Abstract:

A learner’s English proficiency is evaluated with de facto official standardized proficiency tests such as Test of English as a Foreign Language (TOEFL), Test of English for International Communication (TOEIC), and Duolingo among others. A quick and reliable test shows how the learning process proceeds, and this type of test has been sought by research on computer-assisted language testing. This study examined a prediction model of learners’ general English proficiency (GEP) by clarifying the contribution of phonological features. A GEP prediction model can be derived by regression analysis where the independent variables are learners' dictation performance and linguistic features. The GEP prediction model is more cost-effective than de facto official English proficiency tests that examine listening, speaking, reading, and writing performance. The linguistic features explain the dictation difficulty in terms of lexical, syntactic, and phonological properties.

This study clarified the contribution of linguistic features by comparing three types of GEP prediction models using:
(i) phonological features,
(ii) non-phonological (lexical and syntactic) features, and
(iii) lexical, syntactic, and phonological features.

The prediction accuracy was determined by the correlation between the predicted and observed GEPs. The observed GEP was the dependent variable in the regression analysis, and it was determined by test scores of a GEP test. The prediction accuracy was not statistically significantly different among these GEP prediction models. However, the contribution to a GEP prediction model was observed in a phonological feature (the presence of linking), as well as a lexical feature (word difficulty) and a syntactic feature (sentence length).

Keywords:

Evaluation, English language proficiency, dictation performance.