Abstract

A research study on the L2 Motivational Self-systems (L2MSS) and technology acceptance of Foreign Language Learners (EFL) in relation to Language Massive Open Online Courses (LMOOCs) is warranted. In response, 336 Iranian EFL learners participated in three LMOOC platforms, learned language online in line with their language institutes, and answered questions about their L2 selves’ identities and attitudes toward LMOOC. The results of Partial Least Square Structural Equation Modeling (PLS-SEM) showed that learners with positive future images of language learning and intrinsic interests in the target English culture are more likely to engage in LMOOC in the future. Further, they found LMOOC a useful and comfortable system, which enabled them to fulfill their obligations and meet others’ expectations. The authenticity gap in Iranian EFL is also worth mentioning since learners tended to have a more positive attitude toward unstructured language contexts than structured ones. As an implication of these findings, scholars should examine the factors contributing to increasing the authenticity gap in LMOOCs to accelerate the completion rate of these courses. LMOOC designers should take advantage of this issue by adding additional features to their platforms and running their courses in response to learners’ instrumentalities. The study also added a new conceptual framework to CALL, LMOOC, and language learning motivation literature.

摘要

有必要对与语言大规模开放在线课程 (LMOOC) 相关的外语学习者 (EFL) 的 L2 自我激励系统 (L2MSS) 和技术接受度进行研究。作为回应，336 名伊朗 EFL 学习者参与了三个 LMOOC 平台，根据他们的语言学院在线学习语言，并回答了有关他们的 L2 自我身份和对 LMOOC 的态度的问题。偏最小二乘结构方程建模 (PLS-SEM) 的结果表明，对语言学习有积极未来印象和对目标英语文化有内在兴趣的学习者将来更有可能参与 LMOOC。此外，他们发现 LMOOC 是一个有用且舒适的系统，使他们能够履行自己的义务并满足他人的期望。伊朗 EFL 的真实性差距也值得一提，因为与结构化语言相比，学习者往往对非结构化语言环境持更积极的态度。作为这些发现的启示，学者们应该研究导致 LMOOC 真实性差距扩大的因素，以加快这些课程的完成率。LMOOC 设计者应该利用这个问题，向他们的平台添加额外的功能，并根据学习者的工具运行他们的课程。该研究还为 CALL、LMOOC 和语言学习动机文献添加了一个新的概念框架。学者们应该研究导致 LMOOC 真实性差距扩大的因素，以加快这些课程的完成率。LMOOC 设计者应该利用这个问题，向他们的平台添加额外的功能，并根据学习者的工具运行他们的课程。该研究还为 CALL、LMOOC 和语言学习动机文献添加了一个新的概念框架。学者们应该研究导致 LMOOC 真实性差距扩大的因素，以加快这些课程的完成率。LMOOC 设计者应该利用这个问题，向他们的平台添加额外的功能，并根据学习者的工具运行他们的课程。该研究还为 CALL、LMOOC 和语言学习动机文献添加了一个新的概念框架。