Introduction

“Stress occurs when a state of disequilibrium exists within the system of variables relating people to their environments, and only when this state of disequilibrium causes a change in people's normal (i.e., equilibrium) levels of psychological wellbeing,” Hart and Cotton (2003)2 stated, referring to their previous studies. Murphy and Cooper, 20003 With the growing technological usage in every walk of our lives, we will be soon facing stress related to managing and handling the technical gadgets and the consequences related to them. Technological improvements are making jobs more effective and efficient, but they are also putting ongoing pressure on employees to adopt and adapt to recurring, continuous changes and upgrades in technology, which is increasing workplace stress. Technostress is a sort of stress caused by the constant and excessive use of digital technology (Chiappetta, 2017).4 This expression first appeared during the industrial revolution and has since spread to every occupation that involves the use of digital equipment. Inability to cope with technological advances can cause worry and panic, resulting in a condition known as 'Technophobia' (fear of technology). In 2017, Carlotto et al.5, in his book "Technostress: The Human Cost of the Computer Revolution,"s conceived the term technostress for the first time. He declared — technostress as a technological negative impact on humans. He stated that technostress causes psychological reactions such as a pressure of the eye, back pain, headaches, neck and joint pain, insomnia, anxiety, depression, over-related emotional, physical, mental and behavioral disorders and other electronic devices. In personal life and work, technology is necessary and hence it is an unavoidable part of our lives.

As a result of the global preventive efforts used to control the spread of infection during the COVID-19 pandemic, technostress has become more frequent. The tactics to counter or cope up included remote working from home. Various information and communication technologies (ICTs) such as television, mobile phones, the internet, satellite systems, and computer technologies have evolved daily throughout the last few years. These changes have an impact on education, health, the environment, culture, art, and entertainment. Chiappetta, M. (2017).4 As a result, the majority of the population is finding it difficult to keep up with rapid technological advances. In the educational sector, virtual classrooms, social media platforms such as What's App, Google Classroom, Zoom, Facebook, and various online learning management systems were/are used by academics all over the world to communicate with students. A number over 1.5 billion pupils have been impacted by the closure of educational institutions owing to distance learning (UNESCO, 2020). At least for 50% of the teacher and students, this way of teaching and learning was a new or unthought-of experiment. This dilemma affects both teachers and students, especially when the network is down for an extended period and there is a lot of traffic on the internet due to the heavy and continuous use of teachers and students at the same time, as well as power outages or any technical or technical problem with the digital platform. These issues are common in underdeveloped or even developing countries across the world. This pandemic could have far-reaching psychological implications in addition to the potential for physical ill-health, like blood pressure, headache, increased heartbeat, etc. The term "technostress" refers to when people suffer negative psychosocial consequences of technology use and also display negative valence toward ICT use. There are four dimensions to technostress — disbelief , discomfort/fatigue, anxiety, ineffectiveness and each dimension describes two characteristics of technostress (Techno anxiety and Techno fatigue) (Carlotto, et al. ,2017).5, 4, 6, 2, 7, 8, 9, 10, 3

With the unexpected pandemic that covered the world with number of waves and with little or no prior training of usage of technology in education sector, faculty faced a lot of problems to immediately switch to technology forced teaching and assessment. They involved in experiments with various software, applications, gadgets and platforms to keep the teaching and learning continuous. This induced lot of physical and mental stress among the teachers. After the pandemic hit the world, many researchers have worked/researched on the impact of technostress on job satisfaction, employee performance, mental wellbeing, employee efficiency, etc. Unfortunately, very little researches are done to consider teachers/teaching staff as a sample for the study.

Purpose of The Study

High levels of teacher stress have a variety of negative consequences, including impaired concentration, lack of commitment, lack of motivation, poor performance, disconnect from students and the system, and poor classroom instruction quality. Stress levels among academic and non-academic staff at universities worldwide are increasing at an alarming rate (Parray et al., 2016).11

Stress due to the usage of new information technology tools for teaching and learning is stressing teachers, which is affecting their job satisfaction and has effect on organisational commitment.

Objectives of The Study

Literature Review

Results of the research by Penado Abilleira, M., et.al.(2021),12, 13, 14, 15, 1, suggest that female teachers from colleges who are older were the ones who suffered the most from the negative effects of technology. Saim et al (2021)15, did an extensive study of literature to identify and confirm the relation of technostress creators and work life balance. Weems-Landingham, V. (2021)16 in their article “Embracing Technostress to Overcome Online Teaching Challenges” declared that it is inevitable to experience technostress, but the positive mindset and persistence shown can help counter technostress. Brennan F. (2021)17 noticed in his research that 60 percent of the teachers reported feeling stressed by technology. The most significant contributor was techno-overload, which resulted from the shift in teaching format from face-to-face to online. Isolation and disconnect caused by students' reluctance to use webcams during synchronous classes was also a frequently reported cause of synchronous class failure.

In terms of personal characteristics, Coklar & Akçay (2016)6 found that general teacher technostress levels were average; general teacher technostress levels did not vary with gender or length of service but did exhibit a modest variance with Internet use time. According to Syvänen et al., (2016)18, there was no significant difference between male and female teachers or school types, however, younger teachers were less stressed by technology than older teachers. Rebman and Kitchens (2014)14 looked at gender, age, education level, and computer confidence among online teachers and found that female instructors and senior employees have higher levels of technostress; additionally, education level and computer confidence have an impact on technostress. Gender, age, technology awareness, and tenure of academicians all have an impact on technostress, according to Jena & Mahanti (2014).7 Zainun N. F. H in 201319 studying IT professionals published a paper to assess Technostress on Job Satisfaction and Organisational Commitment, and found that technostress is inversely proportional to job satisfaction and organisational commitment. Agbu & Simeon (2011)20 discovered that older distance education instructors have greater levels of technostress, while there was no significant gender difference.

Research Methodology

The random sampling method was adopted for the research. Faculty from technical and non-technical courses responded for the study. A Sample of 84 faculty members, teaching in two technical colleges (Engineering) and three non-technical Degree colleges from Vijayapur city, Karnataka participated in the study. A structured questionnaire, comprising of 35 questions/statements was administrated for the study.

Conceptual framework

Figure 1

Conceptual framework

Results & Discussion

Chart 1

Personal variable assessment

The Significance value of agedo not show any significance with Technostress dimensions (Techno-Overload = 0.972, Techno-Invasion=0.556, Techno-Complexity=0.611, Techno-Insecurity=0.434, Techno-Uncertainty = 0.483), as they are higher than α = 0.05. Though Technostress dimensions like Techno-overload (-0.004), Techno-complexity(-0.056), Techno-Uncertainty (-0.078) show a negative correlation, stating as age increase, these dimensions may decrease. The outcome is not familiar with the results of Syvänen et al., (2016),18 Rebman and Kitchens (2014)14 & Jena & Mahanti (2014),7 who stated that age does have an influence on technostress. Agbu & Simeon (2011)20 specifically stated that older (senior) distance education instructors reported greater levels of technostress. The Significance value of gender is all shown to be higher than 0.05, hence there is no significant relationship between gender and technostress (Techno-Overload = 0.670, Techno-Invasion=0.834, Techno-Complexity=0.704, Techno-Insecurity=0.869, Techno-Uncertainty = 0.825). Dimensions like Techno-overload (-0.047), Techno-Invasion (-0.023) & General Technostress (-0.011), as not good indications to measure technostress. The outcome varies with the results of12 Penado Abilleira, M., et.al.(2021),18 Syvänen et al., (2016), Rebman and Kitchens (2014)14 & Jena & Mahanti (2014),7 who stated that Gender does have an influence on technostress. But studies of Coklar &Akçay (2016)6 stated that though technostress existed overall; gender did not significantly contribute for the technostress

The significance value of Marital status shows higher than 0.05 and so it is not significant with technostress dimensions(Techno-Overload = 0.877, Techno-Invasion=0.356, Techno-Complexity=0.432, Techno-Insecurity=0.898, Techno-Uncertainty = 0.795). All the dimensions of technostress are having negative R value and so none of the dimensions can be considered as suitable to assess the relation between marital status and technostress dimensions.

The significance value of Stream/Course is once again higher than 0.05 across all the dimensions of technostress (Techno-Overload = 0.551, Techno-Invasion=0.759, Techno-Complexity=0.286, Techno-Insecurity=0.229, Techno-Uncertainty = 0.061) and hence stream is not significant relationship with technostress in general. With Correlation, it can be said that Techno-Complexity(-0.118), Techno-Insecurity (-0.133), Techno-Uncertainty (-0.205), General Technostress (-0.076) are not good indicators of effect of stream on technostress.

The significance value of years of experience is showed on a higher scale, i.e., greater than 0.05 and have been not significant with dimensions of technostress(Techno-Overload = 0.116, Techno-Invasion=0.201, Techno-Complexity=0.258, Techno-Insecurity=0.548, Techno-Uncertainty = 0.789). The positive R value of all the dimensions indicate that as years of experience increase, technostress also increase across Techno-Overload, Techno-Invasion, Techno-Complexity, Techno-Insecurity, Techno-Uncertainty.

Jena & Mahanti (2014)7 stated that tenure/years of experience has an impact on technostress, but the results of the present paper differ from the findings of Jena & Mahanti(2014).7 Hence it can be concluded that Personal variables do not have an impact on Technostress among technical and non-technical faculty (Hn1)

With the significance value above 0.05, it can be stated that Technostress has no effect on Job satisfaction. This signifies that Technostress does not have an influence on Job satisfaction among technical and non-technical faculty (Hn2).

With the significance value above 0.05, it can be stated that Technostress has no effect on Organisational Commitment. This proves that Technostress does not have an influence on Organisational Commitment among technical and non-technical faculty (Hn3).

This result is in dissimilarity with the work of Zainun N. F. H (2013), 19 who concluded that technostress has an effect of job satisfaction and organisational commitment. The results so obtained is the result of the sample size chosen for the study. A larger sample size and in a different geographical location may give other value as technostress is subjective in nature and may change.

Conclusion

Traditionally, personal variables have been found to have a relationship with stress. However, more recent research has found that stress can be caused by a variety of factors. The purpose of this study was to determine whether or not the personal variables are associated with technostress in the same way. The findings of the study revealed that the personal variables chosen for the study –age, gender, marital status, years of experience, stream/coursehave no relationship with technostress, indicating that more in-depth research is required to determine the variables that influence technostress in higher education (14Ragu-Nathan et. al. , 2008).

Adoption of new technologies is the only way to avoid technostress. In fact, earlier adaptation and familiarization with the necessary educational ICT is a requirement of the hour and a standard for the foreseeable future. The paper calls for further research on external factors such as technical and technological assistance (Strudler & Hearrington, 2008), organisational infrastructure (Thomas & Knezek, 2008), managerial support (Dexter, 2008), and a variety of other factors (Kirschner, Wubbels, & Brekelmans, 2008) may have an impact on faculty technostress. The Institutes through their various initiatives can conduct regular trainings to the faculty as and when a new technology to support learning and teaching emerge in the market. Support in terms of advance ICT infrastructure and empowerment to the teachers to try new gadgets, software, platforms and applications can be given to the teachers to enable them learn, clarify their doubts and practice before it is implemented. This will give time for the faculty to practice and get themselves comfortable with the ICT and this in turn will reduce the stress they encounter in their teaching and learning.

Source of Funding

None.

Conflict of Interest

None.

Reference