Introduction
COVID-19, caused by the highly transmissible SARS-CoV-2 corona virus, emerged in Wuhan, Hubei, China, in November 2019, and had extensively spread across the globe. By March 2020, the World Health Organization (WHO) officially declared COVID-19 as a pandemic (Jaipuria, S., Parida, R., & Ray, P., 2021). To curb the spread of the virus, countries worldwide implemented a range of measures aimed at reducing overcrowding, encompassing shutdowns, education institute closures, and the termination of transport facilities. This extensive disruption affected over 1 billion and 575 million students, impacting 90% of students globally across 188 countries (Duraku, Z. H., & Hoxha, N., 2020).
The impact of the COVID-19 outbreak extended to India, with Maharashtra, Delhi, Kerala, Rajasthan, and Uttar Pradesh amongst the top five states with the highest number of confirmed cases. In response to the WHO's declaration of COVID-19 as a pandemic, the Indian government swiftly initiated precautionary measures (Gupta, A., & Goplani, M., 2020). The repercussions of the pandemic reverberated through various sectors, notably the tourist and hospitality industries, with an anticipated global loss of 100.08 million jobs. Strategies such as shutdowns, voluntary or involuntary isolation, and crowd management were deployed to stem the spread, leading to significant economic downturns. The impact rippled across sectors including aviation, retail, agriculture, textile, fast-moving consumer goods (FMCG), manufacturing, and start-ups, resulting in substantial economic damage (Tadesse, S., & Muluye, W., 2020). Among the affected sectors, the educational sector bore the brunt of the disruptions, facing unparalleled challenges and uncertainties in the wake of the global health crisis.
According to a statement from UNESCO, the global impact of Covid-19 on the student population was initially staggering, affecting over 90% of students worldwide in mid-April 2020. However, this figure has seen a decrease to approximately 67% by the end of 2020. The pervasive reach of COVID-19 has touched the lives of more than 1.2 billion young individuals globally since its onset. In the context of India, the extensive limitations and worldwide shutdowns due to COVID-19 have left an indelible mark on over 320 million students. UNESCO reports that within this affected group, more than 140 million elementary children and 130 million secondary students in India are particularly beleaguered, making them the two most impacted educational levels in the country (Jena, P. K., 2020).
A considerable number of Indian students pursue education at overseas institutions. The global closure of higher learning institutes is anticipated to result in a decreased interest in seeking education abroad (Agarwal, B., 2022). The fundamental purpose of attending classes or being in school is to enhance a diverse range of skills. Brief periods of education, particularly in business schools, contribute to the acquisition of knowledge and competencies. Conversely, the absence or refusal to attend school can have a profound and lasting impact on lifelong learning. Governments are actively addressing the challenges of active learning and digital literacy. A comprehensive, multi-faceted approach is essential for managing the crisis in the Indian education sector in the long term. A midst this challenging situation, India requires effective learning strategies and well-planned initiatives to foster the development of innovative ideas among the youth. This will not only enhance employment opportunities but also contribute to overall well-being, healthcare, and performance by equipping individuals with the skills necessary for India's substantial progress (Bansal, M., 2022).
Literature Review
Gupta and Goplani (2020) conducted extensive research on the impact of COVID-19 on Indian educational institutions, compiling data from government sites, publications, e-news items, and educator conversations. The study focused on the virus's effects on colleges and universities, assessing government responses and decisions for protecting academic institutions. The findings indicate that during the initial epidemic phase, the ministry and institutional authorities prioritized stakeholder protection. Measures included distributing information to prevent transmission, a nationwide government facility shutdown, and encouragement for digital learning. Concerns for hostel students were raised by the University Grants Commission (UGC), prompting the universities to ensure their care. The study emphasizes the commitment of authorities to stakeholder protection and concludes by acknowledging timely decisions by institutional entities and the Indian government, emphasizing the need for adherence to laws and restrictions to curb the global pandemic.
Deepika Nambiar (2020) conducted research on the impact of web-based learning during COVID-19 from the perspectives of both students and instructors. The study included brief surveys for 70 teachers and 407 students, focusing on their experiences with online classrooms. The research emphasized factors critical for teaching and learning satisfaction, such as the quality of interaction, technical assistance, e-learning configurations, and adjustments for classroom conduct. The study concluded that factors like comfort with online learning structure, communication thresholds, class content quality, technical support, and customer satisfaction significantly influence the overall success of digital learning. Given the early stage of online university education in India, understanding challenges and objectives is crucial for establishing robust and secure systems for online course participation.
Pravat Kumar Jena (2020) conducted a comprehensive review examining the effects of the Covid-19 Pandemic on the Educational System in India. The information collection process involved utilizing auxiliary data, including studies from various national and international institutions on the COVID-19 pandemic, as well as publications and e-content focusing on its impact on the school system.
Toshika Pareek and Kiran Soni (2020) conducted a study titled "A Comprehensive Study On Covid-19 Pandemic: The Effects On School Education In India," involving 100 participants from primary and secondary schools in Udaipur. The objectives included assessing the impact of COVID-19 on educational outcomes, exploring gender-based attitudes toward online learning, evaluating the pros and cons of online studies during the pandemic, and examining the effectiveness of safety measures supporting the shutdown. The study found that online learning became crucial globally to prevent a break in the learning process during the pandemic. The report concluded that online teaching offers additional flexibility and techniques, making it effective according to both male and female students, parents, and teachers in Udaipur district, Rajasthan, during the COVID-19 lockdown.
(Onyema et al. (2020) investigated the impact of COVID-19 on education, collecting data globally through standardized questionnaires and analyzing it with STATA/Regression. The study aimed to understand the challenges hindering education during the pandemic. Findings identified disruptions in education, limited access to facilities, business losses, and increased student debt as consequences of COVID-19. While many turned to technology for continued learning, challenges like poor equipment and connectivity issues hindered online education. The study concludes by advocating for technology integration in education to mitigate the impact of future pandemics, urging the educational community to embrace emerging learning tools for online and remote instruction in the aftermath of COVID-19-induced school closures.
Mukesh Rawal (2021) conducted research on the impact of COVID-19 on the Indian education system, gathering data from various global sources. The study aimed to assess the effectiveness of the education system in handling COVID-19, particularly in virtual classrooms. Findings emphasized the negative impact of school closures on marginalized children, highlighting the need for a combined approach to online learning and a significant economic boost for digital infrastructure. The study also underscored the importance of teacher training and urged higher education institutions to embrace digital innovation. It concluded that COVID-19 has substantially impacted the Indian education industry, revealing the need for nationwide digital access and improved information technology infrastructure, emphasizing efforts to maximize online platforms in prolonged pandemic scenarios.
Jain et al. (2021) conducted a study to gauge the severity of digital literacy in India. A comprehensive questionnaire was developed, and 288 instructors participated, focusing on the openness, use, and academic abilities gap. Findings revealed challenges in reaching economically disadvantaged students during the pandemic, and teachers lacked training in online pedagogy. The study scrutinizes the role of Ed-Tech companies in filling the online academic void but concludes by discussing concerns that these companies might displace rather than aid educators. The data highlighted the need for pedagogical preparation for online teaching, emphasizing that technology should support, not replace, teachers.
Zamira Hyseni Duraku and Linda Hoxha (2021) conducted research on the effect of COVID-19 on education and the well-being of instructors, parents, and students. Challenges related to remote (online) learning and opportunities for improving the overall quality of education in Albania. The study involved a semi-structured interview questionnaire with 13 parents and 11 teachers. Its primary aim was to assess the impact of COVID-19 on education and well-being by identifying challenges associated with online learning. The research observed consistent changes aligning with global predictions of fear, stress, and concerns due to the spread of COVID-19. The study supports the use of remote and online learning, highlighting the efforts of teachers and students in adapting to the learning process. It reinforces the potential for effective digital learning and technology integration into education, aligning with previous findings on Kosovo's technological readiness (STIKK, 2013). Similar to past research, which notes that Kosovar educators undergo various adjustments in response to the requirement for change (Ibrahim et al., 2013).
Kesar Singh (2021) used secondary data to explore challenges in delivering online courses and assess the impact of COVID on India's education sector. Despite challenges, developing countries are adapting and providing support for online learning, leading to increased demand for distance education. However, issues persist, especially for students in rural areas lacking resources. The study suggests a blended learning approach and emphasizes the importance of a real learning environment for holistic student development. Indian institutions have introduced innovative approaches, supported by government initiatives like Diksha, Vidya Dhan, and E-Pathshala. The research concludes that COVID-19 has impacted India's education system, emphasizing the need for comprehensive investigations and collaboration among stakeholders for effective reforms.
Tadesse and Muluye (2020) assessed the impact of the COVID-19 pandemic on education in developing countries, particularly in Africa, using secondary data from national and international sources. Findings highlight disparities in educational delivery methods, with over 90% of high-income nations providing online learning compared to less than a quarter in low-income nations relying on television and radio education. The study emphasizes challenges in access for students in low- and middle-income countries engaging in broadcast and online learning. Conclusions stress the global shift to online teaching, suggesting strategies such as zero-rating educational internet resources, developing digital teaching materials, utilizing free online resources, implementing mobile learning, utilizing broadcast TV, and expanding ICT infrastructure. The responsibilities of schools and colleges post-COVID include curriculum development, learning strategies, and overall education system restructuring, with a focus on recovery planning and strategies for addressing curriculum gaps.
In reviewing existing studies, we identified that most research focused on the impact of COVID-19 on education and the relief measures undertaken, while limited attention is paid to understanding online teaching and its impact on motivation and work efficacy. Addressing this gap, the research questions aim to delve into teachers' comfort and effectiveness with technology for online teaching, assess communication effectiveness in online mode among teachers, students, and administration, explore the support provided by the administration for online classes, gauge teachers' motivation for online teaching, and evaluate teachers' work efficacy in online teaching mode. This study uniquely concentrates on the intricacies of online teaching during the pandemic, particularly within a specific district, offering insights into unexplored aspects of the educational landscape.
Research Methodolody
This section explains, the objective of the study, the hypothesis formulated to be tested, the analytical model, data collection techniques, sampling, and data analysis. After reading the literature review, five objectives have been identified for this study. These objectives are:
To analyse the role of technology in the online teaching process during the pandemic.
To analyse how effective the communication was in the online mode.
To analyse how much administrative support was received by the teachers in the online mode.
To analyse the level of efficacy of the teachers in the online teaching.
To analyse the motivation level of the teachers in the online mode.
The hypotheses are as follows.
H1: Technology has significant influence on motivation of the teachers.
H2: Effective Communication has significant influence on motivation of the teachers.
H3: Administrative support has significant influence on motivation of the teachers.
H4: Technology has significant influence on Work Efficacy of the teachers.
H5: Effective Communication has significant influence on Work Efficacy of the teachers.
H6: Administrative support has significant influence on Work Efficacy of the teachers.
The present study adopts a non-probability sampling technique, specifically the purposive method. This method is chosen deliberately because the focus of this study is on understanding what impacts motivation and work efficacy of teachers in business schools exclusively. Given the targeted nature of the study, where not every member of the population is equally suitable for the research objectives, the non-probability technique is the most fitting choice. The study includes a sample size of 105, carefully selected to capture the diverse perspectives and insights of business school teaching faculties. The present study was conducted in three states i.e., Delhi, Haryana and UP. The business school teachers were used as the samples for this study. Figure 1. shows the analytical model of the study.
In research, variables are characteristics studied to understand their causal effects. In cause-and-effect studies, dependent variables are what researchers want to study but can't control, measured using independent variables that can be manipulated. In this study, work efficacy and motivation are dependent variables, while technology, communication, and administrative support are independent variables.
The primary objective of data collection in this study is to systematically gather and measure information on the variables, facilitating the easy answering of research questions, hypothesis testing, and outcome evaluation. Various primary and secondary sources were used for this study. The primary data collection was employed, through a survey employing diverse question formats, including 5-point scales ranging from ’Strongly Disagree’ to ‘Strongly Agree’, lead-in questions, open-ended questions, fixed alternative questions, and rating scales. Utilizing a self-structured questionnaire with 27 questions, the data collection process involved sharing the questions through an online Google form link. The collected data was then analysed and reported.
The gathered data undergoes analysis through IBM SPSS Statistics 26.0, a software package widely employed by researchers for statistical data analysis. The formulated hypotheses in this study are tested using Exploratory Factor Analysis (EFA), Regression, and Correlation methods. Exploratory Factor Analysis (EFA), employing Varimax rotation, is utilized to determine the factor structure and assess the internal reliability of a measure. Varimax rotation maximizes the total variance of squared loading, emphasizing a smaller set of variables with high factor loading and the rest with lower loading. This approach simplifies the evaluation of results by highlighting a select few key variables.
Regression is a statistical method used to examine and quantify the relationship between a dependent variable and one or more independent variables. In the context of this study, the dependent variables under consideration are Work Efficacy and Motivation, while the independent variables include Technology, Communication, and Administrative Support.
Through regression analysis, the study aims to explore and understand the impact and significance of these independent variables on the identified dependent variables, providing insights into the intricate relationships within the examined factors.
Correlation analysis, a statistical technique, assesses the degree of association between two variables in a study. In this research, the Pearson correlation coefficient is utilized as a measure, with values within the range of -1 to +1. The correlation coefficient indicates the degree of correlation, classified into five types: Perfect (1), High (over .75), Moderate (.50 to .75), Low (.25 to .50), and Absence of correlation (0 to .25). The study employs bivariate correlation analysis in IBM SPSS 26.0 to explore the linear relationship between the dependent variable and the independent variables, providing insights into their associations.
Table 1. shows the demographic details of business school teachers.
Table 1
Demographic details of teachers
Data Analysis and Interpretation
Reliability analysis
The results of Bartlett's sphericity and the Kaiser-Meyer-Olkin (KMO) sampling adequacy tests indicate the suitability of the data for factor analysis. A KMO measure of sampling adequacy of .902 suggests that the sample size is adequate for the analysis. Additionally, the significant result of Bartlett's Test of Sphericity at .000 indicates that there is sufficient correlation between variables for factor analysis to be meaningful. These findings as shown in Table 2. suggest that the dataset is reliable and suitable for factor analysis.
Table 2
KMO and bartlett's test
|
KMO and Bartlett's Test |
||
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy |
0.902 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Sqare |
2315.745 |
|
Df |
210 |
|
|
Sig |
.000 |
|
Cronbach’s alpha (α), an indicator of internal consistency, was employed to evaluate the reliability of all factors (Table 4.3). Strong reliability was observed for each factor, with Motivation at 0.935, Administrative Support at 0.961, Technology at 0.910, Communication at 0.926, and Work Efficacy at 0.886. All factors demonstrated α > 0.6, indicating their reliability for use (Table 4). The overall reliability test for our study, reflected in Cronbach’s alpha (α) at 0.954 (Table 3), underscores the consistency of elements in the developed scale, ensuring statistical significance and fulfilling the necessary reliability criterion for the study's validity.
EFA analysis
In the factor analysis (Table 5), the Varimax rotation with Kaiser Normalization (κ=4) technique was employed for principal component extraction. Initially, 27 elements were reduced to 21. In the subsequent analysis, these 21 variables were grouped into five components based on their factor loadings. Elements with factor loadings below 0.5 were excluded as redundant. The resulting dimensions, named Technology, Communication, Administrative Support, Motivation, and Work Efficacy, represent distinct aspects. Factor loading indicates the strength of a component's influence on a variable, with a value above 0.5 signifying significant impact.1, 2, 3, 4, 5
Table 5
Rotated component matrix (Varimax with kaiser normalization)
Regression
Table 6, depicts the ANOVA results, which is used to report how good the regression equation suits the given set of data.6, 7, 8, 9, 10 The significance level (p < 0.007) is lower than the standard threshold of 0.05, indicating that the regression model is statistically significant. This suggests that the model has a meaningful influence on the dependent variable, namely the motivation of the teachers. Table 7. Depicts the coefficients where the dependent variable is motivation.
Table 6
Anova (where the dependent variable is motivation)
|
ANOVA |
||||||
|
Model |
Sum of Square |
df |
Mean Square |
F |
Sig |
|
|
1 |
Regression |
45.995 |
3 |
15.332 |
34.188 |
0.000 |
|
Residual |
45.294 |
101 |
0.448 |
|||
|
Total |
91.289 |
104 |
||||
|
a. Dependent Variable: MM |
||||||
|
b. Predictors: (Constant), MAS, MC, MT |
||||||
Table 7
Coefficients (where the dependent variable is motivation)
Similarly (Table 8) depicts the ANOVA results, where p < 0.05 which indicates that the following regression model is statistically significant and influence the dependent variable Work efficacy. Table 9 shows the coefficients where the dependent variable is Work Efficacy.
Table 8
Anova (where the dependent variable is work efficacy)
|
ANOVA |
||||||
|
Model |
Sum of Square |
df |
Mean Square |
F |
Sig |
|
|
1 |
Regression |
43.049 |
3 |
14.350 |
64.907 |
0.000 |
|
Residual |
22.329 |
101 |
0.221 |
|||
|
Total |
65.378 |
104 |
||||
|
a. Dependent Variable: MWE |
||||||
|
b. Predictors: (Constant), MAS, MC, MT |
||||||
Table 9
Coefficients (where the dependent variable is Work Efficacy)
In Table 10 and Table 11, the R value, also known as the multiple regression coefficient, is employed to gauge the impact on the work efficacy and motivation of B-school teachers. The values of 0.710 (Table 10) and 0.811 (Table 11) signify a strong level of prediction. The R Square column in the tables, representing the coefficient of determination, indicates how much of the total variation in the work efficacy of teachers and motivation is explained by Technology (T), Communication (C), and Administrative Support (AS). The findings reveal that 50.4% (Table 10) and 65.8% (Table 11) can be explained, respectively. The adjusted R Square, an improved version of R square, is 0.489 (Table 10) and 0.648 (Table 11). The Durbin-Watson value, a measure of auto correlation, is 2.048 (Table 10) and 1.908 (Table 11), suggesting the regression model is a good fit, as it falls within the acceptable range of 1.5
Table 10
Model Summary (where the dependent variable is motivation)
Table 11
Model Summary (where the dependent variable is work efficacy)
Correlation
The current study employs Pearson Correlation to evaluate the relationship between two variables. The Pearson Correlation coefficient 'r' gauges the direction and strength of the connection between the variables, with values ranging between +1 and -1. As per Table 12, Work Efficacy (WE) exhibits a robust positive correlation with Communication (C) (r = .651), Administrative Support (AS) (r = .645), Technology (T) (r = .623), and Motivation (M) (r = .587). Similarly, Motivation shows positive correlations with Technology (T) (r = .595), Work Efficacy (WE) (r = .587), Administrative Support (AS) (r = .572), and Communication (C) (r = .567).
Table 12
Correlation
Findings & Conclusion
Findings of testing of hypotheses status
This research investigates the impact of technology, effective communication, and administrative support on the work efficacy and motivation of business school teachers in online teaching mode during the COVID-19 pandemic in three states: Delhi, Haryana, and UP utilizing a analytical model and regression analysis. The study reveals a robust positive correlation between work efficacy, motivation, and the variables of technology, communication, and administrative Support. Regression analysis with R values of .710 and .811, along with R square values of .504 and .658, respectively, demonstrates that independent variables (Technology, Communication, and Administrative Support) can explain 50% and 66% of the variation in motivation and work efficacy, respectively. All six proposed hypotheses are found to be significant as shown in (Table 13), highlighting the substantial influence of technology, communication, and administrative support on both work efficacy and motivation among business school teachers in online teaching mode during the COVID-19 pandemic. These findings can serve as a foundational framework for broader studies in different samples and demographics.
Table 13
Findings of testing of hypotheses status.
Conclusion & suggestions
The study delving into the impact of productivity and work potency on educators in the digital realm emphasizes the crucial role played by organizational support, student-faculty interaction, course material quality, technology utilization, and e-learning in shaping the teaching and learning experience. To encourage widespread adoption of online channels, a heightened focus on convenience and accessibility is imperative. Addressing concerns related to the layout and administration of online classes is crucial to maximizing learning outcomes. Collaborative efforts involving service providers and institutions can contribute to the recognition and success of e-learning in India. The increasing demand for online classrooms underscores the need for additional research to provide comprehensive insights.
For educational authorities, ensuring a well-established, financially accessible infrastructure for online learning is paramount. Methodological retraining for instructors is crucial for effective online educational adoption. While the study's sample size may limit generalizability, it sheds light on common issues faced by instructors and students in online courses. Considering the impact of the recent COVID-19 pandemic, both students and teachers should receive training on a variety of online educational technology tools. Post-pandemic, continued encouragement for leveraging online technologies to enhance teaching and learning is essential.
Based on the findings, the following recommendations are offered:
Enhance digital literacy among instructors to boost motivation and productivity influenced by technology.
Mandate effective communication training for all teachers, acknowledging its significant impact on motivation and productivity.
Recognize the crucial role of administrative assistance and ensure adequate support is provided to enhance teacher motivation and work efficacy.
Limitations
Because this survey was restricted to only business school teachers, the outcomes may not necessarily be generalized throughout all the education levels. Considering the constrained smaller sample size may not adequately resemble the population, future study should include a bigger sample size to permit for a much more comprehensive inspection of care standard perception and trust.
