Thesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research English Language Teaching

This study investigates the effects of mobile data-driven learning (M-DDL) on the
writing performance of intermediate EFL learners in Libya. M-DDL is a learning
approach that uses corpora to provide learners with contextualised examples of
language use via mobile devices, such as smartphones and tablets. Corpora are large
collections of authentic language texts that have been compiled and analysed to
identify patterns of language use. The mobility afforded by M-DDL gives learners
greater flexibility in how and when they interact with corpora to support their
language learning. A sample of 50 intermediate EFL learners was recruited and
assigned to either the experimental M-DDL group (n = 26) or the control group (n =
24). A mixed-methods approach was adopted, involving quantitative measures such
as pre-, post-, and delayed post-tests, as well as a questionnaire survey, alongside
qualitative data collection through focus group interviews, to gather comprehensive
data. Statistical analysis of the post-test scores revealed significant gains in writing
performance for the M-DDL group. Improvements were sustained over two months
following the intervention. Learners were reported to have positive attitudes towards
the corpus and M-DDL. However, some participants had trouble using the corpus,
such as with cut-off sentences and issues with the analysis of concordance outputs.
Overall, the findings imply that the integration of DDL into the core curriculum
proved remarkably suited to learners’ needs. Therefore, this study demonstrates the
viability of implementing DDL in everyday EFL classrooms using existing tools with
minimal training required for ordinary teachers and students. Undoubtedly, M-DDL
has a positive bearing on students’ learning.