This paper focuses on automatically assessing language proficiency levels according to linguistic complexity in learner English. We implement a supervised learning approach as part of an automatic essay scoring system. The objective is to uncover Common European Framework of Reference for Languages (CEFR) criterial features in writings by learners of English as a foreign language. Our method relies on the concept of microsystems with features related to learner-specific linguistic systems in which several forms operate paradigmatically. Results on internal data show that different microsystems help classify writings from A1 to C2 levels (82% balanced accuracy). Overall results on external data show that a combination of lexical, syntactic, cohesive and accuracy features yields the most efficient classification across several corpora (59.2% balanced accuracy).

The aim of this study is to comprehensively evaluate quantitative experimental mobile-assisted language learning (MALL) studies published between 1994 and 2019 that meet minimal conditions of research design and statistical analysis. Starting with a bibliographical database of 1,144 references to experimental MALL implementations, of which there were 700 objectively substantiated by quantitative experimental language learning outcomes, only 84 experimental MALL studies met the inclusion requirements. Their analysis addresses two critical sets of research questions. First, what are the general characteristics of the selected studies and, second, what are their language learning outcomes in terms of measured effect size. Nine general characteristics are considered: publication source, chronological distribution, country of origin, institutional environment, sample size, intervention duration, targeted language, language learner competence level, and learning focus. Effect size was calculated separately for between-group (independent, experimental) and within-group (quasi-experimental) treatment studies. In both cases, the overall results were quite large: 0.72 for the former and 1.16 for the latter. An analysis of four critical moderator variables (language learner competence level, language area focus, institutional environment, and intervention duration) revealed similarly large effect sizes. Notwithstanding, analysis of the data also confirmed obvious publication bias and a very high level of heterogeneity that frequently approached 100%. The relevance of positive language learning outcome conclusions thus needs to be tempered by these shortcomings.

In an increasingly ageing, multilingual, and digitalised society, there is still a lack of research on older adults’ adoption and use of mobile technology for supporting their self-directed second language learning. In the present study, we investigated the extent to which seniors residing in Germany (aged 60+) engage in mobile-assisted language learning (MALL) and the factors encouraging or discouraging them from using language learning apps by conducting a web-based survey (n = 208) and a series of in-depth individual interviews (n = 22). Our results show that (1) participants were resistant to fully embrace the potential of MALL despite their active engagement in language learning and extensive use of digital technology, online resources, and mobile devices; and (2) self-perceived digital literacy and openness towards new developments are strong factors favouring the use of language learning apps in older adulthood. We interpret and discuss these results in the light of theoretical accounts of mobile learning and education in (older) adults, emphasising the need to consider the specific requirements of late-life learners in future implementations of language learning apps. Based on our results, we highlight several implications for designers and developers of such apps intended to facilitate full inclusion of seniors as mobile language learners.

This paper presents IdiomsTube (https://www.idiomstube.com), the first-ever computer-assisted language learning tool for facilitating the learning of English idiomatic expressions from YouTube videos. The web-based tool is designed to automatically (1) assess the speech rate and lexical difficulty level of any learner-chosen English-captioned YouTube video; (2) generate a range of vocabulary-building and revision tasks (e.g. fill-in-the-blanks, the classic spelling game hangman, pronunciation, flashcards); and (3) recommend YouTube videos based on learners’ individual learning progress, class teachers’ instructions, and current trends. This paper describes the app’s current features in conjunction with the challenges endemic in the development of applications that automatically generate English language learning content out of internet video content. At the time of writing, the IdiomsTube app had over 8,000 registered users worldwide.

The present study aims to verify the impact of dynamic aids on learning L2 prepositions in relation to individual learner variables. Situated within the cognitive linguistics (CL) framework and differing from previous research, the present study hypothesizes that dynamic (animated) aids are not equally effective for all learners; rather, their effectiveness differs according to learners’ first languages (L1s) (Chinese or Japanese) and information-processing styles (verbalizers or imagers). To verify this hypothesis, we utilized learning materials comprised of static and dynamic images for three English spatial prepositions (above, on, over). After conducting a Style of Processing questionnaire, we administered three cloze tests (pretest, posttest, and delayed posttest) of target words to Taiwanese and Japanese participants (N = 109), whose L1s differed in terms of their linguistic proximity to English. Although no significant differences were found between the treatment groups in tests for all participants, the results were differentiated by individual factors. In results of a two-way ANOVA, Taiwanese participants showed significantly greater improvement from the pretest to posttest than Japanese participants when the participants used dynamic images, whereas the Japanese group made more learning gains from the posttest to the delayed posttest test. Moreover, imagers obtained more benefits from the visual aids, whether static or dynamic, than verbalizers. Our findings indicate that CL-based visual aids are beneficial and that individual factors, especially learners’ L1, may produce different learning effects, especially in multimedia environments.

The aim of the paper is to investigate the usefulness of different illustration formats in online English learners’ dictionaries for the accuracy and speed of meaning comprehension as well as immediate and delayed retention. In a controlled online experiment, the meaning of selected English words and phrases had to be explained with the help of purpose-built monolingual dictionary entries. Four experimental conditions were created, which reflected the presence and format of illustrations in the entries: color pictures, greyscale pictures, line drawings, no illustrations. Meaning retention was checked immediately after exposure and two weeks later. The results show that it is worthwhile to include illustrations in online learners’ dictionaries and suggest the most beneficial illustration formats. Line drawings prove the most recommendable; they considerably improve meaning comprehension, reduce reception time, and stimulate the best immediate and delayed retention. Color pictures emerge as the second best. They produce results comparable with those for line drawings, except they do not help so much to remember meaning in the long run. Entries with greyscale pictures are the least recommendable. They do not contribute more to meaning comprehension and delayed retention. Yet, they even shorten reception time and help users to remember more words immediately after exposure.

This meta-analysis examines the effectiveness of technology-assisted second language (L2) vocabulary learning as well as identifies factors that may play a role in their effectiveness. We found 34 studies with 2,511 participants yielding 49 separate effect sizes. Following the procedure developed by Hunter and Schmidt (2004), we corrected for sample size bias and measurement error. The overall effect size for using technology to learn L2 vocabulary was d = 0.64, which is a moderate effect size. The Q statistic indicated a significant variability in effect size, so we followed up with a theory-driven moderator analysis. The results of the moderator analysis revealed that learners benefited more from technology-assisted L2 vocabulary learning with incidental instruction than with intentional instruction; types of assessment were not significant moderators of the effect on technology-assisted L2 vocabulary learning; technology-assisted L2 vocabulary learning is more effective when the target language is close to the learner’s first language; college students benefited more from technology-assisted L2 vocabulary learning than K–12 students; and, finally, mobile-assisted L2 vocabulary learning was more effective than computer-assisted L2 vocabulary learning.