The role of EFL learners’ L2 self-identities, and authenticity gap on their intention to continue LMOOCs: insights from an exploratory partial least approach

Rahimi, Amir Reza

doi:10.1080/09588221.2023.2202215

Cited by 9 publications

(10 citation statements)

References 73 publications

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“…Educ. (2024) 9:49 Rahimi, 2023;Smith et al, 2020;Thorsen et al, 2017). Based on these considerations, and recoemndetations we used L2MSS as the theoretical framework and operationalized the its components based on Henry and Cliffordson's (2017) and Smith et al 's (2020) conceptual models as follows:…”

Section: Literature Reviewmentioning

confidence: 99%

“…The TAM model proposed by Davis (1989) was based on the theory of reason action (TRA; Fishbein & Ajzen, 1980), examining human behavior. However, TAM is employed, tested, and extended to dig further into any computer-based behavior in different learning contexts (Rahimi, 2023). More specifically, Davis (1989) introduced four underlying variables: perceived usefulness (PU), perceived ease of use Rahimi and Mosalli Asian.…”

Section: Technology Acceptance Model (Tam)mentioning

confidence: 99%

“…There have been calls for discovering the discrepancy between language learners' ideal L2 self and current L2 self in different language learning contexts Kangasvieri & Leontjev, 2021;Smith et al, 2020), digital self-authenticity (Rahimi, 2023;Smith et al, 2020) in OLL, extending previous findings in applied linguistics, and psycholinguistics (Rahimi & Cheraghi, 2022;Smith et al, 2020;Wang et al, 2023), exploring the role of language learners' motivation, particularly L2 selves on their language learning behaviors in OLL (Rahimi, 2023;Rahimi & Cheraghi, 2022;Zheng et al, 2018), extending the TAM model with other variables and escalating its explanatory powert in other contexts (Granić, 2022;Granić & Marangunić, 2019), and discovering the role of motivation in shaping language learners' technology acceptance in Computer-Assisted-Language Learning (CALL; Hsu, 2022;Hsu & Lin, 2021;Rahimi, 2023;Wang et al, 2022). We heed these calls by expanding the works by Henry and Cliffordson (2017) and Smith et al (2020) and extending the TAM model with university students' L2 selves in an online language learning context.…”

Section: Current Study: Research Model and Hypotheses Developmentmentioning

confidence: 99%

“…Presently, information and communications technologies (ICTs) are successfully integrated into language classrooms and bring more educational opportunities than traditional language instruction. However, the successful implication of any ICTs in language classrooms relies, to a large extent, on language users' attitudes towards them (Hsu, 2022;Rahimi, 2023). Having been highlighted by recent studies, positive attitudes towards ICTs would lead users to accept the target ICTs (Hsu, 2022;Rahimi, 2023;Wang et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…However, the successful implication of any ICTs in language classrooms relies, to a large extent, on language users' attitudes towards them (Hsu, 2022;Rahimi, 2023). Having been highlighted by recent studies, positive attitudes towards ICTs would lead users to accept the target ICTs (Hsu, 2022;Rahimi, 2023;Wang et al, 2022). Align with this, some contemporary researchs have emphasized a need to explore users' attitudes towards ICTs through psychological (Chen et al, 2020;Hsu & Lin, 2021), professional (Rahimi & Tafazoli, 2022), and technological factors (Hsu, 2022), helping administrators to have a better understanding of users' continued intention to design their programs.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the direct and indirect effects of EFL learners’ online motivational self-system on their online language learning acceptance: the new roles of current L2 self and digital self-authenticity

Rahimi,

Mosalli

2024

Asian. J. Second. Foreign. Lang. Educ.

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The impact of students' intrinsic or extrinsic motivations on their future intentions for online language schooling has been widely documented, but further emphasis needs to be placed on examining motivation beyond traditional theories. Thus, the current study sought to pivot the focus from intrinsic and extrinsic motivation to university language learners’ L2 self-identities in shaping their intention to learn language online. Toward this, we extended the technology acceptance model by integrating language learners’ L2 motivational self-system (L2MSS). Accordingly, 422 Iranian territory students who learned language online completed surveys covering language motivation and attitudes toward online language learning. The results of partial least squares structural equation modeling validated that current L2-self and digital self-authenticity can be used as separable subcomponents of L2MSS in the Iranian territory context. Moreover, learners with a higher level of future self-image and current L2 self-description found online learning more useful and easy to use. A further finding revealed an authenticity gap among higher educators since they were more motivated to learn language online than in face-to-face classrooms. Besides introducing a new conceptual framework into the literature, the researchers suggest that as a way of influencing higher education language learners’ intentions towards online language learning, lecturers should uncover language learners’ future ideal selves in advance of attending this online language course and design their language syllabus accordingly. It is also imperative for instructors to encourage students to self-describe their progress during online courses as it influenced their behavioral intention to learn languages online.

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