Will EdTech go the way of the gig economy?

[By Aditi Surie and Krishna Akhil]

The forced push towards digitization of schooling-related activities due to the onset of the COVID-19 pandemic has accelerated growth of Indian education technology (EdTech) companies. The sector plugs into and supplements the legacy of after-school tutoring and extracurricular activities by building businesses that take these services online. 80% of India’s school teachers are women as reported in the National Sample Survey Office (NSSO) and Quarterly Employment Surveys. Education serves as one of the biggest employment bases for women from scheduled caste communities. In the accelerated environment for online education since the pandemic, the sector has seen investments of 2.2 billion USD, roughly half of the 4 billion USD that has been raised by EdTech companies in India in the last five years.

Given this rise, it is important to ask what business models these companies follow, and how this impacts the educators who ultimately do the teaching. Will EdTech go the way of the gig economy? Is EdTech work structured like Uber work? Since the pandemic, many delivery people and taxi driver woes have been made public. If EdTech companies start to adopt the business models of gig platforms like in food delivery, or the ride-hailing sector, then how do we see the future of our educators? What does EdTech do to the nature of the teacher’s work? How do the patterns of the Indian education sector relate to the ways in which we think about the kind of employment EdTech companies offer educators using their platforms?

These are important questions to ask as we see major disruptions in one of the most established and formal sectors of women’s employment – the education field, and how EdTech may shape the future of their livelihoods.

Private tutoring in India

Tutoring in India is a booming, profitable services industry which acts like an allied sector to all levels of schooling, as well as entrance into professional courses such as engineering and medicine. This private industry is spread across home-based tutoring (or own-account work) for single or multiple students, or micro to large size institutions spreading across the country in all rural and urban areas, with select cities acting as educational clusters like Kota, Madhya Pradesh. According to the National Sample Survey report on education, 21% students opted for private tuitions in 2017-18. Recent news reports from the COVID-19 era indicate that private tutoring in small towns and rural areas has gone online and is now being mediated through digital platforms.

For school education there is evidence to suggest that as more people can afford private schools (as opposed to public government schools where education quality is often in question) the dependence on tutoring has declined. Many of the teachers or tutors work across private schooling, public schooling and tutoring services using different methods of teaching. Their ability to earn, working conditions and industry varies across these segments.

Women use the education sector for employment

Given the variations in the sector, it is difficult to arrive at a clear picture of how many people are employed and under what working conditions.

Some market-based estimations suggest that there are 30 million teaching, non-teaching and support staff in private schools and tuition institutions, making education one of the top 5 employment providers in the country. Case studies indicate that contractual and part-time lecturers form a substantial chunk of the workforce in India’s higher education sector. This suggests that there is a large workforce that could be ready to take part-time or full-time teaching work mediated through platforms.

Dominant models in platform-mediated EdTech sector in India

The EdTech sector in India has dominant players – all unicorns – who are setting the tone for how the sector will play out. The marketplace model followed by Byju’s, Unacademy and Vedantu showcase just that. Here, businesses take charge of deciding the modalities of content delivery, pricing of the courses and marketing the platform to prospective students. The platforms are also responsible for content generation (in-house, or through a network of educators), and maintaining quality of the material on their platform. On the educator front, they control the recruitment, onboarding, upskilling, and reskilling of educators, assessments, payment for educators, and providing technical, and educational support to them.

These companies are not like on-demand models such as Uber. Rather, educational services are sold in multiple classes, courses, or packages; one where the educator’s qualifications and skill are not easily replaceable. Unlike in driving or food delivery where the identified, monetizable skill plays a big role in the sheer number of people who join and are dependent on platforms for their livelihoods. The rating system of driving and delivery platforms is an important place where we witness platform power, and platform’s controlling hand in service delivery. In the EdTech sector, the relationship between an educator and a platform company is a far more involved one than that of a food delivery worker or Uber driver. This raises concerns about the amount of power a company can wield in the management of educators, their skills, content, and ultimately the time they spend to do well on the platform and what they are paid for.

Who are the EdTech platform workers?

These business models necessitate a significant role for the platform worker, particularly in case of the final educator who is interacting with student(s). Workers may be responsible for any or all of the following tasks: course content creation, content moderation, course delivery, doubt clearance and 1-on-1 coaching. Some companies engage workers for specific activities, setting a per task rate, and workers get paid on a weekly, or monthly basis for the aggregate of the tasks they completed within that period. Others employ workers full-time, and these tasks fall under their daily job role.

Companies attract educators from the legacy system of home-based or neighbourhood-based tutoring opportunities by promising them greater reach, and flexible work hours. Each company has a skill assessment component as part of their recruitment and training processes, and only educators that clear preset content and quality thresholds in their chosen area are selected. In cases where companies provide proprietary teaching material, educators go through additional training as a part of the onboarding process.

Labouring as an Edtech worker

Educators are expected to have access to high-quality digital devices (laptops/desktops/phones), and a fast internet connection: two components that are seen as crucial to their ability to deliver the highest quality of online classes that are promised to students. Companies generally insist on a graduate degree (in any discipline), and prefer that teachers go through their proprietary training process and teaching materials. Given that teaching engagements are typically long-term (3-month course, or 9-month certification, for example), educators are expected to make minimum time commitments per week, and the more time they spend the greater is their potential to earn through the platform. This leads to a wide range of possibilities from as little as 2 hours/day to 30 hours/week. Firms say they are only able to track the time educators spend actively teaching on their platforms and have little idea on the time educators may take to prepare before, or after a particular teaching engagement.

In interviews we conducted with senior management at EdTech companies between 2020-21, we found that greater emphasis is placed on the soft skills that educators display, over the subject matter expertise that they have. Through constant monitoring by internal teams, and customer feedback, educators are assessed on their physical appearance via webcams as the main portal of communication on things such as attire and grooming, body language, and most importantly their tone and rapport with the students during teaching sessions. Educators are also implicitly expected to stay beyond the preset class duration, to clarify lingering doubts that student(s) have, and are nudged to be proactive, and go the extra mile in each learning session.

How are women faring as EdTech educators?

Teaching in India has seen the participation of women in significant numbers, however, the transition to teaching online through EdTech companies has yielded mixed results. Outside of organizations that exclusively engage an only female educator base (e.g. White Hat Jr.), most educator bases are dominated by men. A wide range of women work as educators online: college graduates preparing for postgraduate examinations, women that were forced to drop out of the workforce due to familial commitments, and former schoolteachers. In all cases, the relative predictability of timings of classes, and the flexibility and control to schedule when those classes happened are key drivers for women to take up these opportunities.

Our interviews with platform companies also revealed a common set of challenges that they faced in increasing the share of women educators on their platform. These primarily revolved around how teaching from home intersected with women’s existing caregiving and household responsibilities: women tended to take longer to complete the onboarding and training assignments, particularly if there is a lack of flexibility on how these processes are scheduled. In these interviews, what was not clear was whether platforms had to contend with potential women educators that had an issue accessing digital devices, stable internet, advanced digital skills to operate and adequately manage devices, and teaching in sync. This is despite evidence that suggests that women have far less ownership and access to devices and the internet than men. A reason could be that currently platforms are only funnelling the small sliver of women who have unmitigated access to infrastructure and hence online work. This raises several concerns for how inclusive the sector is in terms of employing the diverse population of teachers that India has.

The visual and auditory elements of teaching are important in the online delivery of education. This puts a lot of emphasis on the quality and quantity of content being generated. The time constraint also means that women are unable to continuously create their own new content, and often require more support, either through friends and family, or by engaging people to work with them on content creation and upkeep. The ability for companies to compensate women for class teaching, out of class preparation, content creation is a key point to look for in the coming months.

The gig economy is rife with loans that help workers buy assets that they need for work ­– like drivers who need cars to drive on Uber or Ola, or bikes to do delivery work. For drivers forced to work for lower incomes, these loans become predatory instead of facilitatory. The taxi and delivery sector are defined by a labour oversupply. Given that the education sector is a large employer of educators, it begs the question of what tactics platform companies will use to bring on teachers who cannot afford or do not have their own devices, internet access, webcams and other material needed for online instruction. The retention rates of Indian educators on EdTech platforms are unknown. When taxi platforms faced this issue, it led to predatory practices like loans for work assets, or dynamic wages that lower barriers to work on the platform. Will EdTech go the same way?

Way forward?

EdTech platforms can find more meaningful ways to retain educators to the platform – like stable wages, accounting for the costs of teaching and preparation time, insurance or benefits, and recognition.

For women’s work, the EdTech sector can offer work-from-home, and more control over scheduling class times but enforces a whole new set of expectations, surveillance, and modes of teaching. India’s New Education Policy (NEP) formulated in 2020 locates EdTech solutions at the core of how schooling will be revamped. There is a recognition that these approaches aren’t “teachers versus technology” [but] the solution is in “teachers and technology”. Early adopter educators might be digitally literate enough to make do, but as the employment funnel grows what outcomes can we expect for marginalized women teachers?

The lessons we can take away from other platforms opening their employment funnels are many, but redressal to many of these concerns is quite simple: stability. Stability of pay, time used, quality markers of a service and the stability that comes with having an open dialogue with platforms can waylay many negative parts of platform work. Offering stability doesn’t pit teachers against each other in a race to the bottom, nor against unfair algorithmic processes that are out of their sight and control.

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