Analysis of italki community tutors who teach Arabic, MSA or Egyptian

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Introduction

italki is an online language learning website which connects language learners and teachers through video chat. The site allows students to find online teachers for 1-on-1 tutoring, and teachers to earn money as freelance tutors [Wikipedia].

Objective

This research aims to help with identifying some key information about community tutors who teach Arabic (Ar), MSA or Egyptian (EGY). Those key pieces of information are:
A)
  1. Which year the tutor became a teacher on italki?
  2.  How many lessons did s/he teach?
  3. How many lessons per day did s/he teach?
  4.  What is her/his current hourly rate?
  5. How much money did s/he earn per day?
B)
  1. Who are ranked the first in each of the five criteria listed above? And how do they perform in the other criteria?

Scope

  • The research only covers data obtained through 23-24 December 2017. It should be noticed that all the data may differ in any other date.
  • To calculate how much money each tutor earns per day, the research assumes that each tutor’s hourly rate was fixed since s/he became a tutor, which is possible not the actual case as tutors do change their hourly rate from time to time.
  • The calculated earned money per day is the gross earning without taking any consideration about any deduction like italki fees.

Methodology

  1. Using italki search feature, three searches were done in each the selected criteria were:
    • Tutor Type: Community, Teaches: Arabic
    • Tutor Type: Community, Teaches: MSA
    • Tutor Type: Community, Teaches: Egyptian
  2. The data is collected between 23-24 December 2017 
  3. The data was analyzed using Microsoft Excel and the Venn Diagram was drawn by eulerAPE.

Results

The are 62 unique community tutors distributed as shown in Fig 1.
Ar = 53
MSA = 14
EGY = 12

AR ∩ MSA = 7
AR ∩ EGY = 10
MSA ∩ EGY = 3

AR ∩ MSA ∩ EGY = 3

Fig 1 Number of community tutors who teach Ar, MSA, EGY or a combination

Histograms of each of the 5 questions listed in objectives section A are shown in Figs 2:6.

Fig 2 Histogram of the year a tutor became one
 
Fig 3 Histogram of Number of lessons

Fig 4 Histogram of Number of lessons per day

Fig 5 Histogram of the current hourly rate

Fig 6 Histogram of earned money per day

Who ranked first in each criterion

Oldest Tutor:
  • Date of becoming a tutor: 13 Apr 2009 (ranked 1)
  • Number of lessons: 341 (ranked 13)
  • Lessons/day: 0.11 (ranked 46)
  • Hourly rate: $22 (ranked 2)
  • Earned/day: $22.36 (ranked 30)
Highest Number of lessons:
  • Date of becoming a tutor: 13 Feb 2015 (ranked 9)
  • Number of lessons: 2035 (ranked 1)
  • Lessons/day: 1.95 (ranked 2)
  • Hourly rate: $10 (ranked 16)
  • Earned/day: $19.49 (ranked 2)
Highest Lessons/day & Highest Earned/day:
  • Date of becoming a tutor: 19 Oct 2015 (ranked 56)
  • Number of lessons: 144 (ranked 24)
  • Lessons/day: 2.22 (ranked 1)
  • Hourly rate: $11.9 (ranked 10)
  • Earned/day: $26.36 (ranked 1)
Highest Hourly Rate:
  • Date of becoming a tutor: 28 Jan 2016 (ranked 12)
  • Number of lessons: 13 (ranked 54)
  • Lessons/day: 0.02 (ranked 58)
  • Hourly rate: $25 (ranked 1)
  • Earned/day: $0.47 (ranked 52)

Conclusion

  • There are 62 unique community tutors who teach one or more languages of Arabic, MSA, Egyptian.
  • The statistical Mode of the year a tutor became one: 2017
  • The statistical Mode of Number of lessons: < 50
  • The statistical Mode of how many lessons/day: 0.0 to 0.1
  • The statistical Mode of currently hourly rate ($): 8 to 10
  • The statistical Mode of how much money earned per day ($): 0 to 3  

Future work

The following questions could be investigated:
  • Could this research expand by adding more data like professional tutors or other languages through the use of an automatic method like ripping the data from the website?
  • And does that violate any rules or regulations?

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