Can you trust your participants? How not to get scammed when recruiting online

Ekaterina Sudina; Ruirui Jia; Eunsoo Kang; Luke Plonsky; Katherine Yaw

doi:10.1016/j.rmal.2025.100285

Can you trust your participants? How not to get scammed when recruiting online

Ekaterina Sudina
, Ruirui Jia
, Eunsoo Kang
, Luke Plonsky
, Katherine Yaw

English

Research output: Contribution to journal › Article › peer-review

Abstract

Kim and Chen’s (2025) compelling framework of value, trust, and agency advocates for more inclusive online data collection practices in applied linguistics. In our response to Kim and Chen’s (2025) commentary, we seek to build on the proposed list of suggestions for enhancing a sense of trust. To do so, we reflect on four case studies that come from our own work and share lessons learned from our own online data collection experiences. Ultimately, we aim to expand the framework of research inclusivity by demonstrating that trust between researchers and participants is inherently reciprocal.

Original language	English (US)
Article number	100285
Journal	Research Methods in Applied Linguistics
Volume	4
Issue number	3
DOIs	https://doi.org/10.1016/j.rmal.2025.100285
State	Published - Dec 2025

Keywords

Crowdsourcing platforms
Data trustworthiness
Online experimentation
Online recruitment
Researcher-participant relationship

ASJC Scopus subject areas

Social Sciences (miscellaneous)
Linguistics and Language

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10.1016/j.rmal.2025.100285

Cite this

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title = "Can you trust your participants? How not to get scammed when recruiting online",

abstract = "Kim and Chen{\textquoteright}s (2025) compelling framework of value, trust, and agency advocates for more inclusive online data collection practices in applied linguistics. In our response to Kim and Chen{\textquoteright}s (2025) commentary, we seek to build on the proposed list of suggestions for enhancing a sense of trust. To do so, we reflect on four case studies that come from our own work and share lessons learned from our own online data collection experiences. Ultimately, we aim to expand the framework of research inclusivity by demonstrating that trust between researchers and participants is inherently reciprocal.",

keywords = "Crowdsourcing platforms, Data trustworthiness, Online experimentation, Online recruitment, Researcher-participant relationship",

author = "Ekaterina Sudina and Ruirui Jia and Eunsoo Kang and Luke Plonsky and Katherine Yaw",

note = "Publisher Copyright: {\textcopyright} 2025 The Authors.",

year = "2025",

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AU - Sudina, Ekaterina

AU - Jia, Ruirui

AU - Kang, Eunsoo

AU - Plonsky, Luke

AU - Yaw, Katherine

PY - 2025/12

Y1 - 2025/12

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AB - Kim and Chen’s (2025) compelling framework of value, trust, and agency advocates for more inclusive online data collection practices in applied linguistics. In our response to Kim and Chen’s (2025) commentary, we seek to build on the proposed list of suggestions for enhancing a sense of trust. To do so, we reflect on four case studies that come from our own work and share lessons learned from our own online data collection experiences. Ultimately, we aim to expand the framework of research inclusivity by demonstrating that trust between researchers and participants is inherently reciprocal.

KW - Crowdsourcing platforms

KW - Data trustworthiness

KW - Online experimentation

KW - Online recruitment

KW - Researcher-participant relationship

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Can you trust your participants? How not to get scammed when recruiting online

Abstract

Keywords

ASJC Scopus subject areas

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