How Do Large Language Model-Based Artificial Intelligence Tools Support Finnish Learning as a Second Language?
Fang, Kuiqing (2025)
2025
Master's Programme in Sustainable Societies and Digitalisation
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2025-06-24
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202506247414
https://urn.fi/URN:NBN:fi:tuni-202506247414
Tiivistelmä
Second language acquisition (SLA) is a well-established field of study, yet research has largely focused on English as a target language, often overlooking languages with smaller speaker populations such as Finnish. In light of the growing influence of large language model-based artificial intelligence tools (LLM-based AI tools) across educational domains, it is essential to explore how such technology supports second language learning—particularly for underrepresented languages.
Motivated by personal experience learning Finnish and frequent interactions with LLM-based AI tools for language support, the researcher investigates two questions:
(1) What are the advantages of using LLM-based AI tools to support Finnish language learning?
(2) What are the challenges and concerns when learners use this evolving technology?
The study is grounded in sociocultural theory and employs a qualitative-dominant mixed-methods approach in the form of a case study. Data were collected through interviews with six Finnish learners and one Finnish teacher, as well as a questionnaire completed by 25 learners.
Findings indicate that LLM-based AI tools offer significant potential as mediational resources, helping learners recognise their zone of proximal development (ZPD) and providing scaffolding to support Finnish learning progress. However, concerns about inaccuracy, lack of idiomaticity, and limited adaptive feedback were frequently noted. The study also finds limited evidence that LLM-based AI tools alone can foster internalisation of Finnish. Additionally, participants demonstrated strong AI literacy, including prompt refinement, critical evaluation of outputs, and awareness of ethical concerns.
The study recommends further research on learners across a broader range of proficiency levels to better understand the role of LLM-based AI tools in Finnish language acquisition. Expanding research in this area can contribute to the development of more inclusive pedagogical strategies and enhance the integration of AI technologies in language education for less commonly taught languages.
Motivated by personal experience learning Finnish and frequent interactions with LLM-based AI tools for language support, the researcher investigates two questions:
(1) What are the advantages of using LLM-based AI tools to support Finnish language learning?
(2) What are the challenges and concerns when learners use this evolving technology?
The study is grounded in sociocultural theory and employs a qualitative-dominant mixed-methods approach in the form of a case study. Data were collected through interviews with six Finnish learners and one Finnish teacher, as well as a questionnaire completed by 25 learners.
Findings indicate that LLM-based AI tools offer significant potential as mediational resources, helping learners recognise their zone of proximal development (ZPD) and providing scaffolding to support Finnish learning progress. However, concerns about inaccuracy, lack of idiomaticity, and limited adaptive feedback were frequently noted. The study also finds limited evidence that LLM-based AI tools alone can foster internalisation of Finnish. Additionally, participants demonstrated strong AI literacy, including prompt refinement, critical evaluation of outputs, and awareness of ethical concerns.
The study recommends further research on learners across a broader range of proficiency levels to better understand the role of LLM-based AI tools in Finnish language acquisition. Expanding research in this area can contribute to the development of more inclusive pedagogical strategies and enhance the integration of AI technologies in language education for less commonly taught languages.