Statistical Literacy Among Applied Linguists and Second Language Acquisition Researchers

• Published in: TESOL quarterly 2014-06, Vol.48 (2), p.360-388
• Main Authors: Loewen, Shawn, Lavolette, Elizabeth, Spino, Le Anne, Papi, Mostafa, Schmidtke, Jens, Sterling, Scott, Wolff, Dominik
• Format: Article
• Language: English
• Subjects: Applied Linguistics; Applied statistics; Attitude Measures; College Faculty; Descriptive statistics; Educational research; Educational sociology; Educational statistics; English as a second language; Factor Analysis; Inferential statistics; Knowledge Level; Language Acquisition; Language Research; Linguists; Literacy; Positive Attitudes; Prediction; Qualitative research; Quantitative analysis; Questionnaires; Research methods; Researchers; Second language acquisition; Second Language Learning; Second Languages; Self Efficacy; Sociolinguistics; Statistical Analysis; Statistics; Teacher Attitudes
• ISSN: 0039-8322; 1545-7249
• DOI: 10.1002/tesq.128

The importance of statistical knowledge in applied linguistics and second language acquisition (SLA) research has been emphasized in recent publications. However, the last investigation of the statistical literacy of applied linguists occurred more than 25 years ago (Lazaraton, Riggenbach, & Ediger, 1987). The current study undertook a partial replication of this older work by investigating (a) applied linguists' general experiences with statistics, (b) underlying factors that constitute applied linguists' knowledge about and attitudes toward statistics, and (c) variables that predict attitudes toward statistics and statistical self-efficacy. Three hundred thirty-one scholars of applied linguistics and SLA completed a questionnaire. Eighty percent had taken a statistics class; however, only 14% of doctoral students and 30% of professors felt that their statistical training was adequate. A factor analysis of participants' knowledge of statistical terms revealed three factors: common inferential statistics knowledge, advanced statistics knowledge, and basic descriptive statistics knowledge. An analysis of participants' attitudes toward statistics revealed two factors: statistics are important and lack of statistical confidence. Regression analyses found that a quantitative research orientation was the strongest predictor of positive attitudes toward statistics; nevertheless, participants also expressed support for qualitative research. Recommendations for improving quantitative methods in our field are made based on our findings.