A pathway from surface to deep online language learning approach: The crucial role of online self-regulation.

Students' approaches to online technologies (SAOLT) have garnered significant support among scholars from a variety of fields, particularly in the field of science, technology, engineering, and mathematics education (STEM). The humanistic field needs to explore learners' approaches to target learning contexts, especially in the fields of computer-assisted language learning (CALL) and psycholinguistics. To fill this gap, the researchers explored 686 Iranian high school EFL learners' approaches to online language learning (OLL) with regard to their pedagogical, technical, and peer support, as well as the mediation role of online self-regulation. The partial least squares modeling approach's (PLS-SEM) reflective analysis validated the factorial structure of the conceptual study framework in online language learning and secondary education. The formative model found that instructional and peer support positively impacted language learners' deep and surface approaches to online language learning, thereby maximizing and minimizing their online presence and meaningful language learning. Furthermore, the mediation analysis revealed the significant moderating influence of learners' online self-regulation, which shifted the correlations from relating both learners' perceived support to their surface and deep learning approaches to only relating to the deep learning approach. Consequently, this study has pedagogical implications as it introduces a new conceptual framework to the CALL and psycholinguistic domains, specifically incorporating a new psychological factor related to language learners' complex dynamic systems, known as Language Learners' Approaches to Online Language Learning (OLLA). To do so, the researchers suggested that instructors should design more practical activities for theoretical subjects such as English language learning in online learning and shift online teaching from teacher-centered to peer-centered so as to foster their learners' deep learning approach to online language learning.