Faramarz Kazemainy; Hamed Barjesteh; Nassim Golaghaei; Atefeh Nasrollahi Mouzirji
Juxtaposing the ubiquitous and pervasive facets of mobile technology as everyware (Greenfield, 2010) and vocabulary as one of the most axial aspects of language learning (Bowles & ...
Juxtaposing the ubiquitous and pervasive 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 custom-made mobile app based on the task model and 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.