Factors driving teacher selection on online language tutoring platforms: an experiment-based approach

Lichen Zhen, Nathaniel Ming Curran, Hernan Galperin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Facilitated by the increased availability of affordable broadband Internet, individuals around the world are taking language lessons online from private tutors. A large proportion of online language tutoring takes place through online teaching platforms (OTPs), which are two-sided online markets that connect individual learners and tutors for piece-meal lessons. This paper considers how salient aspects of teachers’ identities drives teacher selection on OTPs. Using a discrete choice experiment design (N = 971) distributed to online English learners from four countries, (Brazil, Italy, Spain and Korea) the paper tests hypotheses related to linguistic, racial and gender-based discrimination. The results reveal that participants’ preference for L1 teachers far exceeds their preference for pedagogically qualified instructors and that learners prefer female to male teachers. Further, learners’ preference for L1 teachers is stronger when the teacher is White than when the teacher is Black. The results also indicate that foreign media consumption correlates with reduced racial bias. Implications and suggestions for further research are discussed.

Original languageEnglish
JournalJournal of Multilingual and Multicultural Development
DOIs
Publication statusAccepted/In press - 2023

Keywords

  • gig economy
  • language learning
  • native speakerism
  • Online teaching platforms

ASJC Scopus subject areas

  • Cultural Studies
  • Education
  • Linguistics and Language

Fingerprint

Dive into the research topics of 'Factors driving teacher selection on online language tutoring platforms: an experiment-based approach'. Together they form a unique fingerprint.

Cite this