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HOW KNOWLEDGEABLE ARE APPLIED LINGUISTICS AND SLA RESEARCHERS ABOUT BASIC STATISTICS?

DATA FROM NORTH AMERICA AND EUROPE

Published online by Cambridge University Press:  11 October 2019

Shawn Loewen*
Affiliation:
Michigan State University
Talip Gönülal
Affiliation:
Erzincan Binali Yıldırım Üniversitesi
Daniel R. Isbell
Affiliation:
California Polytechnic State University
Laura Ballard
Affiliation:
Educational Testing Services
Dustin Crowther
Affiliation:
University of Hawai’i at Mānoa
Jungmin Lim
Affiliation:
Michigan State University
Jeffrey Maloney
Affiliation:
Northeastern State University
Magda Tigchelaar
Affiliation:
Western Michigan University
*
*Correspondence concerning this article should be addressed to Shawn Loewen, Second Language Studies, B255 Wells Hall, 619 Red Cedar Road, Michigan State University, East Lansing, MI 48824-1027. E-mail: loewens@msu.edu

Abstract

Despite the prevalence of quantitative approaches in applied linguistics (AL) and second language acquisition (SLA) research (Gass, 2009), evidence indicates a need for improvement in analyzing and reporting SLA data (e.g., Larson-Hall & Plonsky, 2015). However, to improve quantitative research, researchers must possess the statistical knowledge necessary to conduct quality research. This study assesses AL and SLA researchers’ knowledge of key statistical concepts on a statistical knowledge test. One hundred and ninety-eight AL and SLA researchers from North America and Europe responded to 26 discipline-specific questions designed to measure participants’ ability to (a) understand basic statistical concepts and procedures, (b) interpret statistical analyses, and (c) critically evaluate statistical information. Results indicate that participants generally understood basic descriptive statistics, but performance on items requiring more advanced statistical knowledge was lower. Quantitative research orientation, number of statistics courses taken, and frequent use of statistics textbooks had positive influences on researchers’ statistical knowledge.

Type
Research Report
Open Practices
Open materials
Copyright
© Cambridge University Press 2019

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Footnotes

The experiment in this article earned an Open Data badge for transparent practices. The materials are available at https://www.iris-database.org/iris/app/home/detail?id=york%3a932451&ref=search.

We would like to thank Emma Marsden for her help in recruiting European respondents. We would also like to thank the SSLA editors and anonymous reviewers for their insights and input, which made the paper stronger. Any shortcomings are ours alone.

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