Open AccessUsing Statistics to Solve Practical Vocabulary Problems
Author(s) -
Jenifer LarsonHall,
AUTHOR_ID
Publication year - 2021
Publication title -
vocabulary learning and instruction
Language(s) - English
Resource type - Journals
eISSN - 2187-2759
pISSN - 2187-2767
DOI - 10.7820/vli.v10.2.larson-hall
Subject(s) - computer science , vocabulary , rasch model , bootstrapping (finance) , empirical research , data science , statistics , statistical theory , item response theory , management science , econometrics , mathematics education , psychology , mathematics , psychometrics , linguistics , engineering , philosophy
Most of us who do research on language acqusition have had to use statistics to evaluate the results of experiments. Some may use only the statistical procedures they learned in graduate school and may thus miss out on new advances in statistics that might shed light on some problems in a more straightforward way. The three papers that conduct empirical studies that I will discuss today have used statistical procedures that you may not be very familiar with—bootstrapping, Monte Carlo simulations, and Rasch (or item response theory [IRT]) analysis. Their use of these procedures, however, means that they are able to give quite precise and interesting answers to the questions that they have asked. The fourth paper I will discuss is not an empirical study but a review of studies and call for future research going forward.