  Reading comprehension, which has been defined as gaining an understanding of
written text through a process of translating grapheme into meaning, is an
important academic skill. Other language learning skills - writing, speaking
and listening, all are connected to reading comprehension. There have been
several measures proposed by researchers to automate the assessment of
comprehension skills for second language (L2) learners, especially English as
Second Language (ESL) and English as Foreign Language (EFL) learners. However,
current methods measure particular skills without analysing the impact of
reading frequency on comprehension skills. In this dissertation, we show how
different skills could be measured and scored automatically. We also
demonstrate, using example experiments on multiple forms of learners'
responses, how frequent reading practices could impact on the variables of
multimodal skills (reading pattern, writing, and oral fluency).
  This thesis comprises of five studies. The first and second studies are based
on eye-tracking data collected from EFL readers in repeated reading (RR)
sessions. The third and fourth studies are to evaluate free-text summary
written by EFL readers in repeated reading sessions. The fifth and last study,
described in the sixth chapter of the thesis, is to evaluate recorded oral
summaries recited by EFL readers in repeated reading sessions.
  In a nutshell, through this dissertation, we show that multimodal skills of
learners could be assessed to measure their comprehension skills as well as to
measure the effect of repeated readings on these skills in the course of time,
by finding significant features and by applying machine learning techniques
with a combination of statistical models such as LMER.
