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Investigating Technostress Among Teachers in Low-Income Indian Schools


Abstract and Figures

Smartphones play an increasingly large role in the professional lives of teachers in low-income contexts, creating an urgent need to better understand the role of technology-related stress (technostress) in teachers' smartphone use for work. We contribute a mixed methods study analyzing the impact of smartphone use on teachers' work lives in low-income Indian schools. Findings from 70 interviews and 1,361 survey responses suggest that although smartphones aid teaching and administrative functions, smartphone use also significantly predicts burnout among teachers, with technostress providing a major explanation for this relationship. We reveal how teachers' work is constantly surveilled and monitored via technology and how teachers' personal smartphones were controlled and repurposed through socio-technical structures by the higher management to serve management's goals, substantially increasing the work teachers were required to perform outside of work hours. Our work extends technostress research to HCI4D contexts and highlights the need to develop better support structures for teachers and rethink how smartphones are used in their work.
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Investigating Technostress Among Teachers in Low-Income
Indian Schools
RAMA ADITHYA VARANASI, Department of Information Science, Cornell University, USA
ADITYA VASHISTHA, Department of Information Science, Cornell University, USA
RENÉ F. KIZILCEC, Department of Information Science, Cornell University, USA
NICOLA DELL, Department of Information Science, the Jacobs Institute, Cornell Tech, USA
Smartphones play an increasingly large role in the professional lives of teachers in low-income contexts,
creating an urgent need to better understand the role of technology-related stress (technostress) in teachers’
smartphone use for work. We contribute a mixed methods study analyzing the impact of smartphone use on
teachers’ work lives in low-income Indian schools. Findings from 70 interviews and 1,361 survey responses
suggest that although smartphones aid teaching and administrative functions, smartphone use also signicantly
predicts burnout among teachers, with technostress providing a major explanation for this relationship. We
reveal how teachers’ work is constantly surveilled and monitored via technology and how teachers’ personal
smartphones were controlled and repurposed through socio-technical structures by the higher management
to serve management’s goals, substantially increasing the work teachers were required to perform outside of
work hours. Our work extends technostress research to HCI4D contexts and highlights the need to develop
better support structures for teachers and rethink how smartphones are used in their work.
CCS Concepts: Human-centered computing Empirical studies in HCI.
Additional Key Words and Phrases: HCI4D, ICT4D, teachers, education technology, technostress, surveillance
ACM Reference Format:
Rama Adithya Varanasi, Aditya Vashistha, René F. Kizilcec, and Nicola Dell. 2021. Investigating Technostress
Among Teachers in Low-Income Indian Schools. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 340
(October 2021), 29 pages.
The global proliferation of smartphones has led to them becoming an indispensable work tool
for a diverse range of workers in HCI4D [
], including teachers who work in low-income
schools in India [
]. A rich body of HCI4D research has examined how smartphones can
be used to support teachers in classrooms [
] and advocates for the integration of
smartphones into teachers’ work [
]. While there are arguments that smartphones can improve
teachers’ productivity [
] and compensate for a lack of pedagogical training and resources [
discussions of how the integration of smartphones into teachers’ work lives might have negative
eects, particularly on technostress (dened as a specic type of stress that individuals experience
due to their use of technology), are notably absent.
Authors’ addresses: Rama Adithya Varanasi,, Department of Information Science, Cornell University,
Ithaca, NYC, USA; Aditya Vashistha, Department of Information Science, Cornell University, New York, NY, USA; René F.
Kizilcec, Department of Information Science, Cornell University, Ithaca, NY, USA; Nicola Dell, Department of Information
Science, the Jacobs Institute, Cornell Tech, New York, NY, USA.
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Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
A cluster of prior education-focused studies has established a strong connection between technol-
ogy use and technostress in countries like South Korea [
], Turkey [
], and Finland [
]. However,
the sources of technostress for teachers in these technology and resource rich settings typically
stem from a variety of educational technologies (e.g., laptops, tablets, and smart classrooms) that
are used for work. By contrast, teachers in low-income settings in the Global South often rely on
smartphones as the only available digital technology. Moreover, the smartphones that teachers in
the Global South use for work are often also their personal devices, which may be shared with
family members [
]. These sharing practices introduce additional complexities in the use of
these devices for work.
This paper presents a mixed-methods study to answer the following research question:
does teachers’ smartphone use impact their technostress at work in low-income schools?
We analyze data from 70 interviews and 1,361 survey responses from teachers who work at a wide
range of low-income government and private schools in India.
Our analyses revealed that teachers relied heavily on their personal smartphones for various
work activities. However, we also discovered how teachers’ devices were controlled and repurposed
by higher management to serve management’s goals and expectations, without establishing ocial
policies around smartphone use for work. Higher management used smartphones to surveil teachers
to ensure they followed the school norms, restrict their smartphone based work via CCTV cameras,
monitor their work through location tracking. Moreover, teachers were required to constantly
submit evidence to prove that they were doing their job.
Higher management also enlisted teachers’ peers to aid their surveillance and monitoring eorts,
limiting the support that teachers were able to receive from peers, increasing perceptions of
strain and burnout. Teachers also used smartphones extensively for administrative work, primarily
via work-related WhatsApp groups. Although this was convenient for both teachers and higher
management, it also led to higher management using WhatsApp to frequently assign work to
teachers outside of work hours with tight deadlines. This increased anxiety and technostress for
teachers, many of whom described having an unhealthy work-life balance.
Finally, teachers felt that the ‘always-on’ nature of smartphones enabled students and their
parents to indiscriminately make requests of them outside of work hours. For example, students
who did not pay attention in class asked teachers to reshare digital resources and information,
leading to more work for teachers. Students also used WhatsApp groups to openly question teachers’
expertise by posting challenging questions found on the Internet, thereby contributing to teacher
embarrassment and strain.
These ndings depict a concerning landscape in which teachers’ smartphone use is associated
with technostress and burnout. We further investigate this issue by quantitatively examining the
relationship between smartphone use, technostress, and burnout using 1,361 survey responses. We
use linear regression to show that teachers’ smartphone use for work signicantly predicts burnout,
meaning more the teachers used their smartphones for work-related activities, higher the stress
and burnout they experienced. Then, we use mediation analysis to demonstrate that technostress
provides a major explanation for the relationship between smartphone use and burnout. Finally,
we use moderation analysis to see the impact of support on the relationship between smartphone
use, technostress, and burnout. We see that both peer and school support play a signicant role
in controlling the relationship between smartphone use and technostress, whereas only school
support inuences the relationship between smartphone use and burnout.
Taken together, these ndings extend the concept of technostress to teaching work in HCI4D
settings. Our ndings also suggest opportunities to rethink how teachers use smartphones for work.
We discuss the need to develop better policies and support structures that reduce technostress
experienced by the teachers. We alsoshed light on the ethical aspects of several problematic practices
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
Investigating Technostress Among Teachers in Low-Income Indian Schools 340:3
surfaced in our ndings, including monitoring and surveillance issues, while also acknowledging the
systemic, socio-technical challenges (e.g., teacher absenteeism, procrastination) that may have led
to such practices. We then explore the role of policy and non-prot organizations in (re)dening the
role of smartphones in teaching by recognizing and demarcating appropriate usage of smartphones
for work. Finally, we discuss the potential to create safe spaces for teachers via appropriate boundary
setting between teachers and parents/students, along with ways to improve teachers’ work lives.
In sum, our contributions to CSCW and HCI4D are:
Qualitative analysis of 70 interviews showing that, although smartphones are useful for
teaching and administrative tasks, teachers’ personal devices were controlled and repurposed
by higher management, used to surveil and monitor teachers’ work, and increased the amount
of work teachers’ were required to perform outside of work hours.
Quantitative analyses of 1,361 survey responses that triangulate our qualitative ndings
by showing that smartphone use signicantly predicts teacher burnout, with technostress
providing a major explanation for this relationship.
We start our literature review by introducing the concept of technostress. We then explore how the
concept of technostress has been developed in dierent elds, such as HCI, CSCW, and teacher
development studies. We then situate our work in prior HCI4D literature focusing on teachers in
low-income settings in order to further develop the concept within teacher work in HCI4D settings.
Technostress: Conceptualization and Development of Technology’s Role in Stress.
nostress is dened as “a specic type of stress that individuals experience due to their use of
Information Systems (IS)” [
]. It is a recently established concept in IS that is increasingly gaining
prominence in the HCI literature [
]. However, the conceptual exploration of technostress started
in early 1980s, with Brod [
] dening technostress as “a modern disease” that occurred when people
failed to cope with new computing technologies. Thereafter, conceptualization of technostress has
been heavily inuenced by decades of development around the concept of workplace stress. But it
is only in the last two decades that technostress has been developed and operationalized into a
strong theoretical concept in occupational settings [6,26,78,95].
The concept of technostress has evolved through three main strands of work. The rst strand
of work looked at identifying technology features that contributed to the feeling of stress by the
workers when interacting with a technology [
]. Ayyagari categorized these features into three
main categories: usability features (e.g., usefulness, reliability); dynamic features that indicated rate
of technology change over time; and intrusive features in technology that enables employees to be
reachable and identiable.
Another strand of research identied and categorized the resultant stress experienced by the
individuals into dierent kinds of technostress [
]. Ragu-Nathan et al. [
] identied ve
forms, namely (a) techno-overload, needing users to work with technology more than required, (b)
techno-invasion, requiring employees to connect to technology to fulll demands even outside
their work time, (c) techno-insecurity, feeling a sense of insecurity about their own knowledge of
technology in comparison to others, (d) techno-complexity, needing to constantly learn changing
technology, and (e) techno-uncertainty, feeling stressed due to fast changing ICTs. A constant
feeling of one of these technostress perceptions contribute to negative outcomes in the individuals
like low productivity, exhaustion, poor performance, and burnout [95].
A nal strand of research has looked at organizational factors that impact technostress perceptions
in dierent ways. For instance, Wang et al. in their study demonstrated how organizations with
centralized structures induce more technostress when compared to the decentralized ones [
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
More recent studies have hinted that characteristics such as surveillance prone culture [
] or
organizations’ expectations of employees’ availability outside work hours [
] could lead to negative
outcomes. Taken together, current research in technostress has been predominantly explored in
traditional IS workspaces leaving a great scope for development in work settings that are not
conned to an oce space [95].
Technostress Research in HCI, CSCW, and Teacher Development Studies.
research in HCI and CSCW has expanded the notion of technostress in new directions. In particular,
one set of research studies has looked at developing novel techniques to cope with technostress from
dierent kinds of technologies. For example, Kiss and Schmidt engaged with interaction challenges
that create technostress in mobile work devices (as opposed to work desktops) to propose design
recommendations around them [
], while studies like that of Moya and Pallud [
] have explored
the use of wearable technology in the context of technostress. A second group of studies have
adapted the technostress phenomena to study individuals in everyday activities, including the
impact of notications on productivity [
], managing private information [
], dealing with online
harassment [
], and managing personal health [
]. Lastly, studies have examined the nature of
technostress, specically the techno-invasive nature of work technologies and management of
work-life balance outside traditional IS work spaces [
]. For instance, Cecchinato et al.
studied micro-boundary strategies used by university lecturers to avoid techno-invasion as they
moved between their teaching, research, and personal spaces. Similarly, Calif et al. explored the
impact of positive and negative technostressors on healthcare workers in Western settings [17].
However, the most relevant research for our work is the exploration of technostress phenomena
in teacher work settings. Within this, several studies have explored the relationship between
teachers’ technology use and technostress. For instance, Joo et al. [
] analyzed the impact of
technostress on teachers’ intent to use technology. Syvänen et al. explored contextual predictors of
technostress among teachers’ work lives [
]. Another set of studies have looked at dierent ways
to alleviate technostress around teachers’ profession. For instance, Ozgur looked at how school
support and technological knowledge in the context of teaching reduced technostress experience
by the teachers [
]. But most of this prior work examining technostress in teacher work is situated
in western contexts, with the majority of the studies relying solely on quantitative methods.
The Need for Exploration of Technostress in HCI4D Settings.
A rich body of HCI4D literature
has examined technology-supported education in low-resource settings [
], with a
growing focus on building tools to support teachers in classrooms and beyond [
]. To name a few examples, Mathur et al. [
] developed a phone-based content
authoring system to help teachers develop teaching aids, Ames examined the One Laptop per
Child intervention in Paraguay [
], and Frias-Martinez et al. evaluated a mobile learning tool in
classrooms in Peru [
]. Focusing specically on teachers’ smartphone use at work, Varanasi et al.
describe how Indian teachers recongure their work practices around technological tools [
while Buabeng-Andoh discussed challenges that hinder technology adoption by teachers in low-
income communities [
]. Relatedly, Cannanure et al. [
] explored how teachers’ aspirations may
impact their smartphone use at work. These studies suggest that smartphones are playing a critical
role in teachers’ work lives, directly impacting their practices in low-income settings [
However, research that examines the direct relationship between teachers’ smartphone use and
technostress in HCI4D is notably absent, with only limited work calling out a need for deeper
engagement on this subject [
]. Our work contributes to this literature by asking:
How does
teachers’ smartphone use impact their technostress at work in low-income schools?
answer this question by discussing the role of smartphones in teachers’ work lives and how
technostress manifests in low-income contexts. It is important to study these work contexts because
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
Investigating Technostress Among Teachers in Low-Income Indian Schools 340:5
teachers in these settings frequently encounter systemic issues, such as teacher absenteeism, high
student-teacher ratios, and poor performance that are very dierent than Western settings [
We conducted an IRB-approved mixed-methods study consisting of 70 interviews and 1,361 survey
responses from teachers who work at a wide range of low-income government and private schools.
The study lasted six months and was conducted while school was in session. All data was collected
just before the COVID-19 pandemic impacted India. In this section, we briey discuss the context
in which our research took place before describing our study methods.
3.1 Background and Research Context
Our work took place in the southern part of India, in collaboration with two partner organizations:
(1) a residential school society of 230 government schools (rural and urban), and (2) a consortium
of 240 low-income private schools. Both organizations are dedicated to improving education in
low-income communities and have existed for over 20 years. The rst author, who did all the
eldwork, was born and raised in the community where the organizations are situated.
The government schools in our study provide free education and safe shelter to students from
low income families, many of whom are rst-generation learners. Although the private schools
in our study do charge fees, these are typically low (US $50 to $500 per year), with these schools
specically catering to the needs of low-income urban communities. Unlike government schools,
which are often located on relatively large areas of government land, private schools are typically
located in a residential apartment with limited physical space.
Government schools are overseen by several layers of higher management, including a secretary,
senior ocials, and regional coordinating ocers (RCO). Individual school principals report to
RCOs who in turn report to the senior ocials and are situated close to the cluster of schools they
oversee. Senior ocials report to the secretary and are situated in a head oce in the capital city of
the State. Although government schools follow the state curriculum for education, the secretary in
the last few years has introduced a few student-centered pedagogical reforms, including, modular
teaching [58], ipped classrooms [103], and after-school clubs.
For private schools, however, higher management is situated immediately above the school
principal without additional hierarchies. Consequently, higher management (in most cases) is
physically located in the same place as the teachers. Typical higher management consists of founders,
funders for an established trust, or a board that established the school. Private schools follow
either national or state curriculum. In both private and government schools, higher management
frequently collaborates with NGOs that focus on improving education.
Becoming a teacher in a government school requires passing a written exam and earning a
degree in education. Teachers earn an average of US$ 650 per month. By contrast, teachers in
private schools do not have written exams or degree requirements (some teachers have just a
high school degree), and earn an average of about US$ 250 per month depending on the grade,
subject, and experience of the teacher. Teachers in these schools sometimes work on contract
in multiple shifts across dierent schools in a day. Despite these dierences, teachers in both
government and low-income private schools experience acute challenges, including (1) teacher
and student absenteeism, creating uneven workloads [
], (2) being overburdened with teaching
and non-teaching duties (e.g., election management, COVID management work) [
], (3)
extremely high student-teacher ratio [
], and (4) lack of equal and regular access to professional
development training [
]. Many teachers are also new Internet users and lack know-how
to operate smartphones [
]. They also frequently share their smartphones with their family
members [
]. In the next section, we describe our mixed-method study that comprise of a)
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
understanding the role of technostress experiences in teachers’ work lives through semi-structured
interviews and b) establishing relationship between teachers’ observed technology use, technostress,
and burnout through quantitative surveys, which were informed by our interview protocol and
prior literature in teacher development [18,106,107].
3.2 Semi-structured Interviews
We conducted 70 semi-structured interviews with teachers from government and private schools
to understand their use of smartphones for work and the benets and challenges they provided.
To recruit participants from government schools, we obtained a list of 54 schools
from our partner organization, and selected 12 schools that provided a range of geographies (rural
and urban) and performance levels. We obtained permission from the school’s management to visit
and interview teachers. To recruit participants from private schools, we sent a WhatsApp message
to school principals via the consortium’s WhatsApp group. Our message described our study and
invited principals to respond. Overall, we obtained permission from seven principals to contact
teachers in their schools. All the schools were located in low-income areas of the city. We invited
all teachers who taught grades 6–10 to participate to ensure consistency in our ndings between
public and private schools that otherwise have dierent curricula in the primary grades. In total,
we interviewed 47 participants from government schools and 23 from private schools, stopping
when we reached data saturation. Table 1provides participants’ demographic information.
Interviews were conducted in-person, lasted between 40 minutes and 2 hours, were
mostly in participants’ local languages (Telugu=49, Hindi=13, English=8), and were audio-recorded
with participants’ consent. Our questions covered four high-level topics, including (1) how teach-
ers currently use smartphones at work/home, (2) their positive and negative experiences with
smartphones, (3) impact of smartphone use for work on private life and vice-versa, (4) dierent
types of coping strategies to alleviate frustrations around smartphone use and (5) dierent support
strategies oered to teachers to reduce stress from smartphone. After each interview, we rened our
questions to include new probes, stopping when we reached saturation. In addition to interviewing
teachers, the rst author participated in a range of school activities, including classroom activities
and meetings between higher management and teachers.
Data Analysis.
Our dataset consisted of 78 hours of audio-recorded interviews and extensive eld
notes. Recordings were translated to English (if necessary), transcribed, and analyzed thematically
using MAXQDA. We began by reading through the data several times and creating an initial set
of codes. This was followed by multiple rounds of open coding. After each round, we used peer
debrieng to rene the codes, resolve discrepancies, and reach consensus [
]. Our nal codebook
(see Appendix A) had 29 codes (e.g., digital vulnerability, excessive workload, peer assistance),
which were clustered into six themes (e.g., worklife balance, emotional labor, and social structures).
3.3 Survey
We complemented our interviews with an online survey. Our goals for the survey were to: (1)
enable broad participation by a large number of teachers from all schools connected to our partner
organizations, and (2) collect data to quantitatively measure teachers’ smartphone use, technostress,
and its impact on burnout. Our survey had the following scales:
Smartphone Use for Work.
This scale had 14 structured questions to capture teachers’ smart-
phone use for educational activities (e.g., lesson planning, in-class activities) and specic apps used
(e.g., WhatsApp, YouTube). The questions were created based on our interview results and prior
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
Investigating Technostress Among Teachers in Low-Income Indian Schools 340:7
Interview demographics (𝑛=70)
School type Government schools: 47 Private schools: 23
Participant type Higher management: 9, school sta: 38 Higher management: 7, School sta: 16
Gender Female: 32, Male: 15 Female: 19, Male: 4
Age (yrs) Min: 28, Max: 54, Avg: 37, SD: 6.4 Min: 19, Max: 50, Avg: 33, SD: 8.97
Experience (yrs) Min: 1, Max: 36, Avg: 10, S.D: 9.45 Min: 2, Max: 22, Avg: 10, S.D: 6.16
Education Bachelor’s: 7, Master’s: 40 High-school: 10, Bachelor’s: 12, Master’s: 1
Survey demographics (𝑛=1361)
School type Government schools: 1246 Private schools: 115
Marital status Single: 171, Married: 1072, Other: 3 Single: 48, Married: 61, Other: 6
Gender Female: 826, Male: 420 Female: 94, Male: 21
Age (yrs) Min: 20, Max: 58, Avg: 36.19, SD: 7.12 Min: 18, Max: 52, Avg: 31.15, SD: 9.12
Experience (yrs) Min: .39, Max: 35, Avg: 8.8, S.D: 7.43 Min: .17, Max:33, Avg: 8.18, S.D: 7.09
Education High school: 12, Bachelor’s: 223, Master’s: 1011 High school: 29, Bachelor’s: 53, Master’s: 33
Table 1. Demographic details of interview (top) and survey (boom) participants from government (first
column) and private (second column) schools.
literature around teachers in the Global South [
]. Response options were adapted from
prior work on social media use scales [104]: from never used (1) to 40 hours or more (9).
To establish validity of this custom scale, we accessed face-validity [
], a useful method that
measures how well a custom-created scale covers the constructs it is supposed to measure. Face-
validity was measured by asking (a) three education researchers, (b) four school administrators,
and (c) ve expert teachers who were not part of our study to rate the scale on a measure of 1
(irrelevant) to 5 (extremely suitable). We received an overall score of 4.72. Cronbach’s alpha for the
scale items was 𝛼=0.84, indicating high reliability.
Teacher Burnout.
To measure teachers’ burnout, we adapted six questions from the Copenhagen
Burnout Inventory (CBI) [
] that was originally designed to measure burnout levels in the service
industry (in prior work, Cronbach’s alpha on subscales were
=0.85-0.87). We carefully adapted the
questions for the teaching profession and simplied it for participants with a limited understanding
of English. For example, in the burnout scale, “Do you feel worn out at the end of the working day?”
was adapted to “I feel very tired at the end of the working day.Responses ranged from never (1) to
every day (7). To ensure validity, we measured Cronbach’s alpha for the scales, which were
for the burnout scale, indicating high reliability.
We measured technology stress (technostress) using Ragu-Nathan et al.’s scale
] (in prior work, Cronbach’s alpha on subscales were
=0.71-0.90). Originally designed for
organizational studies, we adapted two sub-scales that captured technology overload and technology
invasion aspects of technostress. Example questions included, “Because of my smartphone, I have to
do more work than I can manage” and “I have to give up my holiday time to constantly check school
work on my smartphone.Teachers responded with options ranging from strongly disagree (1) to
strongly agree (5). Cronbach’s alpha for this measurement was 𝛼=0.82, indicating high reliability.
Peer & School Support.
We used Lam et al.’s scale [
] to measure teachers’ perceptions of
support from peers and higher management (in prior work, Cronbach’s alpha on subscales were
=0.88-0.91). Two sub-scales—competence support (peer) and collegial support (school)—consisting
of 10 items were adapted to teaching contexts. Example questions are, “My school provided sucient
time to use my smartphone in the classroom” and “Many teachers shared useful resources on how
to use my smartphone at work.Responses ranged from strongly disagree (1) to strongly agree
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
(5). Cronbach’s alpha for these instruments was
=0.83 and
=0.84 respectively, indicating high
Survey Distribution and Data Analysis.
We worked with higher management at private and
government schools to send the survey via WhatsApp to teachers at all schools associated with
our partner organizations. The WhatsApp message included a brief description of and link to the
survey, making clear that the survey was optional, condential, anonymized, and did not provide
any compensation. The survey itself was presented in English. Finally, teachers who had questions
or concerns regarding the study had the option to message the rst author using an embedded link.
Appendix Bprovides the full survey. We received 1623 responses in total. To ensure validity of the
survey responses, we followed standardized cleaning measures, including deleting 171 incomplete
responses, deleting 56 outliers in terms of time completion, and deleting 35 careless responses by
comparing them with reverse coded items [
]. Data cleaning left us with 1361 responses: 115
private school teachers and 1,246 government school teachers. Table 1provides the demographic
details of survey respondents.
As our resultant sample size was suciently large and we were interested in identifying mediation
and moderation eects, we conducted parametric analysis even though our measures did not strictly
follow a normal sampling distribution [
]. A cumulative index was created for each scale by
computing the average of all survey items for each respondent. Analysis was done using SPSS and
Hayes Process package [44].
We found that teachers relied heavily on smartphones for work-related activities including, teaching,
preparation, administration, and interaction with parents and peers. Figure 1shows the average
time spent by teachers and the prominent apps used for dierent activities. On average, they
spent 19.2 hours per week (SD=25.51, median=11) on their smartphones for work. The use of
smartphones for work also extended beyond school hours, with teachers working frequently at
their homes as well. Private school teachers regularly used smartphones during school hours
despite policies discouraging or forbidding phone use on school premises. Such no-use policies,
however, contributed to private school teachers spending signicantly less time than government
school teachers using smartphones for work (
=50052.5 ,
0.001). Despite the issues corresponding smartphone use, our data indicated that the teachers
found smartphone as a critical tool for multiple work activities. We briey unpack these smartphone
uses before describing how smartphones based work impacted their technostress.
4.1 Teaching and Preparation
Smartphones played an important role helping teachers to teach and manage their classrooms.
Teachers used smartphones for nearly 3.5 hours per week for teaching-related activities. Smart-
phones proved to be an eective tool allowing teachers to have “information on ngertips” for
supporting their arguments while showing visualizations, teaching aids, and online videos on di-
cult concepts. In addition to teaching, teachers also repurposed smartphones to manage large and
disorderly classrooms. For example, some teachers described how they threatened badly behaved
students with recording videos of their misconduct and sharing it with the principal, with the hope
that this would deter such behavior. Teacher 64 described how she used smartphones in this way.
“I sometimes try to control misbehavior of students by threatening them that I will record
their activity. Sometimes I start recording video. Sometimes I just point the camera towards
them and not record anything. They get scared and behave well in the classroom. If the
recording goes home, parents punish their child.
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:9
Fig. 1. Average weekly smartphone use by teachers from private & government schools; and popular apps
used for each activity.
Teachers preferred such proactive smartphone-assisted measures over more reactive strategies,
such as giving students detention or making unruly students stand outside the classroom, allowing
them to better manage the classroom without getting strained.
Teaching and managing classes with ecient teaching aids and pedagogical strategies meant
preparing a comprehensive lesson with appropriately curated and easy to understand resources.
Smartphones helped teachers in this process by providing a much needed support at home, where
most of the teachers’ lesson preparation process occurred [
]. In our data, teachers used
smartphones for an average of 5.4 hours per week to prepare lessons. Common preparation activities
included teachers subscribing to dierent apps and online platforms (e.g., local YouTube channels)
that provided localized resources and pedagogical approaches. Prior literature have covered these
positive aspects of technology in detail [
]. Below, we add a complementary perspective
to this literature by showing how socio-technical structures created by school management and
teacher practices when using smartphones at work contributed to multiple forms of technostress.
Control and Surveillance of Teachers’ Smartphone Use.
In an eort to enforce a ‘no smart-
phones at school’ policy, ve out of seven private schools where we conducted interviews required
teachers to submit their personal smartphone to an oce administrator at the start of the day, and
only retrieve them at the end of their shift. To accommodate teachers’ needs for emergency com-
munication, some schools designated senior teachers (called incharge) who were allowed to carry
their smartphones at school and who lent the phone to other teachers in cases of emergency. These
incharge teachers were also tasked with enforcing the ‘no-smartphone-use’ policy inside the school.
Teacher 55, a senior Math teacher, explained that if she found a teacher using a smartphone in the
corridor or a classroom, her job was to report the violation to higher management immediately.
Subsequently, such policy violations were publicly reprimanded by the higher management via
announcements on speakers installed in the school, humiliating the teacher.
Despite the negative consequences, many teachers felt the need to use a smartphone at school
for work and personal activities, and so hid a device in a handbag and sneaked it into the school.
However, they often felt stress and anxiety about being caught or reported to higher management.
Teacher 50 explained:
“I constantly show videos to my students around values like appreciation, condence, etc.
If an incharge sees that I am using a smartphone in the classroom, they think – ‘This
teacher is not teaching. She is always on the phone.’ They sometimes threaten me that
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they will inform the management. I feel bad that they misunderstand me. They don’t even
clarify it with me rst. . . I am often tense because of this.”
In addition to asking incharge teachers to surveil and report teachers who use smartphones at
school, higher management in a few schools also used cameras to monitor teachers’ classrooms
remotely. Out of ve schools that installed the cameras, higher management of three schools
described that these cameras had been installed previously in an eort to address known issues
in low-income schools such as teacher absenteeism and frequent class cancellations [
]. We
saw how higher management re-purposed these cameras to monitor teachers’ smartphone use.
For example, Teacher 64, an incharge, explained how she followed this process to nd disengaged
teachers using smartphones:
“A few teachers want to use the phone at any cost. Now we have cameras in place. So
being an incharge, I also observe with the principal. I don’t conscate any phones myself.
But, I show it to the principal - ‘See madam that teacher is busy on her phone. She is not
managing her students and they are coming out of the classroom.’ We also recommend
teachers to inform their family to call them during school hours only in case of emergency.
These ndings suggest that higher management does not trust teachers to follow the rules
or do their work. This echoes prior work, where eroding trust in teachers was used to justify
micromanagement practices, making teachers feel like objects of surveillance [
], contributing to
loss of privacy, decreased morale, and fears of job security [
]. Although a lack of trust in some
teachers is supported by our data, constant use of technology for surveillance and micromanagement
that all teachers experience creates negative outcomes, such as anxiety and depression, leading to
burnout [
]. Another major issue with such surveillance practices is that teachers’ daily activities
are laid bare for scrutiny not only by the higher management but also by the peer incharges who
work alongside teachers on a daily basis, putting them in a position of power who can take undue
advantage [
]. Several teachers tried to cope with managements’ surveillance practices by learning
where the camera’s blind spots were and sitting there to use their phone with the students, or
turned their back to the camera.
Submitting ‘Digital Proofs’ of Teachers’ Work.
Government schools took a completely dier-
ent approach towards smartphone use during school hours. Unlike private schools, who forbade
smartphone use, higher management at government schools required teachers to use their smart-
phones (WhatsApp) to frequently submit photos and videos of their teaching and other work-related
activities to school principals. Principals then shared the messages with RCOs who forwarded these
messages upstream to senior ocials and secretary. Higher management used these messages to
verify whether teachers were carrying out their duties. Higher management ocer, such as P47,
intended this process to improve teachers’ accountability and presence in classrooms.
However, teachers often found this process stressful, “a form of self-surveillance” where they
are expected to share “digital proofs” of their daily work. Teacher 13 described how she had to
start capturing digital proofs at 8:30am when she organized her students in the assembly. This
was followed by another proof at 10am to show that she was using prescribed student-centered
pedagogical methods while teaching in the classroom. At noon, she had to capture a sele with
her students while having lunch to prove that she physically oversaw the provision of mid-day
meals to students. This was followed by two more digital proofs to show that she conducted the
afternoon session and the after school clubs, respectively. In fact, submitting at least ve proofs was
a commonly reported practice. Moreover, part-time teachers, who worked in two or more schools
in a week, had additional self-surveillance requirements as mentioned by teacher 38:
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:11
“We have to update our tasks on an online Google sheet daily to indicate which classes
we took, for which grades, in which school. We also have to share our live locations in a
WhatsApp group to show that we have arrived at school on time. . . .If for some reason, the
GPS location is not updated, they [school administration] call us to ensure that we have
reached. We have to enable the live location for one hour. Its horrible!!”
Teachers were penalized by the higher management when they did not submit digital proofs of
their work. For example, teacher 4 recounted how he received a memo from the higher manage-
ment citing poor performance when he did not share these proofs regularly. Higher management
considered such photos and videos “evidence of innovation and productivity”, in other words, a
demonstration that teachers successfully incorporated student-centered activities and other lessons
from training programs. They issued teachers with memos when they failed to show such evidence.
An alternative punishment, described by P42 (a senior ocial) involved removing oending teachers
from ocial WhatsApp groups (an action that would be visible to the whole group) if they failed to
post digital proofs; they were added back to the group only after agreeing (oine) to cooperate.
Management positioned their actions as care form of surveillance [
]. Sewelland Barker outlined
how adopters of liberal (care) form of surveillance, similar to the management, believe that surveil-
lance is a legitimate tool and the actions to implement surveillance are justied and even required
to some extent. Management followed these principals to push teachers to be more accountable
by discouraging unacceptable behaviors and achieve “checks and balances” in schools. In reality,
management’s intent to use smartphones to evaluate and manage teachers’ labor via performance-
based measures and targets aimed at excessive accountability only caused more technostress [
Teachers were frustrated that such accountability-driven smartphone activities diverted their
focus from their main responsibility of teaching. They felt stressed about higher management’s
expectations of “showing innovation” and experienced burnout from repeating the activities daily.
These ndings add new insights to prior literature’s limited attention to the connection between
technology use for self-surveillance, especially as a requirement for excessive accountability, and
negative outcomes such as burnout [
]. We build on these ndings and make a stronger case
for associating technology use with burnout using quantitative data in section 4.4.
Teachers were also expected to log their work activities via physical (paper) records. When asked
about the need to create two separate records, teachers said that physical records were only used to
measure long-term work performance, whereas digital proofs were used for short-term evaluations.
Teachers created workarounds to reduce the workload and stress caused by the need to share
proofs. For example, a few teachers reused photos from previous days when they had to cancel a
class or forgot to take photos. Teacher 35 said:
“We have to share photos by 6pm in our school. Because I have to post something and if I
am getting late to catch bus for home, I repost previous day pictures. It is wrong to do this,
but other teachers do this too. Some of them skip important duties, go home, and repost
old pictures.
We also note here that although teachers in government schools were required to use their
personal smartphones to submit digital proofs, there was no ocial recognition of smartphones
as work tools, or accompanying policies setting expectations regarding their use at work. This
extends prior work in other service-based work settings like healthcare, where higher management
expected health workers to use personal phones for work-related tasks, without establishing ocial
policies around their use for work [54].
Challenges with Teaching and Managing Classrooms.
Several teachers described how using
smartphones for teaching actually decreased students’ engagement while increasing teachers’
techno-overload. They believed some students were purposely inactive in class because they knew
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that the information was available online and they could ask teachers to share digital resources with
them later, via their parents’ smartphones. Such requests, often made outside of school hours, put
more strain on teachers at home, aecting their preparation for the next day. Teacher 62 explained:
“If we use smartphones a lot in class, students also take advantage of it. They say, ‘madam,
we did not listen to the lesson properly in the class. Can you please WhatsApp us?’ It
creates more work. A few students ask us to share everything in the group. I then have to
do extra work to search again for resources and send them.”’
Some teachers also described how they were frustrated by students’ eorts to outsmart them
by looking up dicult and impractical questions online and asking them in the classroom and on
WhatsApp. Teacher 53, a Science teacher, explained how she felt angry when students doubted her
expertise on purpose, but suppressed her emotions since she was expected to encourage students
to ask questions. Such incidents contributed to a sense of increased stress among teachers. In
line with work from Heargreaves [
], we found that negative appropriation of technology to
assist stereotyping worsened teacher-student dynamics, resulting in teachers to feel emotionally
exhausted and demotivated.
Using smartphones to show teaching aids or visualizations also created tension as teachers
struggled to protect their private information in front of the students. Several teachers reported
that their personal information got exposed to students when sharing their personal devices with
them, resulting in embarrassment. For example, teacher 29 was embarrassed when mature content
showed up in recommended videos when he was showing a YouTube video to explain a complex
concept. Such incidents not only impacted teachers’ relationship with students, but also added
serious worry for teachers about how students might share their personal information with others,
causing them to be more stressed out.
4.2 Administrative Tasks
Apart from preparation and teaching, teachers also used smartphones for a range of administrative
activities, such as responding to higher management’s circulars, planning extra-curricular events,
and preparing for visitors. Almost all of these tasks occurred over WhatsApp. Most teachers
were part of four or more ocial work-related groups, making WhatsApp an indispensable tool
to manage low-income schools. Our survey analysis also found WhatsApp to be the most used
smartphone app for work, with teachers using it nearly ve hours per week for work assignments
Transition from Paper to Digital.
Teachers found WhatsApp the most suitable platform for
administrative communication because of its ubiquity and familiarity. Take the case of circulars
from higher management. Teachers preferred to receive circulars online over in-person (where
a junior teacher takes the physical copy to each teacher and gets their signature on it). With the
in-person system, P40, a senior ocial at the head oce, mentioned that they used to receive many
complaints from teachers stating that the principals forgot to share the circulars on time. Instead of
sending physical copies of circulars, P40 mentioned how they have recently started emailing digital
circulars to principals to reduce turnaround time. Principals, with the help of their data operator,
translate these circulars into WhatsApp messages, add their own instructions, and share them with
teachers. Teachers felt that the new workow made it easier for them to respond to the circulars
quickly and found WhatsApp more convenient than email for such communications.
However, the shift of administrative work from paper to digital also created challenges that
caused more stress and burnout. For instance, several teachers complained about receiving a barrage
of administrative messages outside of work hours, often with tight deadlines, and sometimes even
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:13
late at night. Teacher 9 described his sense of helplessness and frustration on receiving important
circulars during after school hours:
“Everyday some message comes on the WhatsApp: do this work, do that work. Even if I
am on leave, they expect me to work. Sometimes, they ask me to work as soon as I get
home. We get circulars even on Sundays.
The low eort in posting digital circulars allowed school management to send multiple revisions,
adding to teachers’ confusion, frustration, and burden. For example, teacher 37 shared how he
was about to submit the original requirements of a circular, when he received an amendment that
invalidated his previous work. Teachers also felt annoyed when higher management sent follow-up
messages on WhatsApp groups tagging teachers and using labels like ‘siren message’, ‘most urgent’,
very important’, or ‘answer immediately’. The fear of not responding to such urgent messages
pushed teachers to constantly check WhatsApp, even in their personal time.
These ndings suggest that smartphones enabled higher management to “speed-up” the work
creating techno-overload and extend teachers’ expected working hours well into their personal
lives, creating techno-invasion [
]. We connect here to work in other service sectors such as
aviation [
], health [
], white-collar desk jobs [
] and ridesharing services [
] that showed
how employers constantly found opportunities to speed-up the work due to the increased demands
of the industry. This became a source of appraisal for workers’ technostress, who experienced
depletion of their resources, and subsequently failed to perform the work expected of them. We see
similar issues with management moving paper-based administrative work to WhatsApp. This shift
provides management with opportunities to assign work to teachers with tight deadlines, pushing
teachers to work faster to meet management’s targets. These demands deplete teachers’ resources
and increase their stress levels as they struggle to meet management’s expectations.
Teachers with limited understanding of English also had to rely on others to understand circulars
from higher management. At school, most communications happened in local languages and
teachers often discussed circulars with each other. But at home, in the absence of such scaolding,
some teachers felt inadequate as they had to request help from family members and wait for their
availability. This created feelings of frustration and inadequacy contributing to technostress in the
form of techno-complexity [
]. For example, teacher 64 recounted how she had to approach her son
or her daughter for help, depending on who was willing to help at the time. Similarly, teacher 54
said that a senior teacher asked her to translate text messages and circulars into the local language.
Teachers also felt that they did not receive support from school administration to manage their
workload and technostress. Although higher management conducted professional development
training programs for teachers (1–3 times a year), topics that dealt with technology stress and
work-life balance were notably absent. In addition, a senior ocial (P46), while describing training
programs, justied the absence of topics like stress management by expressing how they prioritized
and only oered training to “passionate” teachers who teach and perform well.
Work-life Balance.
Most teachers felt that higher management was insensitive towards their
work-life balance and misused WhatsApp to indiscriminately assign more work to them. These
messages severely interrupted the personal lives of teachers. For example, teacher 9 had to leave a
friend’s wedding in haste to meet an ocer after seeing a message that the management sent at
the last minute. Some teachers reported having arguments with family members who struggled to
understand why they had to be “online always on WhatsApp. For example, teacher 22, a young
woman, explained how her parents thought that she was having an aair:
“My family does not understand that I do work on WhatsApp. Being a young woman, my
parents raise several questions around my work. I regularly get circulars outside work
hours on WhatsApp. Therefore, I am often online on WhatsApp. I tell my family that I am
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busy with work but when they see me online.. .they start questioning ‘what is she really
working on at 10:30pm’. I have to explain myself a lot.
Many teachers felt that they had an unhealthy work-life balance, primarily due to intrusion of
work-related messages in their private time. Women teachers believed that they had more family
responsibilities at home compared to their male counterparts, making their family life more stressful.
Our survey analysis supported this observation. We found that women reported signicantly more
burnout than men (
=-2.379 ,
017). These ndings
corroborate prior work’s results on techno-invasion created by the management through the use of
emails, text messages, or calls. [
]. In contrast to teachers, four higher management
ocers we spoke with described how they considered it to be a teacher’s responsibility to maintain
their own work-life balance.
Teachers in our study proactively searched for what Tarafdar et al. called threat coping responses
] to cope with techno-invasion and separate their professional and personal digital life. For exam-
ple, a tech savvy Hindi teacher described how she helped many teachers, including the principal, to
implement a hack that enabled running multiple instances of WhatsApp simultaneously. The hack
allowed them to separate work and personal conversations, and apply dierent notications and
visibility settings to each instance. A few teachers installed custom apps that enabled notications
only from people in their contact list, thereby avoiding stress related to anticipation of messages
from higher management.
Many teachers also disabled read receipts (check marks that indicate a message’s delivery and
read status), ‘last seen’, and ‘online’ features on WhatsApp to ensure that the higher management
could not claim that they knew teachers were online and therefore knew about the work assigned
on WhatsApp. A few teachers reported taking advantage of low technological awareness and skills
of the principal to avoid work in their personal time. For example, when teacher 46 ignored the
principal’s messages outside work hours, she told the principal that her “phone got corrupt..
4.3 Interaction with Peers and Parents
Teachers often used smartphones to interact with their peers and students’ parents, spending
an average of nearly 3.6 hours per week on such communications. Interestingly, both activities
accounted for 13% each of the total usage time. In the case of peers, smartphones created stressful
situations when peers became competitive with each other and used smartphones as a tool to
show other teachers in a bad light. Some teachers reported how jealous peers recorded their digital
conversations on WhatsApp or took photos of them relaxing in classrooms, only to share these
with higher management. For example, Teacher 23 shared how a peer recorded a WhatsApp call
in which she criticized higher management and sent it to them. Teacher 26 described how her
colleague transferred to another school due to similar challenges:
“She was not in good standing with this peer of ours. The peer took pictures to expose her
negligence at work and shared them with higher management. There were egos involved.
Teacher 17 explained why he acted against a group of peer teachers:
“Those teachers regularly came late to classrooms. I captured proof [of their absence] and
sent them to the principal on WhatsApp. The principal then questioned them citing the
WhatsApp message. .. .On WhatsApp, the messages are recorded with a proper date and
time. Principal can then see in the picture that they were late and that can act as proof.
We also found cases where teachers found sensitive information stored on peers’ smartphones.
Teacher 18 shared:
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:15
“I was working with a new person in school management team. I had to share a few photos
of an event and he gave me his phone for transferring the photos. While going through
the gallery, I saw his photos with a woman teacher from our school.
In some cases, teachers reported being blackmailed by peers in exchange for keeping private
information secret. Teacher 61 shared how her colleague told another teacher to do more work
when the colleague came across messages in which the teacher was critiquing higher management.
Similar adversarial use of technology has been seen in other workplace settings too [98].
Teachers perceived these peer-based practices as a direct threat to their positive relationship
with higher management, impacting their overall standing. These ndings extend the limited
understanding of how technology-based monitoring is conducted by peers due to competition [
The negative perceptions also made teachers hesitant to share their inner feelings with peers at
their own school. Teachers were worried that any discussion on stress, burnout, or workload could
be taken out of context and restricted themselves to sharing only positive feelings with peers, so
that they comply with higher management’s expectations of expressing care towards their peers.
Communicating with Students’ Parents.
Many schools required teachers to create WhatsApp
groups to share announcements with students’ parents instead of writing remarks in students’
diaries. Teachers found digital communication easier and faster, and appreciated how some ad-
ministrative work was more convenient to do on WhatsApp for both parents and teachers. For
example, P31, described how parents in government schools need to physically visit the school
to apply for a leave for their child. Before WhatsApp, they traveled all the way to school only to
realize they received a rejection. Now parents submit the necessary paperwork via WhatsApp and
receive a decision in advance.
While teachers saw benets of communicating with parents on WhatsApp, they felt irritated
when parents disrespected their personal boundaries. Teachers expressed concerns about being
“too accessible to parents” and shared instances of aggression from parents. For example, teacher 21
shared how a student’s drunk parent sent her a voice message saying “all teachers in the government
school should be dosed with kerosene and burnt, when she denied a leave to the student. Such
stressful incidents caused serious harm to teachers’ wellbeing and increased burnout.
4.4 The Relationship Between Smartphone Use, Technostress, and Burnout
Overall, our qualitative ndings demonstrated several instances of technology use by teachers that
contributed to technostress. We also found instances of technostress that contributed to burnout
among teachers. To support our exploratory evidence of the connection between technology
use, technostress, and burnout, we conducted a quantitative study to systematically explore the
relationship between the three concepts. In particular we explore the following questions:
RQ-1: Does technology use predict high levels of burnout?
RQ-2: Is the relationship between teachnology use and burnout explained by technostress?
Does school and peer support moderate the relationship between technology use, tech-
nostress, and burnout?
To answer these questions, we draw from data collected via our 1361 survey responses. On a
high-level, our quantitative analysis supports our qualitative ndings. On average, private and gov-
ernment school teachers used smartphones for nearly 16 hours and 19 hours per week, respectively.
As mentioned previously, since most private schools prohibited teachers from using smartphones
in classrooms, we found a signicant dierence between the overall number of hours government
and private school teachers used smartphones for work (
(govt.)=1246, 𝑝<0.001).
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Fig. 2. Path analysis model showing how technostress (M) completely mediates the relationship between
smartphone use (X) and burnout (Y). Technostress is a major explanatory factor in the relationship.
Smartphone Use Predicts Burnout.
As discussed above, teachers shared how using smartphones
during and after school hours added to their workload. Sending digital proofs, receiving after-hours
memos from higher management, and managing parents in their personal time led many teachers
to feel burned out. Survey data indicated that nearly 60% of teachers felt burned out more than
once a month. Among these teachers, 29% of teachers experienced burnout once a week and 14%
more than once a week. We also found that government school teachers experienced burnout
signicantly more frequently than private school teachers (𝑈=55404, 𝑍=-4.03, 𝑝<0.001).
To examine if there is a direct link between smartphone use and burnout, we conducted a
linear regression analysis using the log-transformed number of total hours spent by teachers using
smartphones for work as the independent variable and the frequency of feeling burned out as the
dependent variable. Our analysis found that smartphone use by teachers signicantly predicted
how often they felt burned out (𝑏=.23, 𝑡(1359)=3.54, 𝑝<0.001).
Technostress Mediates the Relationship Between Smartphone Use and Burnout.
Next, we
investigated the role of technostress in the relationship between smartphone use and burnout. We
began by conducting a linear regression analysis to examine the relationship between technostress
and burnout, and found that technostress levels among teachers signicantly predicted how often
they felt burned out (𝑏= .73, 𝑡(1359)=18.33, 𝑝<0.001).
Although both groups of teachers experienced high levels of technostress, we found that gov-
ernment school teachers experienced signicantly more technostress than private school teachers
=0.003). To see if government school teachers were more stressed because they
used smartphones for work more than private school teachers, we conducted a linear regression
analysis to predict the eect of smartphone use on technostress. We used the logarithmic value of
the hours teachers spent using smartphones for work as the independent variable and the tech-
nostress index as the dependent variable, and found that smartphone use signicantly predicted
technostress (𝑏=.21, 𝑡(1359)=5.37, 𝑝<0.001).
Next, we conducted mediation analysis using path analysis [
] to investigate whether technos-
tress levels (
) mediate the relationship between smartphone use (
) and burnout frequency (
We found that technostress fully mediated the relationship between smartphone use and burnout
(𝑋𝑀𝑌,𝑏=.21, 𝑡(1359)=5.37, 𝑝<0.001). Technostress accounted for 65.2% of the relationship
between smartphone use and burnout (
) and 68.4% when we controlled for age, gender, and
school type. These results suggest that technostress provides a major explanation of how teachers’
smartphone use predicted burnout frequency. Figure 2shows the results of our linear regression
and mediation analyses.
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:17
Fig. 3. Moderated-mediation model showing how peer support (W) and school support (Z) significantly
controlled the relationship between smartphone use and technostress (
). However, only school support
(Z) significantly controlled the relationship between smartphone use and burnout (𝑋𝑌).
Support Moderates the Relationship Between Smartphone Use, Technostress, and Burnout.
Finally, we conducted a moderated mediation analysis [
, Chapter 11] to measure whether peer
and school support has moderating eects on the predictive relationship between smartphone use,
technostress, and burnout (i.e., the overall model shown in Figure 2). In particular, we examined
how peer support and school support inuence the relationship between: (1) smartphone use and
technostress, and (2) smartphone use and burnout. We controlled for age, gender and school type
to generalize the results across dierent teacher demographics.
Our results (see Figure 3) show that both peer support (
) and school support (
) act as
moderators for the relationship between smartphone use and technostress (
) with signicant
interaction eects of peer support and smartphone use (
=0.015) as well as
school support and smartphone use (
=0.018). These results indicate that, as
peer support and school support increase, they reduce the eect of smartphone use on technostress.
On the other hand, we found that only school support (
) acts a moderator for the relationship
between smartphone use and burnout (
) with signicant interaction eects of school support
and smartphone use (
=0.003), meaning that an increase in school support
reduces the eect of smartphone use on burnout. These quantitative results support our qualitative
ndings and suggest that creating both formal and informal support structures for teachers could
help to reduce their stress and burnout.
Our ndings depict a concerning landscape that contrasts the general techno-optimism associated
with the adoption and use of smartphones in HCI4D settings [
]. Although HCI and
Organizational Studies research in the Global North have recognized the potential for technology to
induce strain and burnout in work settings and hamper work-life balance (e.g. Right to Disconnect
policy) [
], very limited conversations (e.g., Karusala et al.’s work around health care
workers [
]) exist around similar themes in HCI4D settings. Instead, most prior work in HCI4D
has focused on improving productivity, eciency, and access, without engaging deeply with the
possible negative implications of technostress around such technology integration. This is especially
concerning in educational settings in the Global South because, unlike resource-rich settings where
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
teachers’ use of technologies may have established norms and policies, smartphone use by teachers
in the Global South does not have clearly dened norms, policies, or checks to protect teachers
from technostress. In this Section, we (1) expand the technostress phenomenon to accommodate
work settings in HCI4D contexts, (2) discuss the ethical issues surfaced as a result of dierent
technostress situations in these work contexts, and nally (3) propose avenues for beginning to
address the technostress that teachers experience.
Expanding Technostress Beyond IT Oces: Technostress in HCI4D Work Settings.
mentioned in Section 2, most prior research around technostress has investigated the phenomenon
in traditional oce-based settings [
]. Work-based technology in these settings is provided,
and therefore recognized, by the management. This provision also allows management the ability to
control these devices through established internal checks and required demarcations (in the form of
software) to regulate the expected employee behavior in work settings. This is a common scenario
in call centers where employers routinely install applications to monitor and manage employee
behavior [
, Chapter 7]. This is in contrast to most work settings in HCI4D contexts, where
employers often do not provide work devices to employees. Instead, employees, like teachers in our
study, repurpose their own personal devices (e.g., smartphones) for work to meet the increasing
demands of productivity. Additionally, these workers share ownership of these devices with their
family (unlike Western settings), limiting device availability outside work hours [
]. As a result,
these smartphones do not attain ocial status of work devices. Moreover, as these devices are
personally owned by the teachers, management cannot control and monitor these devices directly
through internal checks. Consequently, we show how these dierences in “work” technologies
between Western and HCI4D settings extend the concept of technostress in multiple ways.
First, some forms of technostress that have come up in the previous literature did not occur in our
ndings. For instance, the fact that teachers repurposed and brought their personal smartphones
as work devices meant that teachers were familiar with the simple technology operations that
were required for school work, such as using apps for teaching, or completing administrative
requests on WhatsApp. As a result, unlike prior work [
], we saw very few instances where
teachers felt stressed by frequent updates to their smartphone apps (techno-uncertainty) [
]. We
hypothesize that the Play Store updates of these apps were so incremental and small that teachers
did not perceive the new features as stressors [
]. Similarly, managements’ lack of recognition
of smartphones as work devices along with their emphasis on syllabus completion and student
development meant that we did not nd instances where teachers felt that technology (non)-use
might impact their job security, especially to other peers (techno-insecurity).
Second, some of our ndings do not t with the current conceptual vocabulary of technostress.
For instance, management’s lack of internal technological checks on teachers’ smartphones was
compensated by external socio-technical regulations like using peer-surveillance to curb smart-
phone use. Management positioned these actions as care forms of surveillance [
]. Sewell and
Barker [
] outlined how adopters of liberal (care) forms of surveillance, similar to the management,
believe that surveillance is a legitimate tool and the actions to implement surveillance are justied
and even required to some extent.
In reality, these external regulations were seen by teachers as enforced social structures designed
to curb their agency and produce more technostress [
] at work. This contrasts internal technological
checks established in IT oces (e.g., activity monitoring apps) that employees consider as part of
their job contract. Consequently, these structures created new types of techno-stressors. One such
technostress developed when teachers felt that they were in constant conict with the management
to receive permission and use their smartphones for work productivity. This form of technostress,
in which employees are in constant stress to gure out if a certain technology can be used for work
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
Investigating Technostress Among Teachers in Low-Income Indian Schools 340:19
purposes (or not), is not represented in prior literature of technostress. We propose this type of
technostress as techno-permissibility. In our study, we saw how certain teachers in private schools
experienced this stress when the management denied permission to use smartphones for work
even though teachers felt that smartphones were an indispensable work tool. The constant fear of
whether or not to use smartphones for teaching contributed to teachers’ technostress.
Lastly, implementation of socio-technological structures by the management also meant that
certain forms of technostress were observed unusually more in our ndings than they were covered
previously in the literature . For example, one form of technostress that appeared frequently in
our data was the perception of techno-overload, which was caused by implementation of self-
surveillance structures on WhatsApp. Another form of technostress that we observed frequently is
techno-invasion, which occurred when parents had access to teachers through WhatsApp. We also
observed techno-invasion in instances where teachers had to be online for administrative work.
Ethical Issues Raised in Our Findings.
Our ndings also depict a number of ethically question-
able work practices utilized by both higher management and teachers to navigate the ambiguity
of smartphones as work devices. Even though, as researchers, our primary obligation is to report
these ndings, it is also our responsibility to engage with the underlying socio-technical challenges
around such ethically questionable practices. For instance, one set of unethical uses of smartphones
occurred when higher management used surveillance techniques in an eort to make teachers more
accountable. While private schools chose surveillance using CCTV cameras in classrooms, higher
management in government schools repurposed teachers’ smartphones as a self-surveillance tool
to track and monitor their work. It is important to understand these decisions taken by the higher
management in a broader cultural context. These schools face serious teacher-related problems,
such as absenteeism, teaching procrastination, and distraction from teaching, that perhaps led to
adoption of such extreme measures [
]. In parallel, these schools often prioritize students in ways
that sometimes overlook teachers’ needs. However, our work shows how higher managements’
practices are detrimental to teachers’ work lives, potentially impacting students’ educational growth
in ways that contradict the organizations intended aims.
To a lesser extent, we saw how teachers unintentionally exposed personal information (even
mature content) to students while using their smartphones as teaching aids. They also appropriated
smartphones as potential surveillance tools by threatening to record students’ behaviors. These
activities have the potential to cause psychological harm to students, which could be worsened if
the device used to record the video is compromised. On the other hand, lack of teaching resources
pushes teachers to depend on smartphones as a major teaching resource, which is bound to result
in situations where teachers’ work and private information mix, leading to the challenges we saw.
Overall, these are alarming ndings. There is an urgent need, not only from our community of
HCI4D researchers, but also the broader ecosystem of education, government, and policy makers
to come together and tackle the underlying challenges around technology use. One such challenge,
as Toyama points out, is that the technology can only amplify the underlying intent to use the
technology [
]. As seen in our study, the intentions of dierent stakeholders may be in conict
with each other. In the following sections, we advocate for solutions that embrace the notion of
caring [
] for and about teachers to empower them within the local cultures and contexts they
work in, instead of adopting solutions that oppose those structures [93].
The Role of Policy & NGOs in (Re)dening the Role of Smartphones in Teaching.
adoption of smartphones for a wide range of teachers’ work activities has happened rapidly, with
platforms like WhatsApp, that teachers already use for their personal communications, suddenly
playing a large role in their day-to-day work. Indeed, the number of hours that teachers reported
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
using smartphones for work suggests that these tools are now just as important as other, more
traditional work tools (e.g., classroom teaching aids, textbooks, registers, etc.) [36].
However, smartphones as ambiguous work tools, occupy a gray area in which they are some-
times treated as work tools (e.g., higher management requiring their use to submit digital proofs),
sometimes seen as personal devices (e.g., banned from work in private schools), and sometimes a
mix of the two (e.g., expectations from teachers to respond outside of work hours). As a result, most
of the work that teachers do outside of school on these devices becomes invisible work that is not
acknowledged by higher management, causing emotional strain in their work and personal lives.
Additionally, these forms of invisible work no longer represent teacher work and therefore have
the potential to be ignored by the designers who are designing for teachers [
]. At the same time,
smartphones enabled management to easily scrutinize work that was already visible leading to
extreme accountability for teachers [
]. We recognize that this problem cannot be solved overnight
and requires systematic planning and deliberation at a policy level as well as concrete actions at
local school levels.
First, at the policy level, there is a need to recognize and demarcate appropriate (and inappropriate)
usage of smartphones in teachers’ work lives in national-level policies and frameworks like the
2020 National Educational Policy (NEP) [
]. The current policy not only fails to include such
directions, but also provides vague recommendations for promoting teacher training programs via
smartphones that may impact teacher professional wellbeing: “These [training] programmes may
be run through digital/distance mode. . . as well as smartphones, allowing teachers to acquire Early
Childhood Care and Education qualications with minimal disruption to their current work” (Clause
1.7, page 8). Since state governments derive their policies from national frameworks, addressing
the role of smartphones at a national level will likely trickle down to state-level policies as well.
In the short-term, grassroots NGOs that work with low income schools (also called support
organizations [
]) can engage school higher management to initiate dialogue to renegotiate, and
then reinforce, acceptable roles for smartphones in teachers work, with these roles agreed on and
acceptable to both teachers and management [
]. NGOs are often in a good position to do this
because they bring in additional skills and resources that may be benecial for higher management.
For example, NGOs may provide technological and domain expertise, along with a commitment to
eective smartphone-based interventions for teachers [
]. Thus, NGOs can create awareness
around the role of smartphones in teachers’ work lives. Such negotiations can render visible some
of the currently invisible work teachers do using their smartphones [90,91].
Creating Safe Spaces for Teachers through Boundary Setting.
The need to establish and
maintain healthy boundaries is a key requirement for jobs involving emotional labor [
including teaching [
]. Before teachers possessed smartphones, if students’ parents wanted to
interact with a teacher, they needed to visit the school in-person, during school hours, and obtain
permission from an administrator before gaining access to the teacher. This physical separation
was important to ensure that teachers can perform their duties without constant interruption from
students’ parents. However, the always-on nature of smartphones, combined with parent-teacher
WhatsApp groups that expose teachers’ personal contact information, have reduced the distance
between teachers and parents/students, enabling parents to directly contact teachers at any time,
whether to request clarication about homework, ask additional resources, or threaten the teacher
when parents are unhappy with them. The adoption of digital communication has resulted in
teachers losing the safe space aorded to them by physical, in-person interaction.
This suggests a need for mechanisms that (re)establish safe spaces for teachers by creating ap-
propriate digital boundaries between teachers and students/parents. Demonstrating a commitment
to creating and enforcing such boundaries could provide a key opportunity for higher management
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:21
to show care for teachers. For example, mirroring the physical world, higher management might
assign a school administrator to act as a digital liaison to mediate communication with parents and
shield teachers. This can be facilitated via the use of a newly-available WhatsApp business app with
a separate work-only SIM that administrators use for correspondence with parents. Many built-in
features of WhatsApp business, such as an “away message” (automatic message when the device is
oine) or setting explicitly visible “work-hours”, can encourage parents to follow the announced
times, reducing techno-overload and techno-invasion. WhatsApp business also provides an API
that opens up the possibility for future research to examine the extent to which such mediation
could be achieved by conversational chatbots. Using chatbots as mediators may prevent parents
from knowing teachers’ personal phone numbers and could also, for example, store messages sent
outside of work hours until the next morning.
More broadly, such interventions can enable teachers to reduce technostress and focus on
improving dierent aspects of their wellbeing at work (e.g., mental health, worklife balance) [
Explicitly acknowledging the importance of teacher wellbeing, and providing structures that reduce
technostress, could help teachers to feel less alienated [67] and improve their overall work lives.
Future Pathways: Teachers’ Technostress in the Post-COVID Era.
Lastly, the onset of the
COVID pandemic has drastically altered the work of teachers. This is particularly true for low-
resource schools, where months-long lockdowns have pushed almost all of the teachers’ work
online. We now reect on some of the long-term changes, discuss how these changes may impact
teacher technostress, and what we, as a research community, might do about it. The pandemic is
already contributed to a shift from school to home-based teacher work practices, while drastically
reducing the visibility management has into teachers’ work. It may also lead to teachers needing
to intersperse their work with other household chores and childcare duties, extending their work
hours and further blurring their work and personal lives.
The lack of appropriate norms around online work, combined with added invisibility, may push
management to incorporate demand surveillance “proofs”, such as “always be on a video call”, or
possibly adding online monitors who audit teachers’ activity on teaching apps. Future research is
needed to carefully study these changes, and the resultant technostress, to understand their impact
on teachers’ wellbeing. We will also need interventions to counteract the technostress that will
arise due to this pandemic shift. Teachers are also likely to face increased work burdens from other
stakeholders as well. For instance, teachers may be expected to provide greater emotional support
to students, who are also dealing with uncertainty and anxiety during the pandemic. Online classes
may enable parents to take advantage of being present in the same place as their children who
are taking the online classes, facilitating monitoring and scrutinizing of teachers around their
classroom engagement. Such situations could easily lead to humiliation of teachers in front of their
class, impacting their self-esteem. To avoid these situations, management will need to work even
harder to ensure appropriate boundaries between parents and teachers.
This paper describes a mixed methods study that analyzes the impact of teachers’ smartphone use
on their perceived technostress. Although smartphones are convenient for administrative tasks and
helpful for lesson preparation and teaching, we nd that their use signicantly predicts burnout
among teachers, with technostress providing a major explanation for this relationship. Higher
management controlled and repurposed teachers’ own smartphones to surveil and monitor their
work, and demand that they complete administrative work quickly, often outside of work hours,
contributing to technostress. Taken together, our ndings contrast the general techno-optimism
that surrounds the use of smartphones in education settings in HCI4D. We also extend the concept of
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
technostress in low-resources work settings and suggest opportunities to rethink how smartphone
use for work might be restructured to improve teachers’ professional wellbeing.
We thank the management for providing generous access to their schools for research. We are
also grateful to the teachers, such as Chitrangada Chakraverti, for spending their invaluable time
sharing their experiences and providing feedback on our study.
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Investigating Technostress Among Teachers in Low-Income Indian Schools 340:27
Theme / Code Count
Stressors (27.57%) 295
Digital proofs & surveillance 73
Digital vulnerability 58
Excessive workload 45
Issues of trust 35
Non-digital stressors 30
Additional tech dependencies 23
Relationship between the peers 22
Pressure to adopt smartphone 10
Social structures (22.14%) 237
Digital regulations 62
Digital hacks 55
Change in habits 45
Image manipulation 30
Interaction w/ parents 25
Gender dynamics 20
Engagement (17.75%) 190
Teacher strategies 59
Peer connectedness 55
Peer assistance 36
Quicker workow 35
Encouragement 5
Worklife balance (14.86%) 159
Worklife balance issues 68
Always online/blurring spaces 48
Hybridity of smartphone 43
Coping mechanisms (9.53%) 102
Digital mechanisms 42
Social mechanisms 25
Physical mechanisms 15
Mental constructs 15
Higher management assistance 5
Emotional labor (8.13%) 87
Change in emotion management 55
Emotional aspects of smartphone 32
Table 2. The complete codebook that resulted from our analysis of qualitative interviews, showing six themes
(bold) and 29 codes, including the prevalence (%) for each theme, and the total count for each theme/code.
(The count for each theme is the sum of the counts of all codes within that theme.)
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
B.1 Demographics
Instructions. Please answer the following demographic questions:
Q1.1 What is your age?
Q1.2 What is your overall teaching experience? (years)
Q1.3 What subject(s) do you teach?
Q1.4 What is your highest qualication?
Q1.5 Which gender do you identify with?
Q1.6 What is your marriage status?
B.2 Smartphone use: Activity
Instructions. For the following questions, please recollect your average smartphone use in the last 12 months for dierent
school duties and select your answer:
School preparation work using smartphone, in a week (E.g. preparing lesson plans, nding activities for students,
Teaching a concept using smartphone, in a week (e.g. Explaining a chapter through a new activity to students in
Q2.3 Sharing smartphone with students to help them do activities in class, in a week.
Q2.4 Administrative tasks using smartphone, in a week (e.g. duties given by a circular).
Q2.5 Managing parents using smartphone, in a week (e.g. solving parents’ doubts).
Q2.6 Interaction with other teachers using smartphone, in a week (E.g. helping other teachers in subject doubts).
Response options: Never used (1), Less than 1 hour (2), 1-2 hours (3), 3-5 hours (4), 6-9 hours (5), 10-19 hours (6), 20-29
hours (7), 30-39 hours (8), 40 hours or more (9).
B.3 Smartphone use: Apps
Instructions. For the following questions, please recollect your average use of smartphone apps and technologies for
instruction in the last 12 months and select your answer. (E.g. lesson preparation, lesson delivery, evaluation, work
communication and administrative record keeping):
Q3.1 Average WhatsApp use for work, every week.
Q3.2 Average YouTube use for work, every week.
Q3.3 Average Byjus use for work, every week.
Q3.4 Average use of Google search for work, every week.
Q3.5 Average Wikipedia use for work, every week.
Q3.6 Average Projector use for work, every week.
Q3.7 Average Digital tablet use for work, every week.
Response options: Never used (1), Less than 1 hour (2), 1-2 hours (3), 3-5 hours (4), 6-9 hours (5), 10-19 hours (6), 20-29
hours (7), 30-39 hours (8), 40 hours or more (9).
B.4 Burnout
Instructions. For the following questions, please recollect your teaching life in school to answer how frequently you
experience them in your life:
Q5.1 I feel super tired at the end of the working day at school.
Q5.2 I feel that working daily as a teacher is very tiring for me.
Q5.3 I have enough energy for family and friends during leisure time. (reverse coded)
Q5.4 My work as a teacher is emotionally very tiring.
Q5.5 My work as a teacher frustrates me.
Q5.6 I feel burdened because of the work I do as a teacher.
Response options: Every day (7), A few times a week (6), Once a week (5), A few times a month (4), Once a month (3), A
few times a year (2), Never (1).
B.5 Technostress
Instructions. For the following questions, please recollect use of smartphone for your work purposes (i.e. preparation,
teaching, and admin work) to answer whether your agree or disagree with the statements:
Q6.1 Because of my smartphone, I have to do more work than I can manage.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
Investigating Technostress Among Teachers in Low-Income Indian Schools 340:29
Q6.2 Because of my smartphone, I have to work with very hectic time-table.
Q6.3 I am forced to change my old work habits to work with my smartphone.
Q6.4 I have a higher school burden because it is dicult to use my smartphone.
Q6.5 I must be in touch with my work even at late night due to my smartphone.
Q6.6 I have to give up my holiday time to constantly check school work on my smartphone.
Q6.7 I feel my personal life is being occupied by my smartphone.
Response options: Strongly agree (5), Somewhat agree (4), Neither agree nor disagree (3), Somewhat disagree (2), Strongly
disagree (1).
B.6 Peer support
Instructions. For the following questions, please recollect how other teachers have supported your smartphone use in
school work (preparation, teaching and admin duties) to answer whether your agree or disagree with the statements:
Q7.1 Many teachers encouraged me when I faced diculties in using my smartphone for work.
Q7.2 Many teachers shared useful resources on how to use my smartphone at work.
Q7.3 Many teachers shared their smartphone experiences to help me use my smartphone for work.
Q7.4 Many teachers cared about the challenges I faced while using my smartphone in work.
Q7.5 Other teachers and I made an eort together to use our smartphones in our work.
Response options: Strongly agree (5), Somewhat agree (4), Neither agree nor disagree (3), Somewhat disagree (2), Strongly
disagree (1).
B.7 School support
Instructions. For the following questions, please recollect how other teachers have supported your smartphone use in
school work (preparation, teaching and admin duties) to answer whether your agree or disagree with the statements:
Q8.1 My school gave instructions on how to use my smartphone for lesson planning.
Q8.2 My school gave enough training to us on how to teach using smartphone in the classroom.
Q8.3 My school provided sucient time to use my smartphone in the classroom .
Q8.4 My school understood my work pressure and gave me freedom to use my smartphone in school work.
Q8.5 There was good coordination in my school using smartphones so that I could complete my task smoothly.
Response options: Strongly agree (5), Somewhat agree (4), Neither agree nor disagree (3), Somewhat disagree (2), Strongly
disagree (1) .
Received January 2021 ; revised April 2021 ; accepted June 2021
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 340. Publication date: October 2021.
... These gaps are more pronounced in low-income regions in the Global South where many women live in strong patriarchal systems that limit their voice, agency, mobility, and autonomy [68,72,85]. Although women's economic empowerment has been shown to reduce gender gaps, their labor force participation continues to remain low because of barriers like low levels of education [65], unpaid care work and domestic duties [9], and long work hours [93]. In India, the focus of our study, female labor participation is the lowest in South Asia, with four out of fve women not engaged in the labor force [56]. ...
... There are several barriers that contribute to their limited participation, such as low levels of education, societal norms that limit their mobility, and domestic duties, among others [9]. Even when women are a part of the workforce, they experience several challenges, such as limited resources [64], unequal pay [82], lack of support and encouragement [51], long and irregular work hours [93], workplace harassment [76], and frequent disruptions due to unforeseen family circumstances [17]. These challenges impact the labor participation of women much more than men, often making it difcult for women to take up diferent forms of work. ...
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