This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…

Loanwords in Japanese that share form and meaning with English words are referred to as "Japanese-English cognates" (e.g., [Japanese symbol omitted] "radio") and are of fundamental concern for researchers concerned with vocabulary learning and instruction. This concern is reflected in the growing body of research into…

This study used think-aloud protocols to compare essay-rating processes across holistic and analytic rating scales in the context of China's College English Test Band 6 (CET-6). A group of 9 experienced CET-6 raters scored the same batch of 10 CET-6 essays produced in an operational CET-6 administration twice, using both the CET-6 holistic…

This review paper constitutes the first step within a larger research effort to develop an interactive pragmatics learning tool for second and foreign language (L2) learners and users of English. The tool will primarily endeavor to support pragmatics learning within the language use domain "workplace." Given this superordinate objective,…

Aim: To examine the stability of caregiver-reported classifications of function of children with cerebral palsy (CP) measured 12 months apart. Method: Participants were 86 children (50 males, 36 females) with CP of all motor types and severities who were recruited into a population-based longitudinal study. Children were aged 11 years 8 months (SD…

This study compared three methods for identifying non-mainstream dialect use: listener judgment ratings, type-based counts of non-mainstream pattern use, token- based counts. Correct dialect classifications were made for 88 to 97 percent of participants, although regression algorithms had to be applied to the type- and token-based results. For…