how much do online tutors make

how much do online tutors make

The Economics of Online Tutoring: Understanding the Factors Influencing Earnings

1. Introduction to the Online Tutoring Industry

A survey revealed that in 2018, among 440,000 workers in the United States affiliated with the informal sector of the online tutoring industry, 3,400 also had at least one wage or salary job. Recent years have brought rapid growth in the online tutoring sector, enabled by online education platforms, including, for example, a multiplication of flexible and formal continuing-education courses from an increasing number of accredited universities; short, job-or-interest-targeted virtual bootcamps; and extensive boutiques of Massive Open Online Courses (MOOCs) that offer free courses such as Coursera. Platforms that administer and market courses offered by educational institutions hire people to provide these types of assistance online. The economic benefits of tutoring are evidenced by the willingness of students to pay for tutoring services, but it can also provide benefits for societies and schools as it may help to bridge learning gaps and reduce inequality.

A few decades ago, one might think of tutoring as an activity that took place in rich families’ dinner-table conversations, but times are changing. Technological advancements and educational democratization have made it much easier for external tutors to overcome geographical barriers and target their assistance not only to families that can afford to pay a high price but to a broader clientele. In the last few decades, online, digital, and distance tutoring has taken off as a separate business activity. The positive externalities of globalization and technological advancement are the reduction of geographical gaps and facilitation of access to new job opportunities, such that in contrast to traditional (offline) tutoring, online tutoring can be a source of secondary income for a large part of the labor force.

2. Factors Influencing Online Tutors’ Earnings

Another important factor is the marketing strategy adopted. If an individual knows that a tutor’s stock of skill is very high—relative to the rest of the population—they might adopt a high price/low volume strategy. If observationally equivalent tutors adopt different strategies, the market may not clear, as there is nothing to force these individuals to adopt a particular ‘market’ strategy. In periods when the general supply of tutors exceeds the number of students seeking tuition, some individuals might change their ‘market’ strategy to increase their locating stock and hence the probability of obtaining students. Additionally, the average pricing strategy could have some influence on the demand for the tuition service. Anecdotal evidence indicates that many tutors offer different discounts or free lessons to try to ‘sweep’ students away from other tutors by, for example, underpricing them. Moreover, the times that a tutor is available for tuition could influence overall ‘earnings’. For example, if a tutor can only provide classes at the less-popular times on the market, they might have to lower their fee. Similarly, a tutor who can offer private tuition or other forms of earnings might do so and offer a subsidy (by imposing a lower fee) to attract students at these times. Lastly, the local supply of tutors of similar ability could also influence the probability of attracting clients. If on either dimension (experience or ratings), tutors in location l have a lower likelihood of being chosen, they might have to lower their price in that location to maintain their overall earnings. More generally, the competition included in the utility function of individuals using the platform to earn money as an important determinant of the utility provided by the platform in period t. If the rewards are much lower than expected, this could impact tutor and student behavior considerably. For instance, if earnings are well below expectations, students might simply prefer not to seek the services of a tutor, or, for more ‘price-inelastic’ services, tutors might respond by unilaterally lowering their price to attract students. This is an empirical issue in need of further investigation. The merit of considering the factors influencing the additional earning of a tutor is that we can, to some degree, control for demand-decided characteristics of the student when it is absent from the data, and our on-site talent matches the talent of a student.

Factors Identifying Earnings. Before we continue, it is important to gain a sense of the average total earnings of online tutors who, based on their prior experience, have various subject matter expertise. With these students going through the platform respective averages, we can determine the impact of experience and the particular subjects a tutor has expertise on the tutor’s earnings. Doing so can also help identify the relationship between the returns to various subject matter per hour of experience. While the popularity of various subjects is not identical across years, they are generally fairly time-invariant. Given this assumption and the data at our disposal, we provide a detailed examination of how online tutors fare in their efforts to optimize their earnings. Therefore, the principal factors which identify and account for a tutor’s total hourly earnings are the demand elasticity of a tutor’s particular skill and a tutor’s level of that skill/experience. Everything else ought to be considerably less important, except possibly amongst younger tutors. We discuss some of these other factors below.

3. Strategies for Maximizing Earnings as an Online Tutor

Starting with a larger number of already rated academic subjects, the current number of monthly hours of tutoring, the ratings received, and the hours dedicated weekly to tutoring are characteristics that increase the probability of being a tutor. Since these variables increase tutors’ expected wages, the fact that the probability of not receiving any tutoring rights decreases during the contract between months is consistent with tutors mitigating risks over time. This is done by combining employment options. A more cohesive trend along months appears for all these characteristics once the commuting time is included. It increases elasticity coefficients because the addition of this variable mitigates omitted variable bias.

Advantages of having a larger number of different academic subjects taught include the ability to attract students interested in diverse subjects of different difficulty levels. In markets in which tutor ratings are multiaspect evaluations, this diversification can also increase the informational rents by giving a tutor more ratings per aspect, and therefore more precise signals on their unobservable ability in each aspect, thereby reducing the impacts of feedback outliers.

The second strategy is to try to increase the reception of good ratings that do not suffer from luck. These ratings provide information strictly superior to sample average ratings to students in a market characterized by a small sample of ratings and uncontested markets. Furthermore, poor ratings can be biased due to selection, especially if students who did not value the experience do not leave a rating. To avoid this bias and reduce the impacts of random noise, an alternative strategy could be to have a large number of ratings.

While the characteristics of tutors also dictate pay, some strategies can be employed by tutors to maximize earnings. First, it is essential to get the student base completed. Since websites serve as intermediaries and display tutors’ information and ratings, online firms may also play a role in increasing tutors’ visibility.

4. Case Studies and Success Stories in Online Tutoring

4.3. Case Study 3: Aribideola Kusimo Deola’s maximum earnings exceeded $500 ($508) with a smart 60% commission rate from Superprof. The teacher interviewed was from British Columbia, and used several strategies to acquire students. Deola had just one student from students between the ages of 15 and 25. By the time Deola was interviewed, she had around three total students. Deola adapted the teaching style according to the interests and level/tone of the students. In comparison to other tutors interviewed, Deola spent less time on word of mouth or local advertising. Similar to some of the other tutors Deola learned about Superprof through an online search. Deola is 95% consistent and tries to plan for her ventures. Of course, since Superprof helps advertise and supports her efforts, Deola can spend more time. Deola’s future was mainly undecided despite wanting to branch out and teach art students how to speak with complete confidence. Based on the time she had spent utilizing Superprof, Deola was considering completing some additional post-secondary education in art with the plan of pursuing her MFA in going large to have more students in the next year.

4.2. Case Study 2: Jessi Kim (A Cal Poly Graduate who learned how to Teach Math Well) A recent graduate and an international student who came to the Cal Poly campus ranked 1st in US for MS engineering programs with a tool making mechanical engineering. Her curriculum comprised engineering mathematics. Her academic career provided her with lots of mathematical teaching experience. Jessi has been able to teach at least one hour per day and often more. Due to this, she earns above the average among tutors in her region, managing to earn over $600 per week. This is in a place with a cost of living that is some 20% lower than the average across the US. Furthermore, Jessi has a full-time job, so chooses not to teach over weekends, her schedule is flexible, and she can easily adjust teaching to fit in with her own timetables. She has been very successful to date. As someone who was embarrassed about her English speaking ability, she has been able to help English language learners to improve their spoken language using contextual conversation.

4.1. Case Study 1: Ron Tucker (A Mechanical Engineer from South Carolina) Ron has been with Superprof for some time and largely teaches high school and university students. He earns a consistent amount of around $200 per month coaching around five students per month. He has given exams such as GRE, SAT, GMAT and prefers to teach based on those exam patterns. He believes that the results of the students largely depend on the students’ capability and that one exam does not decide fate. Success is basically how much students have learned from the tutor. Ron gets his students through walk-ins and word-of-mouth.

5. Future Trends and Opportunities in the Online Tutoring Market

Given the evolving nature of work and learning, the increasing prominence of AI, and entrepreneurship as a way for young students to make money, these trends are likely to serve as future opportunities allowing more and more people to become a part of the online tutoring market. Other potential opportunities include the following: there is likely to be a trend toward narrowing down to specific subjects and specialization that will require niche tutor specialism rather than generalization, and therefore leading the way to another subfield of service enhancement to which this paper provides a foundation. Globally, the growth of online tutoring will continue to rise as technology advances. Now more than ever, technological advancement has transformed how we learn. Despite the pandemic, positive change has occurred within the e-learning market. More students are embracing online classes, global teaching platforms have benefited, and the need for online tutors, content creators, and developing online learning platforms is growing. While there are many existing market-share-based online teaching platforms, an ever-increasing number of them are set to open, as multiple educational companies are moving to the online education space.

Over the next few years, several opportunities are likely to emerge within the online tutoring market, driven largely by rapid technological advancements. The integration of artificial intelligence, for example, will assist tutors to improve upon personalized learning platforms and create and facilitate learning experiences – from language learning to digital literacy. Online tutoring can be tailored according to the learner’s capabilities, thereby improving competence as per student need.