This study investigates the autonomous digital language learning practices of English as a Foreign Language (EFL) learners outside traditional classroom settings, with a focus on the roles of motivation, academic tracks, and English proficiency levels. Using a mixed-methods approach, the research examines how learners incorporate digital tools into their language learning, the types of activities they engage in, and the factors shaping their autonomy. The findings show that informal digital activities, such as listening to music, watching TV, and browsing the internet, are the most common, largely driven by intrinsic motivation. In contrast, more structured activities, such as attending self-study centers or writing diaries, are less frequently pursued. The study underscores motivation as a key factor in fostering learner autonomy and recommends educational strategies that promote both informal and structured digital learning. These insights offer valuable implications for enhancing learner autonomy and improving language learning outcomes in an increasingly digitalized educational environment.

The Dalton Plan, an educational approach centered on student autonomy through assignment contracts and self-paced learning, offers a potential alternative to traditional teacher-center instruction. This study examines its application within the challenging context of Chinese College English (CE) reading courses, where students often struggle with academic reading comprehension and lack self-regulation skills. A quasi-experimental design was employed to evaluate the impact of Dalton Plan-based instruction on the reading performance and learner autonomy of 31 second-year medical students. Participants were divided into a control group (n=15) receiving conventional instruction and an experimental group (n=16) receiving Dalton Plan-based instruction, which emphasized independent reading assignments with tailored teacher guidance. A mixed-methods approach collected quantitative data (reading tests, Autonomous Learning Scale) and qualitative data (thematic analysis of student self-reports). Results indicated that Dalton Plan-based instruction significantly enhanced learner autonomy; however, its effect on reading test scores was not statistically significant. Thematic analysis of self-reports revealed a developmental trajectory from initial challenges—such as time management and vocabulary inadequacy—to later progress in reading interest, strategy use, and persistence. These findings not only provide pedagogical insights for innovating reading instruction in Chinese EFL (English as foreign language) contexts but also highlight the complex relationship between fostering autonomy and achieving measurable gains in reading proficiency.

This mixed-methods study aimed to investigate the optimal timing for model-text-based written corrective feedback by examining Bahraini university second language learners’ perceptions in large-class settings. The primary research question focused on whether students find model texts more practical and effective when received before or after writing. Addressing this is significant for developing scalable feedback solutions in massified higher education contexts, such as those in the Gulf region, where traditional WCF is often logistically impractical. Sixty students were divided into an experimental group, which received model texts after writing, and a control group, which received them before. Data from a perception questionnaire and reflective notes were analyzed. Results indicated that the experimental group perceived post-task models as significantly more useful, relevant, noticeable, and practical than the control group, with large effect sizes. Qualitative analysis revealed that receiving models after writing enhanced metacognitive awareness, allowing students to identify specific gaps in their own writing and fostering a sense of ownership. The study concludes that post-task model-text written corrective feedback is a highly effective and practical feedback strategy in large-class contexts. Therefore, it is recommended that second language writing instructors and curriculum designers strategically implement model texts as a post-writing feedback tool to foster learner autonomy and address the feedback gap in large classes.

In recent years, artificial intelligence has moved from the margins of education to its very core, profoundly reshaping how English is taught and learned. This study offers a descriptive bibliometric overview of research on AI-assisted English language teaching (AI-ELT) based solely on data retrieved from the Scopus database between 2019 and 2025. Rather than relying on external analytic software, the analysis was conducted directly through Scopus’s built-in tools to ensure transparency and reproducibility. The findings reveal an exceptional surge in academic productivity, especially after 2022, when generative models such as ChatGPT began influencing classroom practice and teacher research alike. Most publications are concentrated in the fields of social sciences and education, followed by computer science and the humanities, confirming the hybrid nature of AI-ELT as both a pedagogical and technological domain. The most active contributors and institutions are clustered in East Asia particularly in Hong Kong, mainland China, Taiwan, and Singapore reflecting the region’s growing leadership in educational AI. Overall, the results indicate a paradigmatic shift from automation toward cognition and reflection in English pedagogy. AI is increasingly viewed not merely as a tool for efficiency but as a partner in meaning-making, creativity, and learner autonomy. The study concludes that future research should deepen empirical validation, explore teacher AI collaboration, and strengthen ethical frameworks that support human-centered innovation in language education.

The development of practical academic writing skills is essential for university success, especially in EFL students. This study, with a quantitative approach and a quasi-experimental design, evaluated the effectiveness of the use of the Virtual Writing Tutor (VWT) in second-year English students at the Centro Regional Universitario de Veraguas, Universidad de Panamá, to improve the writing of topic, supporting, and concluding sentences. Pre-test and post-test were applied using instruments validated by experts to measure the three dimensions of writing. The results showed significant improvements, especially in the writing of topic sentences, with an average increase of 29.2 %. Supporting sentences improved by 17.7%, while concluding sentences improved by only 4.7%. The use of the VWT increased learner autonomy, motivation, and confidence by providing immediate feedback on grammar and structure. It is concluded that the VWT is an effective tool when combined with didactic strategies, and its integration strengthens the teaching of academic writing in EFL learning contexts.

This In the era of learner-centered education, the role of lecturers in academic advising has shifted from providing procedural guidance to cultivating pedagogical awareness that promotes students' learning autonomy. This study explores how lecturers interpret and apply pedagogical awareness in academic advising to foster students' autonomous learning capacities. Using a thematic phenomenological approach, data were collected through in-depth interviews with 10 academic advisors at a public university in Indonesia. The analysis revealed three core themes: (1) reflective-dialogic engagement, (2) facilitation of metacognitive awareness, and (3) value-based mentoring. The findings highlight the importance of pedagogical consciousness not only as a conceptual framework but as a lived experience that shapes academic mentoring practices. This study contributes to the discourse on academic advising by emphasizing the transformative potential of pedagogical awareness in nurturing learner autonomy within higher education.

ABSTRACT This study reports on the design, implementation, and evaluation of an AI‐Supported Pedagogical Architecture (PA) aimed at fostering Self‐Regulated Learning (SRL) within a Virtual Learning Environment (VLE). The architecture was integrated into the Moodle platform and applied in an introductory Python course. It incorporates technological tools such as Completion Progress, Analytics Graphs, Athena, and the Time Tracker SRL plugin to deliver real‐time feedback, facilitate progress monitoring, and support learners in goal setting, planning, and reflection–key dimensions of SRL. Through Educational Data Mining techniques, the study identifies distinct learner profiles based on interaction logs, revealing a significant correlation between SRL strategies and academic achievement. Additionally, qualitative data from focus groups underscore the architecture's effectiveness in enhancing metacognitive awareness, student engagement, and overall satisfaction, demonstrating its potential to support the development of learner autonomy in online education.

The rapid digital transformation in education demands innovative curriculum design that aligns with 21st-century competencies. A digital innovative curriculum serves as a key strategy to enhance students’ critical thinking, creativity, collaboration, and communication skills in facing digital-era challenges. This study aims to analyze the role and effectiveness of an innovative digital curriculum in improving students’ abilities in the digital era. The method used is a literature review by examining recent studies on technology-based curriculum models and competency-based learning. The findings indicate that implementing an innovative digital curriculum that integrates information technology, project-based learning, and authentic assessment can improve students’ digital literacy, learning autonomy, and creativity. Therefore, an innovative digital curriculum plays an essential role in shaping adaptive, productive, and competent learners ready to face global technological developments.

Abstract This study examines the potential of synchronous oral telecollaborative tasks to foster learner autonomy among young language learners. Previous research highlights both the language learning affordances of technology-mediated task-based language teaching and challenges for successful implementation with young learners and suggests that learner autonomy is an important mediating variable. The present article investigates autonomy by exploring learner participation during task-as-process and the teacher’s role in creating opportunities for learning in technology-mediated exchanges. We propose a new analytical framework based on the notion of arena , drawing on Goffman’s dramaturgical concept of frontstage versus backstage interaction, to inform a fine-grained investigation of turn-taking during the same task-as-workplan implemented in two French primary school classrooms with learners of English of CEFR A1 level. Quantitative analysis of the interaction data revealed contrasting participation patterns in various task phases and across different areas of the interactional arena. In one class, learners managed the task independently; the teacher intervened only once, and learners exhibited significantly higher on-task time and greater frontstage engagement. In the other class, the teacher participated in backstage task management, providing prompting and echoing, and also in frontstage interaction, and this in all task phases. The study underlines young learners’ capacity for successful L2 interaction in synchronous telecollaboration and traces critical links between learner autonomy and teachers’ interpretation of tasks.

In the study “Didactic Innovation and Digital Inclusion in Language and Literature: Applications of Emerging Technologies, Gamification, and Artificial Intelligence in the 21st-Century Classroom”, the teaching-learning processes embrace complex problem-solving and systemic educational transformation. It is grounded in the need to transform the teaching of Language and Literature within the context of the digital age through the use of emerging technologies, active methodologies, gamification, and artificial intelligence (AI) as drivers of inclusion, active and meaningful learning, and the reduction of the digital divide. The research followed a mixed-method approach with a quasi-experimental and descriptive design, employing surveys, observations, and performance analyses in primary and secondary education classrooms. Gamified didactic environments, adaptive AI systems based on gamification, and collaborative digital settings were designed and implemented. The analysis of the results revealed significant improvements in students’ reading comprehension and written expression, as well as in their active participation, autonomy, and self-regulation in learning. Moreover, the pedagogical use of inclusive technologies strengthened teachers’ competencies. Among the key findings, the most notable was the promotion of educational equity alongside the enhancement of innovative, flexible, creative, and complex digital problem-solving skills, resulting in a more personalized and ethical educational ecosystem. It is also concluded that the convergence of gamification and artificial intelligence serves as a catalyst for systemic and paradigmatic change in education, with the goal of building inclusive, critical, and sustainable educational ecosystems.

Introduction Educational accompaniment (EA) has gained increasing relevance in recent years, particularly in Spain, with applications across education, healthcare, and social domains. Despite its growing presence, there is no comprehensive synthesis of the academic literature on EA. This review aims to identify and analyze the main models, definitions, and benefits associated with EA. Methods A scoping review was conducted using three databases: Web of Science, Scopus, and nDICEs-CSIC. The search focused exclusively on the term educational accompaniment, which narrowed the scope but ensured conceptual specificity. Inclusion criteria targeted studies that explicitly addressed EA, excluding those using the term in a colloquial or unrelated sense. A total of 28 studies were selected and analyzed following PRISMA guidelines. Results The review identified four distinct paradigms of EA: psychosocial, personalist, socio-educational, and competency-based. Each model is grounded in specific theoretical and methodological frameworks. An integrated definition of EA is proposed as an intentional educational action through which one person enlightens and supports another in their integral development, facilitating their autonomy, maturity, and realization of a fulfilling life. Key findings highlight the importance of the quality of the accompaniment relationship, sustained engagement, practitioner training, and stakeholder coordination. Reported benefits include enhanced learner autonomy, holistic development, and improved employability. Discussion EA emerges as a salient and evolving discipline with strong theoretical foundations and practical relevance. It is increasingly recognized as a valuable pedagogical approach in diverse fields, including education, healthcare, and social services, where its relational and formative nature supports autonomy, personal growth, and holistic development.

Learner autonomy-the ability to self-direct and regulate learning-is a key determinant of success in online education, yet its quantifiable impact in voluntary noncredit courses remains unclear. Understanding how autonomy translates into measurable behaviors and outcomes in clinical skills training may inform more effective online learning design and learning outcomes. This study aims to quantify the association between behavioral indicators of learner autonomy and performance in a voluntary noncredit online cardiac auscultation course. We conducted a prospective, self‑controlled, single‑center study. A total of 199 registrants (n=122 physicians and n=77 medical students) were recruited via WeChat and attended four weekly 2‑hour synchronous sessions using authentic patient heart sound recordings with imaging‑based explanations. The primary outcome was the final posttraining quiz score (0-100); training effectiveness was assessed by the pre‑ to posttraining score change. The autonomy indicators were full participation (attendance at all four sessions), in‑class engagement (number of responses to brief content‑aligned prompts posed approximately every 10-15 minutes; responses recorded for participation monitoring only), and postclass review (frequency/duration of reviewing recordings and materials). Analyses included Wilcoxon signed rank tests, χ2 tests, multivariable linear regression, and receiver operating characteristic profiling of "excellent learners" (top 10% improvement). Of the 199 registrants, 146 (73.4%) attended ≥1 session and 46 (23.1%) completed all sessions. Median test scores improved from 40 (IQR 20-50) to 70 (IQR 50-83; P<.001). Intrinsic motivation was associated with full participation (χ21=4.03; P=.045). In multivariable models, full participation (unstandardized B=41.55, 95% CI 24.43-58.67; standardized β=0.60; P<.001) and in‑class engagement (B=4.79 per additional response, 95% CI 3.05-6.45; β=0.70; P<.001) independently predicted higher final scores (adjusted R2=0.48). Receiver operating characteristic profiling indicated that greater postclass review (recordings/materials) led to learners achieving excellent performance. In this voluntary online clinical skills course, showing up consistently, engaging during class, and reviewing after class-practical expressions of learner autonomy-were key correlates of short-term performance. These behaviors may be encouraged through simple, feasible course designs such as clear expectation setting, periodic interactive prompts, and structured review opportunities, which warrant prospective evaluation in future studies.

Background and Aims: This study investigates the development and implementation of a Japanese language blended teaching model specifically designed for Chinese university students, leveraging advanced digital technologies. The integration of online and offline learning modes is vital in language education as the educational landscape evolves. This research aims to address the innovative challenges faced by students and educators in the Japanese language major within Chinese universities. The study proposes a blended teaching model that combines traditional face-to-face instruction with digital learning tools. Methodology: This study used a mixed-method approach, utilizing pre- and post-tests to assess language proficiency, surveys to evaluate student engagement and satisfaction, and learning analytics to track digital platform usage. Expert reviews were also conducted to ensure instructional quality and validate the blended teaching model’s implementation outcomes Results: The results of the study showed that there was a significant increase in student engagement, language proficiency, and overall satisfaction with the learning experience under this blended learning model. The study also highlighted the importance of flexibility, interactivity, and personalized learning pathways in enhancing language acquisition through blended learning. Conclusion: Integrating digital technology and adopting a blended teaching model in Japanese language teaching in Chinese universities meets the language learning needs of students at different levels and improves the effect of language learning. It also cultivates students' digital literacy and learning autonomy and motivation, thus further improving the quality of foreign language learning and teaching. This research contributes to the growing body of literature on blended learning in language education and offers practical insights for educators seeking to innovate their teaching practices. Future research should examine adaptive learning or conduct comparisons with alternative language teaching models.

Conventional lecture-based instruction in music theory often falls short in fostering deep engagement, critical thinking, and applied musicianship—particularly in educational contexts shaped by teacher-centered traditions. This study presents the design, implementation, and empirical evaluation of a Flipped Classroom Module (FCM) tailored to undergraduate music theory instruction in Chinese higher education. Grounded in a tripartite theoretical framework integrating Self-Directed Learning, Course Development Theory, and Collaborative Learning Theory. The module employs a three-phase instructional sequence—pre-class preparation, in-class collaboration, and post-class reflection—delivered through a customized learning management system. A quasi-experimental design (N = 60) compared the FCM group with a traditional instruction control group across both cognitive and practical learning domains. Validated pre- and post-tests assessed music-theoretical knowledge and applied skills, and statistical analyses (independent and paired-sample t-tests) revealed significant learning gains in the FCM group (p < .05). Beyond confirming the pedagogical efficacy of the flipped approach, the study demonstrates how culturally responsive instructional design can enhance accessibility, learner autonomy, and instructional coherence within constrained curricular environments. The findings contribute to ongoing international discourse on digital transformation in higher music education and offer a replicable framework for theory-informed, discipline-specific flipped pedagogy.

In the evolving landscape of digital education, there is an increasing need to enhance traditional Learning Management Systems (LMSs) by integrating innovative pedagogical practices that promote active participation and learner autonomy. This study presents the transformation of a Greek LMS platform into an open learning ecosystem, incorporating three key educational innovations: collaborative hackathons, microcredentials, and blended learning support. The primary goal was to modernize the LMS in a way that encourages deeper engagement, social learning, collaboration, and mixed learning. To accomplish this objective, the system integrated advanced innovative tools designed to facilitate structured collaborative processes including hackathons, microcredentials aligned with specific learning objectives, and blended learning through flexible content delivery and student learning tracking tools. The use of these tools in the educational process contributes to the creation of a more dynamic and participatory learning environment, where knowledge is co-shaped and learning acquires a social character. In addition, the tools promote differentiated learning, allowing students to engage at their own pace and in their own way.

The integration of Artificial Intelligence (AI) into online education is rapidly transforming learning environments, particularly for adult learners. While AI promises personalized and efficient educational experiences, its impact on crucial affective domains, such as student confidence and self-efficacy, remains underexplored. Confidence is a critical determinant of persistence, engagement, and success in adult learning. This meta-analysis and systematic review synthesizes current empirical evidence to evaluate the effect of AI-powered tools and platforms on student confidence in online adult learning contexts. A systematic search of major academic databases was conducted to identify peer-reviewed studies published between 2019 and 2025 that investigated AI interventions in online adult education and measured outcomes related to student confidence or self-efficacy. Following PRISMA guidelines, we screened and selected studies for inclusion. We performed a quantitative synthesis of reported effect sizes and a qualitative thematic analysis to identify the mechanisms through which AI influences learner confidence. Our analysis of the included studies reveals a predominantly positive and significant effect of AI on student confidence. A quantitative synthesis of studies providing effect sizes revealed a large, positive impact (mean Cohen's d = 1.24). The thematic analysis identified four key mechanisms: (1) Enhanced scaffolding and personalized support, where AI provides immediate, non-judgmental feedback that builds mastery; (2) Fostering autonomy and self-directed learning, empowering learners to take control of their educational journey; (3) The double-edged sword of dependence, where over-reliance on AI can potentially undermine intrinsic confidence; and (4) The amplification of human connection, where AI tools, when used effectively, free up instructor time for more meaningful, confidence-building interactions. When thoughtfully designed and implemented, AI technologies can be powerful tools for enhancing confidence among online adult learners. The most effective interventions are those that use AI to augment, rather than replace, human instruction, providing personalized support while fostering learner autonomy. These findings provide crucial insights for educators, instructional designers, and policymakers seeking to harness AI to create more supportive and empowering online learning environments for adults.

This study investigates the implementation of Speech-to-Text (STT) and Text-to-Speech (TTS) technologies in multimodal English as a Foreign Language (EFL) assessment for students with disabilities in Indonesian special senior high schools (SMALB). Using an embedded mixed-methods design, the research involved 25 students with diverse disabilities, alongside teachers and support staff, to explore how STT and TTS tools support inclusive pedagogy and assessment. Qualitative data from observations, interviews, and student work samples were integrated with quantitative results from language performance tests and attitude questionnaires. The findings indicate that STT and TTS technologies enhanced accessibility, engagement, and learner autonomy, allowing students to demonstrate language competence through alternative modalities aligned with Universal Design for Learning (UDL) principles. Teachers reported increased sensitivity to learner diversity and adopted more flexible, student-centered assessment strategies. Quantitative analyses showed significant improvements in students' speaking and writing performance, as well as positive shifts in motivation and confidence. Despite implementation challenges such as limited infrastructure and teacher readiness, the study highlights the transformative potential of assistive technologies in advancing equitable and meaningful EFL instruction in inclusive settings. These insights contribute to the growing discourse on inclusive digital education in under-resourced contexts and inform future policy, practice, and teacher training initiatives.

Artificial intelligence is reshaping higher education, with chatbots increasingly explored as virtual assistants for language learning. This study investigates Malaysian students' awareness, usage, and expectations of chatbots in tertiary education. A survey of 101 students from Klang Valley institutions across disciplines such as Teaching English as a Second Language (TESL), nursing, business, and engineering was conducted. Findings show that although awareness of chatbots is high, their actual use for language learning remains limited. Nevertheless, students strongly expressed interest in using chatbots for grammar, pronunciation, vocabulary, and conversational practice. The study suggests that integrating chatbots could promote learner autonomy, instant feedback, and student-centred pedagogy.

The aim of this study is to examine the relationship between learner autonomy and lifelong learning skills of secondary students in foreign language education. The study employed a correlational survey model, one of the quantitative research methods. The population consists of students attending secondary schools in the district of Yunusemre in Manisa province in 2024. The study sample comprises 647 secondary school students, selected using convenience sampling, one of the purposive sampling methods. As data collection tools, the "Learner Autonomy Scale" developed by Orakçı (2017) and the "Lifelong Learning Skills Scale" developed by Çiftcibaşı et al. (2020) were utilized. Data analysis was conducted using SPSS 25.0 statistical software, and Pearson Correlation analysis was performed to determine the relationship between students' learner autonomy and lifelong learning skills. One-Way Analysis of Variance (ANOVA) and Independent Samples T-test were conducted to determine whether or not participants' learner autonomy and lifelong learning skills differed according to various variables. The findings revealed that students' learner autonomy levels were at a high level, while their lifelong learning skills levels were at a moderate level. Based on the correlation analysis conducted, a statistically positive, and low-level significant relationship was found between learner autonomy in foreign language education and lifelong learning skills of secondary school students.

This review article examines the integration of human-machine teaming principles into college English speaking classroom design with the specific objective of enhancing students' willingness to communicate. As educational technology continues to evolve, the convergence of human expertise and artificial intelligence capabilities presents unprecedented opportunities for language learning pedagogy. This comprehensive review synthesizes current research across multiple domains including second language acquisition theory, educational technology, human-computer interaction, and artificial intelligence to propose a novel framework for classroom design. Through systematic analysis, the research identifies key HMT components that directly impact WTC: adaptive feedback mechanisms, empathetic AI interactions, collaborative task design, and personalized learning environments. The findings indicate that well-designed human-machine partnerships can significantly reduce speaking anxiety, increase learner autonomy, and enhance communicative competence. The review proposes a multi-layered theoretical framework that positions educators as orchestrators of human-AI collaboration rather than sole content deliverers, while AI systems serve as adaptive learning partners providing real-time feedback, conversation practice, and anxiety-reducing interventions. Key recommendations include implementing transparent AI systems that build trust, designing collaborative speaking tasks that leverage both human creativity and AI analytical capabilities, and developing teacher training programs for effective HMT integration. This work contributes to the growing body of knowledge on AI-enhanced language education and provides practical guidelines for educators seeking to modernize speaking instruction through human-machine collaboration.