Collecting Big Data Through Citizen Science: Gamification and Game-based Approaches to Data Collection in Applied Linguistics

Author:

Kim Yoolim1ORCID,Kogan Vita V2,Zhang Cong3

Affiliation:

1. Psychology Department, Cognitive & Linguistic Sciences Program, Wellesley College , 106 Central Street, Wellesley, MA 02481 , USA

2. School of Slavonic and East European Studies, University College London , London , UK

3. School of Education, Communication and Language Sciences, Newcastle University , Newcastle upon Tyne , UK

Abstract

Abstract Gamification of behavioral experiments has been applied successfully to research in a number of disciplines, including linguistics. We believe that these methods have been underutilized in applied linguistics, in particular second-language acquisition research. The incorporation of games and gaming elements (gamification) in behavioral experiments has been shown to mitigate many of the practical constraints characteristic of lab settings, such as limited recruitment or only achieving small-scale data. However, such constraints are no longer an issue with gamified and game-based experiments, and as a result, data collection can occur remotely with greater ease and on a much wider scale, yielding data that are ecologically valid and robust. These methods enable the collection of data that are comparable in quality to the data collected in more traditional settings while engaging far more diverse participants with different language backgrounds that are more representative of the greater population. We highlight three successful applications of using games and gamification with applied linguistic experiments to illustrate the effectiveness of such approaches in a greater effort to invite other applied linguists to do the same.

Publisher

Oxford University Press (OUP)

Subject

Linguistics and Language,Language and Linguistics,Communication

Reference19 articles.

1. ‘English language learning through non-technology games: A case study of international students at a Lithuanian university,’;Annamalai;The Qualitative Report,2021

2. ‘Disentangling emphasis from pragmatic contrastivity in the English H*~ L+ H* contrast,’;Arvaniti;Proceedings of Speech Prosody,2022

3. ‘Remote testing of the familiar word effect with non-dialectal and dialectal German-learning 1–2-year-olds,’;Braun;Frontiers in Psychology,2021

4. ‘The design and efficiency of loyalty rewards,’;Caminal;Journal of Economics & Management Strategy,2012

5. ‘Systems from sequences: An iterated learning account of the emergence of systematic structure in a non-linguistic task,’;Cornish;Proceedings of the Annual Meeting of the Cognitive Science Society,2013

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