This study investigates how language learners prioritize criteria for evaluating data-driven learning (DDL) tools and how these priorities relate to tool preference. While previous research has proposed multiple criteria for evaluating the perceived effectiveness of DDL tools in capturing the emic dimension of the learner experience, empirical work has scantily examined how learners differentially prioritize these criteria, or how such priority structures can be empirically incorporated into systematic comparisons of tools. Given the recent emergence of generative artificial intelligence (GenAI) in language learning, this study examines how GenAI-based tools may contribute to DDL when judged against learner-valued effectiveness criteria. Drawing on a literature review, six criteria were identified: sentence comprehensibility, relevance to semantic learning, relevance to syntactic learning, perceived pedagogical value, accessibility for independent use, and support for autonomous learning. Thirty-five Korean EFL university students completed an analytic hierarchy process (AHP) task. First, they made pairwise comparisons among the six criteria, yielding priority weights that indicated the relative importance learners attach to each aspect of DDL effectiveness. Second, the study compared the perceived effectiveness of a traditional online concordancer that accesses the British National Corpus with that of a custom-developed GenAI-based concordancer, prioritizing these weighted criteria. The results indicate that learners assign differentiated importance to the six criteria and that these priority patterns are associated with the concordance they regard as more effective. This study demonstrates the usefulness of AHP for modelling multi-criteria, perception-based evaluations of DDL tools and incorporating learners’ priority judgements into the comparison of alternative tool designs.

This study investigates how working memory (WM) abilities are implicated in second language (L2) learners’ (a) morphosyntactic achievement and (b) perceptions of required mental effort and task difficulty under oral versus written task modality conditions. Beginning-level learners of L2 Spanish completed two computerized focused tasks in which they produced output and received feedback in oral form (Speaking group) or written form (Writing group). Two grammatical structures varying in their relative level of salience were targeted. After each task, participants rated their perceptions of mental effort required and task difficulty. Production and written and aural acceptability judgment tasks were employed to measure immediate and sustained L2 morphosyntactic achievement. Executive, phonological, and visuospatial WM abilities were gauged using automated operation span, nonword recognition, and forward Corsi block-tapping tasks, respectively. Regression analyses revealed that WM capacity was predictive of L2 morphosyntactic outcomes and task perception ratings in the Speaking group only. Specifically, phonological and visuospatial WM were associated with production and acceptability judgment performance accuracy, whereas executive WM was related to learners’ ratings of perceived mental effort. Differences were also observed based on the target structure.

While the use of mobile devices for language learning has sparked the interest of an increasing number of researchers in recent years (e.g., Aizawa & Kiernan, 2003; Thornton & Houser, 2005), our knowledge of learners' preferences for the mobile platform and their usage patterns remains limited. Are learners prepared to use mobile phones for performing language learning activities, or is there still a preference for desktop computer environments? Do learners make attempts to use mobile phones and then opt for a desktop computer instead? When and where do those learners who choose to use mobile phones use them, and why do they choose them? The current study investigated 75 learners of English at a Japanese university who were assigned vocabulary learning activities which they could choose to complete on either a mobile phone or desktop computer. It sought to determine their intentions to use mobile phones for language learning if other options were available, to compare this with their actual usage patterns, and to determine when and why learners used mobile phones. Learner attitudes and preferences were elicited through a post-survey, and usage patterns were determined through analysis of detailed server logs. The results are discussed in terms of the readiness of learners to undertake mobile-based language learning activities, and the issues having an effect on the establishment of the mobile phone as a language learning tool.