نسیم گل آقایی

The present study investigated the relationships among willingness to communicate, communication apprehension, and self-perceived communication competence in Persian (L1) versus English (L2). A total number of 235 adult native Persian EFL learners were selected through convenience sampling to participate in the study. The population consisted of 118 intermediate learners and 113 upper-intermediate learners. The transferability and predictability of these communication variables across L1 and L2 was checked through correlational analyses and linear regression. The findings showed that among these variables communication apprehension was more of a trait-like predisposition which was transferred across first language and foreign language. WTC in Persian had little predictive effect on WTC in English; also, self-perceived communication competence in Persian predicted only 15% of SPCC in English. Implications of findings could provide teachers insight into the extent to which these communication variables are trait-like or situational.

 Juxtaposing the ubiquitous facets of mobile technology as everyware (Greenfield, 2010) and vocabulary as one of the most axial aspects of language learning (Bowles & Cogo, 2016; Schmitt & Schmitt, 2020) , besides the importance of considering learners’ attributes and needs (Taghizadeh, 2019) while developing a mobile vocabulary application (app), necessitates analyzing the relationship and impact of all these elements in a single structural model. To tackle the issue, first, via a mixed-methods design, the researcher developed a bespoke mobile application using the task model and the principles of agile methodology. and then investigated the impact of using the app on a sample of 62 Iranian EFL university students’ vocabulary recognition and recall, the results of which were published in two other articles. In this study, the researcher integrated the obtained data within a proposed structural model and assessed the model's fitness to investigate the interaction and interrelationship among the latent variables mentioned above. The results obtained from SEM-PLS analyses revealed that within the unified structural model, the learners’ preferences and needs were favorably influenced by their learning style orientation and technology savviness. Similarly, the findings verified the positive impact of considering learners’ preferences and needs during the agile app development lifecycle on the target participants’ vocabulary knowledge, encompassing vocabulary recognition and recall. Finally, the fitness of the proposed structural model was verified based on the criteria for model assessment mentioned by Sparks and Alamer (2022) . The SEM-PLS data analyses and the implications of the study are presented and discussed.