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This article discusses formal and informal foreign language learning before university level. The focus is on beginning university students' perceptions of their earlier learning experiences, especially in digital contexts. Language learners' digital competence is a part of their everyday lives, but its relationship to learning in and outside educational settings is still relatively seldom studied. The article discusses learning in formal and informal (i.e., hybrid) contexts and digital learning profiles −that is, a learner's own personalized style in acquiring language competence by creating affordances in personalized digital or mobile learning environments− in primary and secondary education identified in a language learning survey. The results are based on an online survey sent to all beginning university students majoring in languages at a Finnish university (N= 87/192), which was complemented by a short narrative task (N=47) a few months later focusing on earlier education and the use of language learning technologies. The results suggest that the use of technologies seems to differ between extramural and in-school language learning. The learners were well aware of various possibilities to create affordances for learning, and their own involvement increased with age. Most participants had positive attitudes towards the use of technologies to enhance language learning, but critical views emphasized the importance of inspiring contact teaching. Three different digital learning profiles were identified: a digiage learner, a hybrid learner, and an in-school learner. These can be useful when planning differentiated foreign language instruction.

Spoken and written language are two modes of language. When learners aim at higher skill levels, the expected outcome of successful second language learning is usually to become a fluent speaker and writer who can produce accurate and complex language in the target language. There is an axiomatic difference between speech and writing, but together they form the essential parts of learners’ L2 skills. The two modes have their own characteristics, and there are differences between native and nonnative language use. For instance, hesitations and pauses are not visible in the end result of the writing process, but they are characteristic of nonnative spoken language use. The present study is based on the analysis of L2 English spoken and written productions of 18 L1 Finnish learners with focus on syntactic complexity. As earlier spoken language segmentation units mostly come from fluency studies, we conducted an experiment with a new unit, the U-unit, and examined how using this unit as the basis of spoken language segmentation affects the results. According to the analysis, written language was more complex than spoken language. However, the difference in the level of complexity was greatest when the traditional units, T-units and AS-units, were used in segmenting the data. Using the U-unit revealed that spoken language may, in fact, be closer to written language in its syntactic complexity than earlier studies had suggested. Therefore, further research is needed to discover whether the differences in spoken and written learner language are primarily due to the nature of these modes or, rather, to the units and measures used in the analysis.

The present study provides a multilingual perspective on speech fluency by examining fluency across first language (L1), second language (L2), and third language (L3) productions in Finnish, Swedish and English among L1 Finnish (Group 1, G1) and Finnish-Swedish bilingual (Group 2, G2) university students in Finland. The two research questions focused on differences in speech fluency across the three languages between the groups and correlations across speech fluency measures in the different languages. 90 speech samples in Finnish (L1), Swedish (L1/L3), and English (L2) from 30 participants were analyzed in the present study. The speech samples consist of short picture narrations based on comic strip prompts. The fluency analyses focused on temporal fluency and stalling mechanisms. The data were analyzed quantitatively with Mann-Whitney Utests and Spearman's rank-order correlation coefficients. The results demonstrated minor differences between the groups in their Finnish (L1) and English (L2) productions, but a higher level of fluency in Swedish for G2 (their L1) than G1 (their L3). For G1, the correlations were strongest between their L1 Finnish and L2 English, whereas for G2, mostly moderate to strong correlations were found between the different language pairs. The results suggest connections in fluency across the languages in a multilingual speaker's repertoire, but the strength of the correlations varies depending on the participants' L1(s) and proficiency level in the additional languages. Based on the findings, further research on fluency among multilingual speakers is needed. The results have implications for L2 teaching and assessment.

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