Abstract
Being renowned as the state-of-the-art of open educational movement, Massive Open Online Courses (MOOCs) have been expanded noticeably in online schooling. This study aims to unify learners’ online motivational self-system and online self-regulation in MOOC. To meet this end, 358 Iranian EFL learners from five cities in Iran were signed up on two online platforms (i.e., Edmodo and Google Classroom) and responded to two questionnaires of Online Language Learning Motivation (OLLM) and Online Self-Regulation (OSEL) developed by Zheng et al. (2018). The result of the structural equation modeling (SEM) portrayed learners with positive future images and intrinsic interest in English culture that could manage their online self-regulation. Additionally, learners who learn English for their extrinsic objectives and optimize their social obligation and expectation could manipulate their language learning behaviors in MOOC. Furthermore, learners with a low online language learning experience could positively manipulate their self-regulation the implications of the current study are taking language learners’ ideal image priority on their online achievement and encouraging them to interact with the target culture in MOOC.
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In Iran, this study was approved by the Iranian Research Institute for Information Science and Technology (IranDoc) with the code 11920028 and Shahid rajaee teacher training university (SRTTU) as a research project of the Amir Reza Rahimi Master thesis.
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Rahimi, A.R., Cheraghi, Z. Unifying EFL learners’ online self-regulation and online motivational self-system in MOOCs: A structural equation modeling approach. J. Comput. Educ. 11, 1–27 (2024). https://doi.org/10.1007/s40692-022-00245-9
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DOI: https://doi.org/10.1007/s40692-022-00245-9