Finnish upper secondary school students’ and teachers’ experiences and opinions of mobile language learning applications: A mixed methods study
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This research attempted to find out upper secondary level learners’ and language teachers’ opinions
and experiences about mobile language learning applications (MLLAs), and especially what attributes
and elements should a positively perceived application include. The study is closely related to area of
Mobile assisted language learning (MALL), and the specific interest lies in various MLLAs’ attributes
and features. The study combined both quantitative and qualitative research methods. The learners’
responses were gathered via Webropol questionnaires during the beginning of Fall term 2022, and the
teachers were interviewed using semi-structured individual interviews.
The results of the study suggested that learners and teachers share similar aspirations and preferences
when it comes to actual features and elements within MLLAs used for learning and teaching. Major
differences were observed especially in selection of used applications, as teachers tended to use one
type of applications in the classroom, whereas learners would choose other types of MLLAs for their
individual language learning.
The results can be applicable in both language teaching, as well as MLLA development. If learner
preferences regarding to MLLAs are charted in depth, various MLLAs could be more easily
incorporated to language teaching, and the applications could be utilized with greater efficiency,
potentially resulting in better learning motivation among learners. Developers of MLLAs might find
information of user preference valuable when creating and updating their MLLAs. Future research
could inspect specific applications while keeping user preferences and perceptions in mind to find out
what specific applications would perhaps meet the requirements of a specific target group the best.
The present study could also be replicated with other age groups, to find out whether the preferences
might change according to the age of the user, for instance.