. Third section of article is methodology. A concise methodology is provided that covers the research design, research method, population, sampling, data collection tool, sources of data collection, measurement, use of SPSS, strategies of interpretation and presentation of data. Fourth section is results derived from analysis. It contained description of demographic variables and findings of hypotheses. Last section of article comprised discussions. A precise discussion has been made for the readers. At the end conclusion is drawn based on the analysis of data.

4 Literature review

The higher education system is in the continued process of structural change (Altbach 2005; Ansell 2008; Crosier et al. 2007). The universities have to keep pace with the needs, desires, requirements, and changing landscapes of the educational activities and institutions (Gibbons 1998; Hunt 2011; Marginson and Rhoades 2002). So, information technologies and the e-learning systems are found necessary factors in carrying out the educational activities in universities (Liaw et al. 2007). Thus, the HEIs are investing more on the technologies i.e., devices and online system to keep updating the e-learning process (Salloum et al. 2019). However, in the changing landscapes of the technology, major challenge for HEIs is to integrate the proactive e-learning system to reinforce the effective learning to the students (Samsudeen and Mohamed 2019). The online learning initiative was taken owing to the pandemic situation across the globe.

In the developed countries, use of technology in academia is normally carried out for the educational activities (Pearce et al. 2010; Volchik and Maslyukova 2017). The digital transformation is not a new phenomenon in higher educational institutions (Abad-Segura et al. 2020). These countries are efficient in technology and keep updating the educational e-learning systems with the passage of time (Castro Benavides et al. 2020). The online systems are utilized along with on campus educational activities according to the requirements (Xiao 2019). Normally, the e-learning has always been the part and parcel of the traditional educational system (Kuzu 2020). For the first time in history, the traditional educational system was replaced through online learning system due to the pandemic (Adnan and Anwar 2020). Initially, to curb the prevalence, the HEIs were closed, and educational activities were suspended (Chung et al. 2020). While looking at severity and dire consequences of the pandemic, educational activities were shifted to online systems as it was not possible to keep institutions closed (Fatonia et al. 2020). Although the online learning has been beneficial to the great extent however the issues have been reported by the students (Muthuprasad et al. 2021). As the research studies revealed that performance of students is affected due to online learning. Onyema et al. (2020) and Rasheed et al. (2021) revealed that students are not satisfied with complete shift of educational activities. Research also revealed that students complained about the grading and marking criteria as well (Rizun and Strzelecki 2020; Sheerman et al. 2020).

In developing countries, the situation is quite different to that of the developed countries. As most of the developing countries are deficient in technology (Kituyi and Tusubira 2013; Quimno et al. 2013). Similarly, there scant use of technology in HEIs (Sife et al. 2007). The use of technology is considered only for the meetings, conferences, and special events (Crosier et al. 2007). It is asserted that means of technology is restrained for the academic activities on campus (Salloum et al. 2019; Samsudeen and Mohamed 2019; Santos et al. 2019). Adnan and Anwar (2020) argued that it was very difficult for the HEIs to initiate the online learning due to the limited use of technology. However, it was to curb the prevalence of pandemic HEIs had to shift the academic activities online (Ali 2020). It is important to mention here that developing countries undersupplied in digital technologies suffered during the pandemic (Farooq et al. 2020). The effects of such a transformation were directly experienced by the students who were neither trained nor familiar with the excessive use of technology for the sake of academic pursuits (Mukhtar et al. 2020; Mumtaz et al. 2021). As the performance of the students was affected badly, they were unable to learn the skills (Rasheed et al. 2021). Moreover, students suffered from the tension, anxiety, stress, and fears of infection (Shoaib and Abdullah 2021; Wang and Zhao 2020). Similarly, students also faced the issues of grading and marking (Wargadinata et al. 2020; Zai and Akhunzada 2020). Almaiah et al. (2020) and (Anwar et al. 2020) found that students had the issues in technology use. Sheerman et al. (2020) added that majority of undergrad students had not access to technology either laptop or smart phones. It was further complicated when they faced the poor internet connectivity. As Zai and Akhunzada (2020) and TI (2020) elaborated that the poor internet is the issues of most of the students in developing countries. In the same fashion, Wargadinata et al. (2020) also asserted that students in developing countries are unable to learn and enhance the skills. Further, it affects the performance of the students (Alkamel et al. 2021; Almaiah et al. 2020).

5 Conceptual framework

While developing the conceptual framework, we have developed the following hypotheses.

Hypothesis 1

There is association between educational performance and lack of technology, grading and marking issues, low learning skills, internet, and mental issues.

Hypothesis 2

The bad educational performance is due to the lack of technology, grading system and marking issues, low learning skills, internet, and mental issues.

5.1 Dependent variable

Educational performance.

5.2 Independent variables

Lack of Technology, Grades, Marking, Learning Skills, Internet, and Mental issues.

6 Methodology

6.1 Survey tool and sampling

In this study, we selected quantitative research design and employed cross-sectional research method. We conducted this research in one of the universities of AJK. The Google survey was carried out from 20th October to 20th December 2020. The data was collected from the students studying in Bachelor and Master programmes. Keeping in view the lockdown situation, owing to the pandemic, it was not possible to organize a campus-based sampling survey, thus, online survey form was designed by using Google survey form (https://docs.google.com/forms/). It was also not possible to visit the students physically to get the questionnaire filled. Thus, the questionnaire was designed in English language and converted into Google survey form. Primarily, it has been helpful in the present situation of COVID-19 where social distancing and social isolation is strictly enforced to curtail the spread of virus. Secondly, students are not available on campus rather online learning/ teaching activities were started since the pandemic. To determine sample size, we disseminated Google survey form among 1228 students. Out of 1228 students, 405 responded and filled the questionnaire. Thus, sample size of study was n = 405. We did not use probability sampling technique as we were not sure whether the students will respond or not despite having data. To avoid the inconvenience, we used nonprobability convenience sampling technique. Among the four faculties, 46 teacher were identified, contacted and shared the Google survey form i.e., 15 from Arts, 12 from Sciences, 11 from Engineering and 8 from Health Sciences. The purpose of selecting the teacher was to access students because they were directly in contact with the students via online learning. By means of teachers, students were contacted and Google survey form was shared with them. The Google survey form was shared through a link containing brief introduction, objective, information about anonymity and confidentiality, procedure, and statement about the voluntary nature of survey was also printed on the front page of survey form. The survey from was circulated among teachers via university WhatsApp group and teachers further circulated among the students through WhatsApp and Microsoft Teams. As Microsoft teams is recommended by university for the online learning. Thus, it is believed that every student would have the Teams account. The Google survey form was distributed among the 1228 students while 405 students responded over a period of two months. Thus, the response rate has been 33%.

6.2 Measures

The survey form comprised two portions. First portion was demographic information, and second portion was on the problems faced by the students due to online learning during the pandemic. In personal information portion, we asked question of age, educational level, faculty, and residence. In second portion, ten questions were asked about the issues they face in learning due to the pandemic. The second portion was purely designed on the Likert scale. After the formulation, the questionnaire was pretested, and omissions were removed. Thus, the Cronbach’s Alpha ranged from 0.72 to 0.83 and to overall 0.88. Statistical Analysis was done and frequency (N) distribution of the demographic information was determined by means of SPSS. Two hypotheses were formulated and tested by employing Chi-square and Regression Model respectively. First hypothesis was to check the association of educational performance with lack of technology, grading and marking issues, learning skills, internet, and mental issues In the second hypothesis, predictors of bad educational performance of the students were: use of technology, grading and marking issues, learning skills, internet, and mental issues. The data was documented while all the statistical analyses were performed using SPSS Statistics, version 20, and Microsoft Excel 2018.

7 Results

7.1 Socio-demographic characteristics

Table 1 showed that the demographic information of the students. As the age of students is distributed as, 69.4 percent students fall in age bracket 20–25, 25.9 percent were of age 26–31 years and 4.7 [percent were found above than 32 years of age. The students belonged to four faculties of university. As 29.6 percent belonged to faculty of arts, 25.6 percent fitted into the faculty of arts, 25 percent in faculty of engineering and 19.7 percent from faculty of health sciences. The distribution of students according to the residence is found interesting as 62 percent belonged to the rural areas as compared to 38 percent belonged to urban areas. The educational level of students ranged from BS to PhD. A major proportion of students’ 67.4 percent fall in the BS category, 19.8 percent having MSc/MA educational level, and 9.4 percent have MS and only 3.5 percent were earning the PhD degrees.

Table 1 The demographic characteristics of the students
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7.2 Hypotheses testing

Hypothesis 1

There is association between educational performance and lack of technology, grading and marking issues, low learning skills, internet, and mental issues.

Table 2 shows the association of educational performance with different variables. As the lack of technology is highly significant with the results of p < 0.000. It is noted that results of all the variables included in hypothesis were most significant. The results suggest that the lack of technology impacts the performance of the students to the great extent during pandemic crisis. Similar arguments are given by Coman et al. (2020). They stated that technology has affected the educational performance of the students. The low grades are also highly significant with the low education performance indicating that performance is affected (Adnan and Anwar 2020). It is further revealed by Barrot et al. (2021). They asserted that low. grades affect the performance of students. The effects on mental growth are also highly significant to the educational performance of the students (Faisal et al. 2021). As Abdullah and Shoaib (2021) found psychosocial impacts on the lives of people. Similarly, the performance is significantly associated with the educational performance of the students resulting that the marking issues negatively affected performance of the students (Fatonia et al. 2020). The rests suggested that further supported by Ahmad et al. (2022). They found that performance is impacted by the low marking grades. The association between performance and learning skills is also significant that construes students’ performance is affected, and they are unable to learn the skills due to online learning (Wang et al. 2020). Similar assertions are given by Dutta and Smita (2020) who described nexus of learning and performance are important for the good performance. In the same fashion, internet issue have association with the performance that shows that the performance is affected by the internet disconnectedness (Wargadinata et al. 2020). Similar results are given by many studies (Adnan and Anwar 2020). Based on the above findings, it is argued that educational performance has strong association with the lack of technology, low grades, effects in mental growth, marking issues, low learning skills and internet issues (Agormedah et al. 2020; Onyema et al. 2020; Tanveer et al. 2020). Thus, it is argued, the due to the online learning performance of the students in AJK in badly impacted due to internet disconnectedness. It is noted that students have less access to technology either laptop or smart phones (Rahiem 2021). Similarly, it is noteworthy that the students are unable to learn the skills at home (Hashemi 2021). Owing to these issues, students experience mental issues of stress, anxiety, tension, and fears (Abdullah and Shoaib 2021). Moreover, students also experienced the issues of score, marking and internet.

Table 2 Chi-Square statistical test (dependent variable = educational performance)
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Hypothesis 2

The bad educational performance is due to the lack of technology, grading system and marking issues, low learning skills, internet, and mental issues.

Table 3 revealed determinants of bad educational performance. It showed the most significant values of p values in each category of the analysis i.e., P < 0.000. These results how that lack of technology, grading and marking issue, low learning skills, internet and mental issues are predictor of the negative educational performance of the students. These significant values highlight the impact on the educational performance of the students. As the performance is affected using technology as the students were not aware about the use of technology and suffered in educational achievements (Abad-Segura et al. 2020; Castro Benavides et al. 2020). Similar findings are given by (Mahyoob 2020). He argued that use of technology has key role in educational performance. The performance of students is also affected by the grades of the students (Farooq et al. 2020). It is further supported by the argument of Tadesse and Muluye (2020) who noted that performance is linked with grades of the students. Findings revealed marks criteria discriminatory (Zai and Akhunzada 2020). It is also argued by (Tadesse and Muluye 2020). They stated that students were unable to learn the skills due to online learning (Tanveer et al. 2020). It is pertinent to mention that students suffered from the internet connectivity issues (Simamora 2020). All these issues added on the mental issues of stress, anxiety, tension and fears in students (Faisal et al. 2021; Tang et al. 2020). It is thus found that the educational performance is affected by the different predictors (Hashemi 2021; Tadesse and Muluye 2020). By looking at the ß values, we found that learning skills and internet issues are the major indicators of the bad educational performance of the students (Fig. 1).

Table 3 An OLS multiple regression predicting educational performance of students (standard errors and parameter estimates)
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8 Discussions

The online educational activities were commenced amidst the pandemic due to the urgency of the disease (Aboagye et al. 2020; Adnan and Anwar 2020; Shoaib and Abdullah 2020). It has been revealed that the online educational activities were quite new in most of the developing countries like Pakistan (Cecilio-Fernandes et al. 2020; Chung et al. 2020). As these countries were either incapacitated or none even through to shift the whole system of education on e-learning (de Boer 2021; Dwivedi et al. 2020). However, same happened in Pakistan and the learning was shifted to the online (Adnan and Anwar 2020; Ali 2020). This shift of educational activities has created a vivid gap in educational performance of the students the world over (Fatonia et al. 2020). Similar issues have been reported in Pakistan (TI 2020) and we also found that educational performance is affected badly due to online learning system during the pandemic. The research across the globe indicated the different factors of the bad educational performance of the students (Agormedah et al. 2020; Baticulon et al. 2021; Tanveer et al. 2020). These included, the lack of technology, grading and score issues, marks criteria, learning skills, internet issues and mental issues experienced by the students during the online learning (Khattar et al. 2020; Lukong et al. 2020). Crosier et al. (2007) found that the students in developing countries suffered due to the poor technology as the HEIs and management was not even prepared to initiate the learning online. Thus, due to lack or deficient technology, students were not able to properly take the online classes (Rasheed et al. 2021). Similar issues we found in the study that due to deficient technology students suffered in pandemic while learning online. The learning skills of the students were not enhanced, and they also experienced the issues of low grading and marking issues (Leal Filho et al. 2021). It further affected the performance of the students (Rasheed et al. 2021). In this study, we also found same issues of grading and marking impacting the students’ performance (Azlan et al. 2020). Owing to the week network, they were not able to attend the classes regularly (Lembani et al. 2020). The results of our study also endorsed the bad connectivity of students that further affected the performance. Research revealed that, due to all these factors, students experienced the mental health issues of stress, anxiety, tension, and fears (Faisal et al. 2021; Khan et al. 2020; Tang et al. 2020; Wang et al. 2020). In this case, we also reached at the vantage point that the students suffered from the mental issues due to the lack of technology and disconnected internet. It is thus revealed that the educational performance of the students was badly impacted due to the online learning amidst the pandemic crisis.

9 Conclusion

We reached at the conclusion that the educational performance of the students is mainly impacted by the lack of technology including internet. Similarly, students were unable to learn the skills and improve the scores. As the grading and marking criteria also impacted the scores of the students. Owing to these issues, they suffered from the mental issues of anxiety, tension, stress, and fears of losing scores and maintain the consistency. It is, thus, concluded that the students’ educational performance is badly affected due to the online learning midst the COVID-19 pandemic in AJK. It is suggested to the higher educational institutions to take the radical measures of preparedness during any such crisis to ensure the smooth online educational and learning environment to the students.

Fig. 1
figure 1

An OLS multiple regression predicting educational performance of students

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