Lee, Yong-hun. 2018. A Conditional Inference Tree Analysis of Can and May
in Korean EFL Learners’ Writings. English Language and Linguistics 24.3, 165-187.
This paper applied an analysis using conditional inference trees to the corpus data
of native and non-native speakers and examined the behaviors of some of linguistic
factors in the data sets. For this purpose, the corpus data in Lee and Yu (2017)
were taken. In the corpus data, all the sentences with two modal verbs can and
may were extracted from two corpora (the ICE-USA corpus and the Korean
component of the TOEFL11 corpus) and twenty linguistic factors were annotated.
This paper applied a conditional inference tree analysis to the annotated corpus
data so that it can be examined how differently some of linguistic factors behaved
in two different types of data sets. Through the analysis, the following findings
were observed: (i) the factors Sense, Mood, AnimType, and SubjMorph were highly
ranked in the (American) native speakers’ corpus, whereas the factors Sense,
AnimType, VerbSem, and SubjMorph were highly ranked in Korean EFL learners’
one, (ii) although the factor Sense was located at the top of the conditional inference
trees, their behaviors were different in the two types of corpora, and (iii) while
the use of three types of Senses was fairly balanced in the native speakers’ English,
that of the Korean EFL learners was biased. The analysis results imply that slightly
different types of criteria are involved in the determination of choice between can
and may in (American) native speakers and Korean EFL learners.

Keywords: can, may, corpus data, conditional inference tree