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\"Level 1 of a complete self-study English-language course that combines easy-to-use visual learning with crystal-clear grammar explanations, practice exercises, and free audio.\"--from page 4 of cover.

Artificial Intelligence (AI) plays an increasingly important role in language education; however, the trends, research issues, and applications of AI in language learning remain largely under-investigated. Accordingly, the present paper, using bibliometric analysis, investigates these issues via a review of 516 papers published between 2000 and 2019, focusing on how AI was integrated into language education. Findings revealed that the frequency of studies on AI-enhanced language education increased over the period. The USA and Arizona State University were the most active country and institution, respectively. The 10 most popular topics were: (1) automated writing evaluation; (2) intelligent tutoring systems (ITS) for reading and writing; (3) automated error detection; (4) computer-mediated communication; (5) personalized systems for language learning; (6) natural language and vocabulary learning; (7) web resources and web-based systems for language learning; (8) ITS for writing in English for specific purposes; (9) intelligent tutoring and assessment systems for pronunciation and speech training; and (10) affective states and emotions. The results also indicated that AI was frequently used to assist students in learning writing, reading, vocabulary, grammar, speaking, and listening. Natural language processing, automated speech recognition, and learner profiling were commonly applied to develop automated writing evaluation, personalized learning, and intelligent tutoring systems.

Hundreds of millions of language learners around the globe study a second language with popular apps such as Duolingo, Rosetta Stone, Busuu, and Babbel. This study examined the effectiveness of one app, Babbel, for developing both receptive linguistic knowledge of vocabulary and grammar, as well as oral communicative ability in Spanish as a second language. Fifty‐four English speakers not enrolled in Spanish classes studied Spanish on Babbel over the course of 12 weeks, with a goal of studying roughly 10 min per day. Participants completed pretests and posttests, and provided data on their motivation to learn Spanish and use Babbel. Results showed that learners were able to develop grammar and vocabulary knowledge as well as oral communicative ability. The amount of Babbel study time was the strongest predictor for all three measures, with motivation to learn Spanish also significantly predicting growth in oral communicative ability. The Challenge Hundreds of millions of learners use digital apps to learn world languages, but how effective are these apps for learning how to speak a second language? To answer this question, this article compares the grammar, vocabulary, and speaking development of 54 learners who spent three months studying Spanish with the app Babbel.

While the use of automated writing evaluation software has received much attention in CALL literature, as Frankenberg-Garcia (2019) notes, empirical research on predictive text and intelligent writing assistants is lacking. Thus, this study addressed this gap in the literature by examining the impact of Grammarly, an intelligent writing assistant that incorporates predictive text technology, on the mobile writing quality of Japanese L2 English students. Specifically, the study explored if Grammarly had a significant effect on the grammatical accuracy, lexical richness, writing fluency, or syntactic complexity of L2 students’ writing when compared to unassisted mobile writing. A total of 31 university EFL students participated in the 8-week study which utilized a counterbalanced design. Participants took part in weekly guided freewriting tasks under each writing condition (on-Grammarly and Grammarly) over the duration of the study. The descriptive statistics and results from t-tests showed that when students wrote with the assistance of Grammarly, they produced fewer grammatical errors and wrote with more lexical variation. These findings highlight the potential of predictive text and real-time corrective feedback as a way to support L2 writing, particularly among novice writers who may struggle to write effectively in the L2.

This emerging technology report delves into the role of ChatGPT, an OpenAI conversational AI, in language learning. The initial section introduces ChatGPT’s nature and highlights its features, including accessibility, personalization, immersive learning, and instant feedback, which render it a valuable asset for language learners and educators alike. Subsequently, the paper discusses recent empirical studies investigating its impact, revealing that it is best suited to complement traditional instruction, forging a symbiotic relationship that empowers language learners. The report concludes with some limitations and associated challenges in utilizing ChatGPT within language learning contexts.

This study presents the IDOL model (Arafah, 2019), a framework that integrates literature and Computer-Assisted Language Learning (CALL) into developing ELT materials. Structured in four systematic stages, the model demonstrates how pedagogical principles—combining literature with technology-enhanced instruction—lay the foundation for creating a prototype of CALL resources enriched with literary content. This rigorous development research was conducted at Alauddin State Islamic University Makassar, involving 73 participants, including 53 students, 10 lecturers, and 10 graduates from an EFL program. Data collection methods included needs analysis questionnaires, interviews, and evaluation checklists. Guided by the IDOL model, the developed prototype served as a versatile teaching resource for English instruction in the university's EFL program, functioning effectively as both primary and supplementary material. The application of the IDOL model illustrates the creation of robust teaching materials that integrate the rich potential of literature in language instruction, the interactivity of technology, and strong pedagogical foundations. This study offers a valuable framework for future projects to develop CALL materials that harness the potential of literature in English Language Teaching (ELT), inspiring educators and material designers alike.

This study extends research on written corrective feedback (CF) by investigating how timing of CF affects grammar acquisition. Specifically, it examined the relative effects of synchronous and asynchronous CF on the accurate use of the hypothetical conditional structure. Participants were 68 intermediate-level students of English at a university in Japan. Learners from a synchronous CF group (SCF), an asynchronous CF group (ACF), and a comparison group completed 2 writing tasks using Google Docs. The 2 experimental groups received focused direct CF with the following differences: The SCF group received synchronous feedback on grammatical errors during writing tasks, while the ACF learners received feedback after the tasks. Participants revised their texts upon receiving the feedback. The comparison group completed the writing tasks without feedback. Accurate use of the target feature was measured by a set of 3 text reconstruction tasks conducted as pre-, immediate post-, and delayed posttests. The results showed that both experimental groups significantly improved from the pretest to the 2 posttests while the comparison group did not. Overall, however, effect sizes for the posttests indicated that SCF was more effective in improving learners' accuracy with only the SCF group outperforming the comparison group on the delayed posttest.

Computer-assisted textual enhancement (CATE) technology has been widely used to improve English as foreign language (EFL) learners’ syntactical and grammatical learning. Visual attention, repetition, and prior knowledge are known as the vital factors in CATE-assisted knowledge-acquisition; however, there still lacks a model which can describe those factors’ intrinsic cooperating-mechanism that works in the CATE-based knowledge-acquisition. Therefore, this paper built up a computational model (PESE) of using those factors as variables, by fitting and predicting the data collected from empirical experiments with an average accuracy of 78%, PESE testified and complemented the assumptions proposed by previous studies. PESE suggested that although the efficacy of CATE is majorly decided by learners’ prior-knowledge of the targets, the interactive effects of visual-attention, repetition, and inductive activity could partly compensate for the effect from prior-knowledge, and the efficacy ceiling of repetition also could be estimated according to the ‘easy-perceiving level’ coefficient. At the end of this paper, 3 pedagogical implications were proposed for English teachers who are willing to integrate CATE into their teaching activities.

The current study investigated task effects on listener perception of second language (L2) comprehensibility (ease of understanding). Sixty university-level adult speakers of English from 4 first language (L1) backgrounds (Chinese, Romance, Hindi, Farsi), with 15 speakers per group, were recorded performing 2 tasks (IELTS long-turn speaking task and TOEFL iBT integrated listening/reading and speaking task). The speakers' audio recordings were evaluated using continuous sliding scales by 10 native English listeners for comprehensibility as well as for 10 linguistic variables drawn from the domains of pronunciation, fluency, lexis, grammar, and discourse. In the IELTS task, comprehensibility was associated solely with pronunciation and fluency categories (specifically, segmentals, word stress, rhythm, and speech rate), with the Farsi group being the only exception. However, in the cognitively more demanding TOEFL iBT integrated task, in addition to pronunciation and fluency variables, comprehensibility was also linked to several categories at the level of grammar, lexicon, and discourse for all groups. In both tasks, the relative strength of obtained associations also varied as a function of the speakers' L1. Results overall suggest that both task and speakers' L1 play important roles in determining ease of understanding for the listener, with implications for pronunciation teaching in mixed L1 classrooms and for operationalizing the construct of comprehensibility in assessments. (Verlag).

PurposeThis study aims to explore computer-assisted language learning (CALL) activities to improve the English essay writing of Pakistani university students. It highlights the role of CALL in the language proficiency model cognitive academic language proficiency (CALP), which can enable second language learners to engage in more critical thinking skills effectively. Furthermore, it aims to explore English language teachers’ experience about the use of CALL-based activities in English language classrooms or labs.Design/methodology/approachThis study followed a pre-post study design to examine whether the structure of an essay and computer-based activities helped to improve English language proficiency among non-native speakers. This design is adopted to investigate the effects of CALL activities on students’ English essays. This study used data from 198 students and after this, four English teachers were interviewed to know their opinions and observations about these CALL-based activities and students’ essay writings. Pre- and post-test data was analysed in percentages and further examined through a t-test. The findings of teachers’ interviews were further analysed through Nvivo software to develop an understanding of research questions through significant themes.FindingsThe pre-test results confirmed that students’ language proficiency is underdeveloped and informal. Students needed help constructing introductory paragraphs with the reader’s hook, background information, three-point thesis statement and transitional hook. Whereas, post-test results showed that students’ English language proficiency in essay writing was found improved with the use of technological tools and CALL-based activities. Furthermore, it was observed that structure and teacher feedback in essay writing are vital for English proficiency.Originality/valueThis study benefits English language teachers, administrators, language policymakers and syllabus designers at colleges and universities. The debate over how to improve English language proficiency and academic achievement presents diverse challenges across several countries. Non-native speakers, at an undergraduate level, can significantly improve academically and become proficient in English essay writing with the help of structural guidelines and the use of educational technology. This article demonstrates a two-way process to improve an objective definition of English language development, which is conceivable if the technology is adopted.