![]() Directed motivational currents: Extending the theory of L2 vision. Individual differences in language learning: A complex systems theory perspective. Computer Assisted Language Learning, 27(1), 70-105. Technologies for foreign language learning: A review of technology types and their effectiveness. Ushioda (Eds.), Motivation, language identity and the L2 self (pp. Flow: The psychology of optimal experience. Measuring flow in the EFL classroom: Learners’ perceptions of inter‐and intra‐cultural task‐based interactions. To address this issue, Mirosław Pawlak and Mariusz Kruk put together the volume Individual Differences in Computer-Assisted Language Learning Research, providing timely and insightful guidelines for the exploration of IDs in CALL and the broader realm of second language acquisition (SLA) research.Īubrey, S. However, despite their critical role, IDs have not garnered the attention they genuinely merit in this context (Pawlak, 2022). With a plethora of technology-based options and functionalities, CALL provides learners with a high degree of autonomy (Pawlak et al., 2016), making it an environment that is ripe for capitalizing on learners’ individuality (p. ![]() There is now a consensus that individual differences (IDs) significantly influence the process and product of L2 learning (Pawlak, 2020). In the era of rapid technological expansion, the integration of various technologies into the process of second and foreign language (L2) learning and teaching has become pervasive, making computer-assisted language learning (CALL) a well-established field (Golonka et al., 2014).
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