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- PaperRELC Journal22 Jul 2026
Translanguaging for critical multilingual language awareness: Classroom activities for socially just language education
Jennifer Burton, Shakina Rajendram
Introduces a Translanguaging for Critical Multilingual Language Awareness (TL-for-CMLA) approach, operationalized through two concrete pedagogical activities: multilingual versions of Little Red Riding Hood for metalinguistic awareness and multilingual spoken word poetry for identity exploration. The activities challenge target-language-only assumptions and engage learners critically and affectively, aiming to foreground power, racialization, and linguistic hierarchies in language education.
Original abstract
This article introduces a Translanguaging for Critical Multilingual Language Awareness (TL-for-CMLA) approach and illustrates how it can be operationalized through concrete pedagogical activities in language teacher education and additional language classrooms. The paper argues for an explicitly critical orientation that foregrounds power, racialization, and linguistic hierarchies rather than treating multilingualism as a neutral resource. The purpose of this innovation in practice article is to present two classroom activities that bridge critical language ideologies and everyday teaching practice in English as a Second Language (ESL) and Kindergarten-Grade 12 (K-12) classrooms with multilingual learners. The first activity uses multilingual versions of Little Red Riding Hood to develop metalinguistic awareness and challenge target-language only assumptions. The second activity centers multilingual, identity focused spoken word poetry to engage learners affectively, critically, and multimodally with questions of language, identity, and belonging. Together, these activities present adaptable examples, reflection prompts, and underlying rationales that can be applied across proficiency levels and educational contexts. This paper contributes theoretically by clarifying TL-for-CMLA and pedagogically by offering adaptable activities that support socially just language education.
- PaperOpenAlex — TESOL research22 Jul 2026
Second language embodiment in actor training through mindful practice
Kristýna Zinková
Applied Practice as Research with EAL acting students to explore how a second language can become disembodied and affect performative authenticity. Found that training linguistic awareness through mindful practices like Dialogical Acting enhances second language embodiment. Supports integrating deep linguistic embodiment into multilingual acting curricula.
Original abstract
At the turn of the twenty first century, the Embodied Cognition Theory emerged, positing that human cognition, including language, is inherently embodied. This theory suggests that even imagining movement can activate muscles similarly to actual movement, highlighting the mind and body as an interconnected system. However, it raises a question: are second languages also embodied? While this theory has intrigued performative sciences, more rigorous research is required. To investigate this matter, I applied Practice as Research as part of my Master’s Thesis at the Academy of Performing Arts in Prague. Working with EAL acting students,I explored how, or why, a second language (English) can be “disembodied” and how this affects performative authenticity. My findings revealed that linguistic awareness may be a vital tool for enhancing performance. The research incorporated the Academy's practice Dialogical Acting with The Inner Partner, investigating how well awareness can be trained in order to increase the embodiment of a second language. By fostering awareness in second-language acquisition, including sound and rhythm in life-like situations, performers can deepen their understanding of linguistic systems and enhance their personal linguistic capabilities. This research supports integrating deep linguistic embodiment into multicultural and multilingual acting curricula, offering a pathway to more authentic performances.
- PaperOpenAlex — TESOL research22 Jul 2026
Analysis of challenges and opportunities in english language teaching to improve its methodologies at CEBG Nuevo San José, 2025
Benicio Ramón Chacón Rodríguez
Analyzes challenges and opportunities in English language teaching at CEBG Nuevo San José, a rural multigrade school lacking specialized teachers and resources. Uses interviews, observations, and surveys to understand student attitudes and proposes recommendations for improving language learning in underserved contexts.
Original abstract
La dirección principal de esta investigación es analizar e investigar los desafíos y oportunidades de la enseñanza del inglés que se presentan en el CEBG Nuevo San José, una escuela de entorno rural multigrado, en la actualidad no se cuenta con un docente especializado en la materia. Esta carencia, acompañada a la falta de recursos didácticos, dificulta al docente de grado regular que pueda impartir una enseñanza de calidad a un grupo de alumnos de diferentes niveles en la misma aula. Esto representa un gran obstáculo para que los estudiantes progresen en su aprendizaje y en su desarrollo académico. La adquisición de una segunda lengua es un instrumento esencial para su desarrollo profesional y educativo futuro, pero se ve limitada debido a que no reciben la orientación adecuada. Esta investigación utiliza diferentes instrumentos, como entrevistas, observaciones de profesores y alumnos, y encuestas, para comprender cómo se sienten los alumnos respecto al aprendizaje de un nuevo idioma. También busca explorar las cualidades de los estudiantes y la necesidad de utilizar tecnologías y herramientas reales que ayuden a mejorar sus habilidades de aprendizaje de idiomas de una manera real, sostenible y organizada en entornos rurales multigrado. El objetivo principal de esta investigación es generar recomendaciones claras sobre la importancia del aprendizaje de idiomas en entornos donde hay escasez de profesores especializados y promover políticas educativas más inclusivas.
- PaperOpenAlex — TESOL research22 Jul 2026
Inclusive English Language Teaching: Bibliometric Analysis of Multilingualism and Inclusive Classroom Practices
Cristine Ombao
A bibliometric analysis of 56 articles from Scopus (2017-2025) mapped publication trends, leading contributors, and thematic clusters in multilingualism and inclusive classroom practices in English Language Teaching. The United States and Indonesia led research output, with inclusive education and ELT as dominant theoretical anchors. Underdeveloped areas include decolonization and disability-inclusive pedagogy.
Original abstract
This bibliometric analysis examined published research on multilingualism and inclusive classroom practices in English Language Teaching retrieved from the Scopus database from 2017 to 2025. Guided by three research questions, the study mapped publication trends, leading journals, authors, institutions, and dominant thematic clusters across 56 articles using VOSviewer for keyword co-occurrence visualization. The findings revealed a steady acceleration in publication output over the analyzed window, with inclusive education and English language teaching emerging as the dominant theoretical anchors of the field. The United States and Indonesia led the field in research output, followed by a globally distributed tier including Poland, Iran, Spain, and South Africa. The University of Warsaw (3 publications) and Isfahan University of Technology (2 publications) ranked as the most productive institutions, while Chan and Lo, Lau and Shea, and Nijakowska et al. registered as the most cited authors. The keyword analysis clustered scholarship around inclusive, multilingual, EFL/ESL, and higher education strands, with peripheral domains such as decolonization and disability-inclusive pedagogy remaining underdeveloped. The findings provide a foundation for advancing evidence-based, multilingual, and equitable ELT research through the next decade.
- NewsEdSurge22 Jul 2026
What Does AI Cost When We Skip the Work?
This EdSurge podcast episode discusses the enduring value of a college degree and writing skills in the age of AI, featuring guests who argue that the benefits of these experiences—such as personal growth and deep learning—cannot be replicated by artificial intelligence.
Original abstract
<p>Every few months, another headline declares the college degree dead. <strong>This Week with EdSurge</strong> examines what still holds up when artificial intelligence moves fast, through two guests who are both defending something slow against something fast.</p><h2>A Four Year Degree in the Age of AI</h2><p><a href="https://www.edsurge.com/author/rita-finkel--9b5e61f9-c70d-441e-b13a-0c1a116d3d60"><u>Rita Finkel</u></a>, co-president of the Armory Foundation and director of the Armory College Prep program, argues that a college degree was never just about a technical skill. She says the data tells a different story than the headlines suggest, and that the value of a degree comes from something artificial intelligence cannot replicate.</p><h2>The Fourth Essay</h2><p><a href="https://www.edsurge.com/author/cobretti-williams"><u>Cobretti Williams</u></a> of the <strong>EdSurge</strong> Voices of Change Fellowship makes a similar case for writing. He talks about the beauty in imperfection, and how a fellow's fourth essay reads nothing like the first, growth that only comes from doing the work yourself.</p><p><a href="https://www.edsurge.com/podcasts"><u>Listen to the episode</u></a>.</p><h2>Stories Mentioned in This Episode</h2><p><a href="https://www.edsurge.com/news/2026-05-28-why-college-degrees-matter-in-the-age-of-ai"><u>Why College Degrees Matter in the Age of AI</u></a></p><p>by Rita Finkel</p><p><a href="https://www.edsurge.com/collections/edsurge-voices-of-change-writing-fellowship"><u>EdSurge Voices of Change Writing Fellowship</u></a></p><p>by EdSurge</p><p><strong>This Week with EdSurge</strong> is a weekly podcast from <strong>EdSurge</strong>. Subscribe to the <a href="https://www.edsurge.com/newsletters"><u>EdSurge newsletters</u></a> for more news and analysis on education and technology.</p><p> </p>
- PaperOpenAlex — TESOL research22 Jul 2026
ENHANCING FOREIGN LANGUAGE TEACHING METHODOLOGY THROUGH ARTIFICIAL INTELLIGENCE: A CASE STUDY OF ENGLISH LANGUAGE LEARNING
Farmonova Naimakhon Furkat kizi
AI tools like intelligent tutoring systems and adaptive learning platforms significantly improve vocabulary acquisition, communicative competence, and learner autonomy in English language teaching, though challenges such as teacher readiness and ethical concerns persist.
Original abstract
Artificial Intelligence (AI) is rapidly transforming educational practices, particularly in the field of foreign language teaching. This study explores how AI can enhance English language teaching methodology in higher education. Using a mixed-method research design, the study evaluates the impact of AI-based tools such as intelligent tutoring systems, natural language processing applications, and adaptive learning platforms on students’ language proficiency. The findings reveal that AI significantly improves vocabulary acquisition, communicative competence, and learner autonomy. However, challenges related to teacher readiness, infrastructure, and ethical considerations remain. The study contributes to the development of modern AI-based pedagogical frameworks.
- PaperTESOL Quarterly22 Jul 2026
Pedagogical Translanguaging in Motion: Multimodal Mediation in Preservice Teachers' Storytelling with Young English Learners
Sue Garton, Serdar Tekin
This study investigated how eight preservice English teachers in Turkish primary schools used translanguaging and multimodal strategies during storytelling lessons over eight weeks. Initially, teachers relied on shared linguistic repertoires to manage interaction and scaffold comprehension, but over time they shifted toward increased use of gesture, visuals, and realia while verbal translanguaging became more selective. The findings provide classroom-based evidence of how translanguaging practices evolve and offer implications for multilingual pedagogy and teacher education.
Original abstract
Amid growing interest in multilingual pedagogies, translanguaging has increasingly been positioned as a response to monolingual teaching norms. Yet empirical accounts of what pedagogical translanguaging looks like in everyday classrooms—particularly in teaching English to young learners—remain limited. At the same time, although storytelling occupies a central place in young learner pedagogy, little research has examined how teachers mobilize linguistic and semiotic resources during storytelling lessons. Addressing both gaps, this study draws on the pedagogical translanguaging framework and the Dynamic Model of Multilingualism to investigate the evolving practices of eight preservice English teachers (PSTs) in Turkish state primary schools. The data set comprises 32 video‐recorded storytelling lessons over 8 weeks and follow‐up in‐depth interviews. Findings show that PSTs initially drew on shared linguistic repertoires to manage classroom interaction and scaffold story comprehension. Over time, however, these practices shifted, and translanguaging use decreased as PSTs increasingly employed multimodal strategies, including gesture, visual supports, and realia. Findings suggest how teachers' mediational practices became increasingly adaptive, with verbal translanguaging becoming more selective alongside increased use of multimodal mediation. The study contributes classroom‐based evidence of how translanguaging evolves over time and offers implications for multilingual pedagogy and teacher education in young learner contexts.
- PaperOpenAlex — TESOL research22 Jul 2026
Learners’ perceptions and challenges of microlearning in Indian ESL tertiary education
K. Arunesh Kumar, N. Hema
A quantitative study of 48 Indian ESL undergraduates found positive perceptions of microlearning's flexibility and interactivity, but identified challenges such as poor internet connectivity and content fragmentation. A significant negative correlation between perceptions and challenges indicates that greater obstacles worsen attitudes toward microlearning, highlighting the need for context-sensitive technology integration.
Original abstract
The swift digitalization of higher education has fuelled the curiosity surrounding microlearning as a new form of pedagogy in the field of English Language Teaching (ELT), particularly English as a Second Language (ESL) instruction. Although microlearning is increasingly used globally, little empirical evidence has investigated on how learners perceive microlearning in the context of tertiary level ESL learners in India. This paper explores perceptions of microlearning among ESL learners at the tertiary level, challenges faced by these learners, and the correlation between their perceptions and challenges. Using a quantitative research design, a study involving 48 Indian ESL undergraduate students was conducted, where a structured questionnaire with perception and challenge scales was administered. Data analysis was done using descriptive statistics, reliability analysis, and Pearson correlation. The results indicate that students tend to have positive attitudes towards microlearning, especially its flexibility, interactivity, and vocabulary/grammar acquisition support. Nevertheless, there are still important limitations, including the lack of internet connectivity and issues with content depth and fragmentation. The correlation between the perceptions of learners and the challenges met was statistically significant and negative, denoting that greater impediments have a negative impact on attitudes towards microlearning. The research highlights the significance of technology integration that is learner-focused and context-related and provides pedagogical implications in support of educators, curriculum developers, and policymakers aiming to maximize the use of microlearning in Indian tertiary ESL institutions.
- PaperOpenAlex — TESOL research22 Jul 2026
THE TRANSFORMATIVE ROLE OF ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE TEACHING
Madaminova, Nargizaxon Jahongir qizi,
The integration of artificial intelligence (AI) into English Language Teaching (ELT) is prompting a reevaluation of curriculum development, learner assessment, and teacher responsibilities. A thematic analysis reveals a shift toward personalized learning and data-informed curricula, suggesting AI will redefine teachers' roles and learning objectives rather than replace traditional instruction.
Original abstract
The integration of artificial intelligence (AI) into English Language Teaching (ELT) signifiesa critical evolution in both pedagogical practice and instructional design. As AI technologiesrapidly develop and become widely accessible, educators and researchers are reevaluating thefoundational components of language instruction, including curriculum development, learnerassessment, teacher responsibilities, and communicative goals. This article explores themedium-term implications of AI in ELT, identifying key challenges and opportunities arisingfrom its implementation. A thematic analysis of current discourse in the field reveals a shifttoward personalized learning, data-informed curricula, and the need for new literacies amongboth teachers and learners. The findings suggest that AI will not replace traditional instructionbut rather redefine the teacher's role and reshape learning objectives.
- PaperEdArXiv (OSF Preprints)21 Jul 2026
Changes in Motivational Beliefs and Science Identity During an AI-Assisted Reading of Primary Scientific Literature
Sebastian Alvarado, Bradley Bergey, Leif Philips, Maral Tajerian
Undergraduate biology students using the AI tool Scite to read primary scientific literature showed increases in intrinsic, utility, and attainment values and science identity, alongside an unexpected rise in perceived costs. The study, guided by Expectancy-Value Theory, suggests complex motivational implications of AI-assisted engagement with primary scientific literature.
Original abstract
Reading primary scientific literature is essential yet challenging for undergraduate science students, who often report low confidence and difficulty navigating complex texts. Guided by Expectancy-Value Theory, this mixed-methods study examined changes in students' motivational beliefs across a biology literature review assignment in which students used Scite, an AI-powered citation analysis tool, including science identity; self-efficacy; and intrinsic, utility, and attainment values and perceived costs of reading primary scientific literature. Students enrolled in a 200-level Foundations of Research in Biology course were assigned a structured literature review on pharmacological interventions for a disease of their choice, using Scite.ai to locate, evaluate, and synthesize primary research. A racially diverse sample of 27 undergraduate biology students (48% women, 42% first-generation college students) completed a posttest questionnaire, including a subsample (n = 21) with matched pretest questionnaire responses. Paired-sample t tests revealed statistically significant, medium-sized increases in intrinsic, utility, and attainment values and science identity, alongside an unexpected rise in perceived costs (d = .51-.65); results revealed a small nonsignificant increase in self-efficacy. Students rated Scite as highly useful for identifying, summarizing, and synthesizing research. Thematic analysis of open-ended responses revealed the salience of perceived utility, enjoyment, cognitive support, and credibility, alongside concerns about reliability, ease of use, and occasional identity-related conflicts. Findings suggest that AI-assisted engagement with PSL carries complex motivational implications, warranting controlled investigation.
- PaperEdArXiv (OSF Preprints)21 Jul 2026
Toward Responsible AI Implementation in K–12 Music Education: A Human-Centered Conceptual Framework Informed by Emerging U.S. Educational Priorities
Jose Gregorio Reinoso Yepez
A conceptual framework for responsible AI implementation in K–12 music education is developed, drawing on U.S. educational priorities and international governance. The framework emphasizes human-centered design, pedagogical integrity, teacher agency, AI literacy, and ethical governance. While focused on music, the principles may apply to other K–12 subjects.
Original abstract
Artificial intelligence (AI) is increasingly reshaping K–12 education, influencing curriculum design, instructional practice, and educational governance. Emerging U.S. priorities emphasize not only technological innovation but also responsible implementation, AI literacy, data privacy, and equitable access. These priorities are especially relevant to K–12 music education, where learning depends on cognitive, artistic, emotional, and social dimensions requiring sustained teacher guidance. Although AI-supported tools offer promising applications for adaptive practice, automated feedback, and AI-assisted composition, their value depends on implementation conditions that preserve pedagogical integrity and teacher agency. This conceptual article develops a Human-Centered Conceptual Framework for Responsible AI Implementation in K–12 Music Education, drawing on U.S. priorities, international governance frameworks, and contemporary scholarship. The framework positions AI as a support system within an educational ecosystem shaped by pedagogy, educator leadership, AI literacy, ethical governance, professional capacity building, and continuous improvement, offering a conceptual foundation for future research, policy, and practice in music education and other K–12 settings.
- PaperEdArXiv (OSF Preprints)21 Jul 2026
From Environmental Noise to Pedagogical Signal: Analyzing the Educational Potential of Strategic Cinema in Representing Teachers' Professional Crises (A Case Study of Social Studies Pre-Service Teachers)
Hossein Talebzadeh
A qualitative study evaluated the 'Image Pedagogy' framework using strategic films as pedagogical laboratories for social studies pre-service teachers. Exposure to cinematic narratives improved their ability to differentiate 'environmental noise' from 'pedagogical signals' based on the Signal-to-Noise Ratio model, fostering a cognitive shift from emotional descriptivism to strategic analysis. The approach provided a safe environment for encountering classroom crises and enhanced managerial competencies under uncertainty.
Original abstract
This qualitative study was conducted to evaluate the operational framework of "Image Pedagogy." Utilizing an Observation–Analysis–Synthesis protocol, three strategic films were analyzed as dedicated pedagogical laboratories. The findings indicate that exposure to cinematic narratives significantly improves pre-service teachers' capability to differentiate "environmental noise" from "pedagogical signals" based on the Signal-to-Noise Ratio (SNR) model, inducing a cognitive transformation from "emotional descriptivism" to "strategic analysis." The results demonstrate that this approach, by redefining "professional experiences," provides a safe environment for encountering classroom crises and enhances educators' managerial competencies under conditions of acute uncertainty.
- PaperarXiv — AI in Education (cs.CY)21 Jul 2026
Sequential Learner Modeling Using Multi-Relational Graph Convolutional Networks
Rawaa Alatrash, Mohamed Amine Chatti, Hong Yang, Yumeng Wang
Introduces MR-ConceptGCN, an unsupervised method for sequential learner modeling using multi-relational graph convolutional networks. It combines personal knowledge graphs and sentence embeddings to capture learner interactions and generate sequential models. An online study with 31 users demonstrated improvements in accuracy, usefulness, diversity, and satisfaction for an educational recommender system.
Original abstract
User modeling is a critical task in a variety of personalized systems. Recognizing their effectiveness in learning from graph-structured data, Graph Neural Networks (GNNs), particularly Graph Convolutional Networks (GCNs), are increasingly employed for user modeling. However, existing approaches typically treat different relation types in a graph as homogeneous, limiting their ability to capture richer semantics and construct more informative user models. While multi-relational GNNs (MR-GNNs) have been adopted for representation learning and recommendation, their application for user modeling remains unexplored. Moreover, existing GNN-based user modeling approaches ignore the user interaction sequence. To address these research gaps, in this work we propose MR-ConceptGCN, a novel fully unsupervised approach focused on concept-based sequential learner modeling using multi-relational GCNs (MR-GCNs). MR-ConceptGCN effecively combines Personal Knowledge Graphs (PKGs), MR-GCNs, and the pre-trained language model SBERT to obtain enhanced relation- and semantic-aware representations of the PKG items. The enriched embeddings of the knowledge concepts that a learner did not understand when interacting with learning materials in CourseMapper are then used to construct a sequential learner model that combines long-term and short-term learner interactions. We report the results of an online user study (n = 31), demonstrating the benefits of MR-ConceptGCN in terms of several important user-centric aspects including accuracy, usefulness, diversity, and satisfaction with an educational recommender system.
- PaperarXiv — AI in Education (cs.CY)21 Jul 2026
Assessment in Team Problem-Solving Exercises in Computing Education
Valdemar Švábenský, Jan Vykopal, Sukrit Leelaluk, Pavel Čeleda et al.
Compares clustering and large language models for post-exercise team assessment in tabletop exercises, using data from 81 participants. Clustering proved valid and reliable for grouping teams by task approach, while newer LLMs (GPT-5.2) showed lower error than GPT-4o when scoring communication. Methods are integrated into the open-source INJECT platform to support scalable assessment in computing education.
Original abstract
This full paper in the research-to-practice track presents methods for assessing student teams in tabletop exercises (TTXs). TTXs enable learner teams to prepare for workplace tasks and practice crisis responses, such as resolving cybersecurity incidents. While assessment is essential for determining how well teams achieve learning objectives, the complex, open-ended nature of TTXs often leads to delayed or incomplete feedback. TTX learning platforms can record teams' actions and communication; yet, leveraging these data to assess performance is underexplored. To address this gap, we compared two post-TTX team assessment methods -- clustering and large language models (LLMs) -- using an original dataset from 81 participants across two countries. We evaluated these methods against instructor-assigned scores based on standardized rubrics. Clustering grouped teams that approached TTX tasks similarly, enabling instructors to deliver faster, targeted feedback to teams within a cluster. This method was valid and reliable, with low computational requirements. LLMs used the standardized rubrics to assess teams' communication. While GPT-4o frequently disagreed with instructor scores, GPT-5.2 demonstrated considerably lower error. The researched methods have been integrated into INJECT, an open-source TTX learning platform, to support scalability and teaching practice. To encourage community adoption, we publicly share all datasets, software tools, and a full-fledged TTX scenario.
- PaperRELC Journal21 Jul 2026
Enhancing English Public Speaking Self-Efficacy and Performance Through a CDIO-Based English Course
Yen-Hui Lu
This quasi-experimental study integrated the CDIO framework into English public speaking instruction for EFL university students in Taiwan. The experimental group showed significantly higher self-efficacy and superior performance in content, organization, and delivery compared to traditional training, but no improvement in language accuracy. Pedagogical implications include using authentic project-driven tasks and supplementing with language-focused interventions.
Original abstract
This study investigates the impact of integrating the Conceive–Design–Implement–Operate (CDIO) framework into English public speaking (EPS) instruction for English as a foreign language (EFL) university students in Taiwan. EPS has been widely recognized as a critical competence in academic and professional contexts, yet EFL learners often struggle with anxiety, limited practice opportunities and low self-efficacy. To address these challenges, the study implemented a quasi-experimental design with two Freshman English classes: a control group receiving traditional presentation training; and an experimental group engaged in a CDIO-based presentation training. Over an 18-week semester, students’ self-efficacy was measured using a validated EPS self-efficacy scale, while performance was evaluated with a rubric assessing language use, content, organization and delivery. Pre-test results showed no significant differences between groups, ensuring baseline equivalence. Post-test findings revealed that the experimental group demonstrated significantly higher self-efficacy, as well as superior performance in content development, organizational structure and delivery techniques. However, no significant improvements were found in language accuracy and fluency. These results suggest that CDIO-based instruction enhances students’ confidence and competence in public speaking through authentic, project-driven tasks. The findings yield three key pedagogical implications: (a) integrating authentic, product-based tasks such as sustainable innovation pitches can foster mastery experiences and boost learner motivation and self-efficacy; (b) using CDIO's four-phase structure enables instructors to scaffold content and organizational development through guided brainstorming, outlining and rehearsed delivery; and (c) to address limitations in grammar and vocabulary acquisition, supplementary language-focused interventions such as vocabulary mini-tasks and grammar workshops should be embedded within the CDIO cycle to balance fluency with accuracy. These strategies can optimize the effectiveness of CDIO-based EPS instruction in EFL contexts.
- PaperOpenAlex — TESOL research21 Jul 2026
Methodological guidelines for english language teaching to help parents and educators at CEBG José Marciano Moreno
Manuel Antonio Cárdenas Aguirre, Patrick Alexis Gil Meneses
Designed a participatory English language training program for parents and educators at a multi-grade school in Panama, addressing the lack of specialized teachers and limited parental support. Four interactive sessions covered the importance of English, daily integration strategies, reading techniques, and building a support network. Outcomes included improved teacher methodologies, empowered parents, and a motivational mural symbolizing community unity.
Original abstract
Este proyecto está centrado en el diseño de un programa participativo de formación del idioma inglés, dirigido a padres y educadores del CEBG José Marciano Moreno, en la comunidad de Buen Retiro, Antón, provincia de Coclé. Esta iniciativa surgió ante la problemática de las escuelas multigrado-panameñas, en donde carecen de docentes especializados, y esto le sumamos el limitado apoyo de los padres debido a su desconocimiento del idioma. El objetivo principal es crear una red de apoyo sostenible para mejorar la calidad de la enseñanza, pero sobre todo empoderar a los padres con herramientas prácticas que sirvan como guía en el aprendizaje del idioma inglés. Teniendo como intervención un diagnóstico inicial de necesidades y la implementación de cuatro sesiones de capacitación interactiva. Estas sesiones abordaron temas como la importancia del inglés, estrategias para incorporarlo en la vida diaria, técnicas de lectura y la creación de una red de apoyo. Como resultado, se fortalecieron las habilidades metodológicas de los docentes, se empoderó a los padres con herramientas prácticas y se fomentó la creación de un mural motivacional que simboliza la unión de la comunidad. Este estudio de caso, con enfoque participativo, demuestra que la implicación conjunta de familias y educadores es clave para superar las limitaciones estructurales.
- PaperOpenAlex — TESOL research21 Jul 2026
The Impact of AI Empowerment on the Development of College Students' English Speaking Skills: A Mixed-Methods Analysis Based on Speech Competence Assessment and Self-Directed Learning Efficiency
Jian Li, Luo ZhiYao
A mixed-methods study with 20 Chinese college students found that using the Doubao AI platform for autonomous speaking practice significantly improved fluency, pronunciation, and lexical resources. AI empowerment enhanced self-directed learning efficiency through synergy between self-determination theory and self-regulated learning, though a 'situational gap' between virtual practice and real interaction persisted.
Original abstract
In the context of the digital transformation of global education, artificial intelligence (AI) has become a transformative force in the field of second language acquisition. This study explores the impact of AI empowerment on the development of Chinese college students’ oral English competence and the efficiency of self-directed learning (SDL). The core of the research is to explore the synergy between the self-determination theory (SDT) and the self-regulated learning (SRL) model to clarify the interaction between technology empowerment and psychological mechanisms. Under this framework, SDL is the main learning mode, while SDT provides motivational basis (answering students “why” initiates SDL), and SRL provides strategic guarantee (answering students “how” manages learning process). This study adopts a mixed research method and conducts a six-week quasi-experiment with 20 International Business English majors students from Guangdong University of Foreign Studies. During the winter vacation, participants used the Doubao AI platform for autonomous speaking practice and received instant, data-driven feedback. The data were comprehensively analyzed through pre-test and post-test (measuring fluency, lexical resources, accuracy and pronunciation), validated questionnaires and qualitative interviews. The results show that AI empowerment significantly improves objective speaking ability, especially in terms of fluency, pronunciation and lexical resource. More importantly, the study found that there is a deep synergistic effect between the learner’s motivation process and the strategy process: the satisfaction of the two basic psychological needs of autonomy and ability (SDT) provides the internal motivation for students to enter the three cycle stages of SRL; the effective strategy execution guided by the role of AI “virtual supervisor” further strengthens the learners’ sense of achievement, thus jointly improving the overall SDL efficiency. Despite these advances, the study also found a “situational gap” between virtual practice and real social interaction. This study highlights the importance of an AI-supported teaching model that combines technical efficiency with human-led strategic guidance to optimize the self-directed development of oral English in the digital age.
- NewsEdSurge21 Jul 2026
The Language Barrier Is the Real Barrier in Edtech
This article argues that most educational technology platforms are built in English first, creating an invisible barrier for non-English-speaking families who cannot help their children with schoolwork. It highlights how this language gap widens opportunity disparities, particularly as states like California mandate personal finance courses, and calls for bilingual solutions to ensure equitable access.
Original abstract
<p>When I started looking closely at the learning platforms schools ask families to use, I noticed something easy to miss if it doesn’t affect you: almost all of them are built in English first.</p><p>For families who speak Spanish at home, that one fact quietly changes everything. A child might be able to follow along in class, but the parent often can’t — and a parent who can’t understand the material can’t sit beside their kid and help them with it. The language barrier becomes an opportunity barrier. And it’s invisible to the people who never have to think about it.</p><p>For me, the English-first technology trend was never abstract. My own children use the technology I’ve built, and I built it for families like the ones all around me — so that the opportunity to understand money, technology, and how to build something of your own doesn’t depend on which language gets spoken at the dinner table. I’m tired of watching the same families get left a step behind — not because their kids are any less capable but because no one built the on-ramp in a language they could use.</p><p>That language gap is what I set out to close.</p><p>It matters now more than ever because a growing number of states are starting to require students to take a personal finance course to graduate. For example,<a href="https://www.cde.ca.gov/ci/cr/cf/personalfinance.asp"> <u>California’s Assembly Bill 2927</u></a> requires students to complete a stand-alone personal finance course to graduate high school starting with the class of 2030-31, with schools required to offer it by 2027-28. But if the lessons exist only in English, many households that need that knowledge are also the ones least able to access and reinforce it at home. A mandate built that way doesn’t close the gap. It can widen it.</p><p>I’ve spent the past three years building a bilingual K-12 learning platform, and the single most important thing I’ve learned is this: there is a world of difference between a product that has been
- PaperOpenAlex — TESOL research21 Jul 2026
The Role of Artificial Intelligence in Lesson Planning and the Development of English Teaching Methods: Teachers’ Perspectives
Azza Elmadani, Shiraz Al-Ali, Salma Mohammed Osman Elias, Mudathir Yousif Mohamed Ahmed et al.
Artificial Intelligence (AI) is transforming English Language Teaching by aiding lesson planning, instructional design, material development, personalized instruction, assessment, and classroom interaction. Teachers report that AI saves time, offers differentiated instruction options, and provides adaptive materials, while ethical concerns include overdependence, plagiarism, privacy, and teacher qualifications. AI is seen as supplementary rather than a replacement for human educators.
Original abstract
In today's world, Artificial Intelligence (AI) represents an innovative factor in education, especially in English Language Teaching (ELT). The purpose of this research paper is to explore the influence of AI on lesson planning and English teaching methodologies based on teachers' insights. Specifically, it will be considered the impact of AI on instructional design, material development, personalized instruction, assessment, and classroom interaction in the context of English language teaching. For analysis, a qualitative-descriptive and analytical approach will be applied using a review of empirical findings, scientific literature, and personal experience related to integrating AI in ELT. According to results, artificial intelligence contributes to teachers' performance by saving their time, offering options for differentiated instruction, providing adaptive instructional materials, and enabling innovation in the pedagogy field. At the same time, the use of technology is viewed as supplementary to traditional educational activities rather than replacement to human educators. Ethical aspects associated with the integration of AI in the process of education, overdependence on AI-based resources, plagiarism and academic integrity, privacy protection issues, and teacher qualifications should be considered in the case of English teaching.
- PaperOpenAlex — TESOL research21 Jul 2026
An Exploratory Investigation of ELT Instructors’ Attitudes Toward Bilingual Medium of Instruction (BMI) and the Role of Technology in Bangladeshi Classrooms
Bushra Jesmin Trisha, Swaha Das, Ritu Ghosh
A survey of 18 ELT instructors at a Bangladeshi university found 88.9% support for bilingual medium of instruction (BMI), citing improved comprehension and learner confidence. However, 66.7% worried about reduced English exposure, and most reported barriers such as inadequate training, restrictive policies, and limited resources. Instructors held positive attitudes toward AI tools and gamification, though implementation varied with available resources.
Original abstract
This study investigates the outlooks, reported practices, and perceived constraints of English Language Teaching (ELT) instructors concerning Bilingual Medium of Instruction (BMI) in Bangladeshi university classrooms. Eighteen instructors from Feni University participated in a structured survey. The research is organized around three objectives: (a) examining instructors’ perceptions of translanguaging practices, (b) investigating the obstacles they report when implementing bilingual instruction, and (c) exploring how technological integration may facilitate translanguaging pedagogy. Within this sample, 88.9% of respondents indicated support for bilingual instruction, citing enhanced comprehension, increased learner confidence, and faster learning as the most frequently reported benefits. Approximately 66.7% of participants expressed concern about reduced English exposure, and a majority reported inadequate training, restrictive institutional policies, and limited bilingual resources as recurring barriers. Respondents held positive attitudes toward AI-driven tools and gamification, although the extent of implementation appeared to vary with available resources. The study discusses these findings in relation to each research objective, situating the sample-level results within the broader literature on translanguaging, language policy, and educational technology. The discussion concludes with practical implications for teacher education, institutional policy, and bilingual resource development, and acknowledges the limitations of the current study alongside directions for future inquiry.
- PaperJournal of Second Language Writing21 Jul 2026
Writing the local: How place-based writing mediates learners’ perceived authenticity in L2 writing
Delin Kong
Examines how place-based writing tasks influence learners' perceptions of authenticity in second language writing contexts.
- PaperOpenAlex — TESOL research21 Jul 2026
Teachers’ Perceptions Towards Learner-Centered Techniques: A Gateway to Educational Enrichment
Manda Paudel, Shiv Ram Pandey, V. Girija, Sameer Madasseri
Secondary-level English teachers in Kathmandu value learner-centered techniques such as group work, problem-based learning, and project-based learning for effective teaching, but face challenges including time constraints, large class sizes, and inadequate resources.
Original abstract
This research article entitled ‘Teachers’ Perceptions Towards Learner-Centered Techniques in English Language Teaching Classroom’ aims to explore secondary-level English teachers’ perceptions towards learner-centered techniques in English language teaching classrooms in terms of group work, problem-based learning, and project- based learning. To meet the objectives of this study, ten English language teachers of secondary level from five institutional and five community schools located in Kathmandu district were selected as participants. The participants were selected using a purposive sampling strategy. The researcher collected data by using semi-structured interviews. The collected data were first transcribed and then analyzed thematically. After analysis and interpretation of the data, it was found that the majority of the teachers understand the value of learner-centered techniques for effective teaching in ELT classrooms. This study found that teachers faced challenges while implementing learner-centered techniques in their classrooms, for example, limitation of time, a large number of students, and inadequate resource materials.
- PaperOpenAlex — TESOL research21 Jul 2026
English Language Teaching and Learning Program (DOS)
A program is described for English language teaching and learning, possibly under the Department of State.
- PaperOpenAlex — TESOL research21 Jul 2026
Language Development of International Adoptees
Elena L. Grigorenko
This chapter reviews the scarce research on language development in internationally adopted children, focusing on the role of age at adoption in second language acquisition, maintenance of the birth language, overall language outcomes, and the predictive value of language skills for broader development.
Original abstract
This chapter reviews research on language development in IA children. Compared to the extensive literature on attachment and mental health, as well as the substantial bodies of research on cognitive development and educational achievement, studies focusing on language development in this subpopulation of children remain relatively scarce. Nevertheless, the unique combination of factors shaping IA children’s developmental trajectories makes their language acquisition an important area of inquiry. In this chapter, I examine the existing literature with particular attention to: (a) the age at adoption and its role in second language acquisition and related critical periods; (b) the maintenance of the birth language alongside learning new languages; (c) overall language functioning outcomes; and (d) the predictive value of second language acquisition for broader developmental domains such as cognition and communication.
- PaperTESOL Quarterly21 Jul 2026
Receptive Meaning‐Recall Knowledge of Derivational Morphology Among EFL Learners: A Case for L1 ‐Population‐Specific Assessment
Mastoor Al‐Kaboody, Geoffrey G. Pinchbeck, Joseph P. Vitta, Christopher Nicklin et al.
Arabic-speaking EFL learners consistently perform better on base word meaning-recall than on derived forms, with proficiency level moderating this gap but not eliminating substantial knowledge deficits. These findings support a (f)lemma-based approach to vocabulary assessment and instruction for low-to-intermediate proficiency Arabic-speaking learners, highlighting the need for explicit teaching of derivational morphology.
Original abstract
Vocabulary knowledge plays a crucial role in L2 proficiency, significantly impacting learners' reading comprehension. Although extensive research has explored whether knowledge of base words extends to recognition of derivational forms, results are inconsistent, especially among learners from non‐Indo‐European linguistic backgrounds. This study investigates the relationship between base word knowledge and comprehension of derivational forms among Arabic‐speaking EFL learners, examining how this relationship varies with proficiency. Using a meaning‐recall vocabulary test consisting of 30 base words and 46 derivational forms, data from 108 learners across four Common European Framework of Reference (CEFR) levels (Below A1 to B1+) were analyzed through logistic mixed effects modeling. Results indicated that learners consistently performed better with base forms than derivations, with proficiency significantly moderating this relationship. Higher proficiency learners showed increased accuracy, but substantial knowledge gaps persisted across all proficiency levels, highlighting the complexity of derivational morphology for Arabic‐speaking learners. These findings support a (f)lemma‐based approach in vocabulary assessment and instruction for low‐ to intermediate‐proficiency Arabic‐speaking learners, emphasizing the need for explicit attention to derivational morphology in curriculum design and instructional practices.
- PaperAssessing Writing21 Jul 2026
Student-AI collaboration in peer feedback: Effects on perceived feedback quality, emotional responses, and feedback literacy development
Hua Wang, Kai Guo
A quasi-experimental study with 60 Chinese EFL undergraduates found that student reviewers using generative AI (Doubao) for feedback generation in peer assessment produced progressively higher-quality feedback (in affect, description, justification, constructiveness) and reported greater task enjoyment and lower anxiety than a control group. The intervention also enhanced all dimensions of feedback literacy, including knowledge, willingness, cooperative learning, and appreciation of peer feedback.
Original abstract
This study investigates how English as a foreign language (EFL) student reviewers engage in open-ended, dialogic interactions with generative artificial intelligence (AI) during the feedback generation process in peer assessment within EFL writing classrooms. It examines the impact of these interactions on feedback quality perceived by recipients, emotional responses (task enjoyment and anxiety), and feedback literacy. A quasi-experimental design was employed with 60 Chinese undergraduate students, divided into an experimental group (EG) that used generative AI (Doubao) for support and a control group (CG) that did not. Over three intervention cycles, data from chat histories, feedback quality ratings by recipients, and pre/post questionnaires on emotions and feedback literacy were analyzed. The results indicated that EG students primarily employed AI for linguistic refinement of their comments, with limited use for enhancing the content or structure. Nevertheless, AI support led to significant, progressive improvements in the perceived quality of feedback, particularly in affect, description, justification, and constructiveness. Furthermore, EG students reported significantly higher task enjoyment and lower anxiety compared to the CG. The intervention also positively enhanced all dimensions of feedback literacy: knowledge and abilities, willingness to participate, cooperative learning, and appreciation of peer feedback. The findings suggest that generative AI can serve as a powerful scaffold, reducing the emotional and cognitive burdens of peer assessment while fostering a more supportive and effective feedback environment. This study underscores the value of integrating AI into peer feedback practices to develop students’ feedback literacy and improve the overall quality of peer learning experiences.
- PaperTESOL Journal21 Jul 2026
Purpose, Audience, Context, and Culture: A Framework for AI ‐Assisted Writing in ELT Classrooms
Flora D. Floris, Willy A. Renandya
The PACC framework (Purpose, Audience, Context, Culture) is proposed for AI-assisted writing in ELT classrooms, drawing on Systemic Functional Linguistics and Genre Theory. Students use these four elements to design AI prompts and to evaluate and revise AI-generated texts, ensuring they meet reader needs. The article explains the theoretical basis, provides classroom examples, and discusses implementation challenges.
Original abstract
Artificial intelligence (AI) tools can help students draft and revise texts more efficiently. However, AI‐generated texts may sound fluent but still fail to meet the needs of readers. This article proposes the PACC framework as a conceptual model for AI‐assisted writing in ELT. Informed by Systemic Functional Linguistics and Genre Theory, PACC focuses on four elements: purpose, audience, context, and culture. Students use these elements to design AI prompts and to evaluate and revise the AI‐generated text. This article explains the theoretical basis of the framework, shows how it can be applied in writing lessons, presents an integrated classroom example, and discusses possible implementation challenges. The PACC framework contributes to ELT writing instruction by giving teachers and students a practical and meaningful way when preparing AI prompts and when reviewing AI‐generated texts.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
The Verification Paradox
Greg O'Keefe
The paper identifies a second verification failure in AI-generated academic work: students cannot determine if the material is correct, deep, or safe. It argues that AI-sourced claims lack an accountable party, structurally different from textbook claims, making novice learning problematic. It concludes that oral defense cannot resolve the gap because ownership and validity are independent.
Original abstract
When a student uses generative AI to produce academic work, the capacity to verify that work fails for two parties, for two reasons, at two moments. The teacher, examining the finished artifact, cannot determine who performed the thinking. The student, situated inside the process of production, cannot determine whether the material the system has supplied is correct, deep, or safe to build upon. This paper concerns the second failure. It argues that a student operating outside their own domain of competence faces three distinct verification problems — correctness, depth, and calibration — and that the third is the most consequential, because it is not a failure to check but a failure to recognize that anything requires checking. The paper then argues that this predicament is not reducible to the familiar condition of novice ignorance. AI-sourced claims differ structurally from textbook-sourced claims in a way that is independent of quality: no accountable party stands behind any particular sentence, which removes the external correction mechanism that has historically made novice learning survivable. Following recent work on the testimony gap, the paper shows this difference to be structural rather than incidental, and therefore permanent: it does not resolve as the underlying systems improve. Finally, the paper argues that the most natural institutional response — verifying student understanding through oral defense — cannot close the gap, because ownership and validity are independent variables. A student can genuinely own a false claim. Any instrument that certifies ownership while remaining blind to validity does not merely fail to detect the problem; it launders it, converting an unverified claim into credentialed knowledge.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Beyond the Average: Analyzing Heterogeneity and Latent Profiles of Cognitive Involvement in Iranian Senior High School Sociology Textbooks
Hossein Talebzadeh
Analyzed cognitive involvement profiles in Iranian high school sociology textbooks using secondary data from the Comparative Adjudication Protocol, revealing that Sociology 2 had the highest textual irregularity while Civic Identity was most uniform. Cluster analysis identified three structural profiles: 'fully passive', 'hyper-active', and others, with a persistent mismatch between passive text content and high-demand end-of-chapter tasks. The study advocates for better structural alignment between narrative content and assessment tasks in textbook design.
Original abstract
Previous evaluations of school textbooks have predominantly focused on aggregate overall averages, thereby overlooking critical intra-textbook heterogeneity. This study aimed to identify latent profiles of cognitive involvement and assess the instability of instructional design within Iranian senior high school sociology textbooks. Utilizing a secondary data analysis of datasets derived from the Comparative Adjudication Protocol (CAP)—encompassing 51 lessons across 4 core textbooks (Sociology 1, Sociology 2, Sociology 3, and Civic Identity)—cognitive involvement indices for text, images, and questions were calculated using the William Romey (1968) method. To quantify internal heterogeneity, the Coefficient of Variation (CV) and Levene's test were utilized, while K-means clustering with Euclidean distance (Hair et al., 2010) was employed to uncover latent profiles. The findings revealed that the Sociology 2 textbook exhibited the highest textual irregularity (CV = 122.45%), whereas the Civic Identity textbook possessed the most uniform text structure (CV = 36.52%). Levene's test confirmed no statistically significant difference in variances across the textbooks for any component (p > 0.05), indicating a more structurally homogeneous design across sociology textbooks compared to history textbooks. However, cluster analysis uncovered three distinct structural profiles, revealing that 35.3% of the analyzed lessons fell into a "fully passive" cluster, while 21.6% were classified as "hyper-active." These findings demonstrate that while sociology textbooks exhibit lower overall heterogeneity than history textbooks, a persistent question-text disjuncture remains—where end-of-chapter tasks demand high analytical engagement while the textual content remains predominantly passive. Consequently, future curricular interventions must prioritize structural alignment between narrative content and assessment tasks, alongside variance reduction across grade levels.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Sustainable Governance in Iran's Higher Education System under Geopolitical Crisis: A Study on the Resilience of Teacher Practicum during Internet Shutdowns
Hossein Talebzadeh
This study examined governance gaps in Iran's teacher practicum system during internet shutdowns caused by geopolitical crisis. Quantitative results showed improved micro-observation skills but a shift from overconfidence to realism in crisis management. Qualitative analysis identified growth patterns despite infrastructural collapse, highlighting the need for institutional resilience.
Original abstract
Over the past two decades, educational systems—particularly in countries embroiled in geopolitical crises—have encountered unprecedented challenges that fundamentally disrupt their core functions. Among the most critical of these challenges is the widespread and recurrent internet shutdown, which renders both in-person instruction and virtual platforms inoperative. The present study aims to identify governance gaps within Iran's teacher practicum system under geopolitical crisis and internet disruption, and to propose a sustainable governance model for its stabilization. Employing a qualitative approach and secondary data analysis, the study re-examined data from 12 student-teachers collected under actual crisis conditions through the lens of sustainable governance. Quantitative findings indicated a significant positive effect of the instructional intervention on students' micro-observation skills (p = .021); however, the non-significant improvement in crisis management style identification (p = .413) reflects not a failure of the intervention, but rather a transition from overconfidence to professional realism. Qualitative analysis further revealed three growth patterns: development of micro-observation despite infrastructural collapse; growth in self-awareness in the absence of institutional support; and the design of alternative strategies to compensate for institutional voids. The findings underscore that despite students' high individual resilience capacity, the educational system lacks any "alternative protocol" or "backup plan" for crisis conditions, severely constraining the effectiveness of any pedagogical intervention. By introducing the concept of "governance gaps" and proposing a 5-step model for stabilizing teacher practicum, this study illuminates the imperative of transitioning from individual resilience to institutional resilience.