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- PaperOpenAlex — TESOL research21 Jul 2026
Language Development of International Adoptees
Elena L. Grigorenko
This chapter reviews research on language development in internationally adopted children, focusing on the role of age at adoption and critical periods, birth language maintenance, overall language outcomes, and the predictive value of second language acquisition for cognition and communication. The review finds that studies on language in this population are scarce compared to other developmental areas, yet the unique factors make it an important area for inquiry.
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 were tested on base words and derivational forms, consistently performing better on base words across proficiency levels. Higher proficiency improved accuracy but substantial knowledge gaps persisted. The findings advocate for explicit instruction in derivational morphology and a (f)lemma-based approach for this population.
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 using generative AI (Doubao) for peer feedback support led to significant improvements in perceived feedback quality, higher task enjoyment, lower anxiety, and enhanced feedback literacy across all dimensions. However, students primarily used AI for linguistic refinement rather than content or structure enhancement.
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 as a conceptual model for AI-assisted writing in ELT. Grounded in Systemic Functional Linguistics and Genre Theory, it guides students in designing AI prompts and evaluating AI-generated texts. The framework offers a practical approach for teachers to integrate AI tools into writing instruction while maintaining focus on communicative goals.
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
This paper identifies three distinct verification problems students face when using generative AI outside their domain of competence: correctness, depth, and calibration, with calibration being the most critical as it involves a failure to recognize the need for verification. It argues that AI-sourced claims differ structurally from textbook-sourced claims because no accountable party stands behind them, removing the external correction mechanism that novice learning relies on. The paper further contends that oral defenses cannot close this gap, as they certify ownership but not validity, potentially laundering unverified claims into credentialed knowledge.
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
This study examines latent profiles of cognitive involvement in Iranian high school sociology textbooks using secondary data from the Comparative Adjudication Protocol. Applying William Romey's method and cluster analysis, it finds three distinct structural profiles: fully passive, hyper-active, and others, with a persistent disjuncture between passive text and high-demand questions. The results highlight the need for better 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 identifies governance gaps in Iran's teacher practicum system during internet shutdowns and proposes a sustainable governance model. Data from 12 student-teachers showed improved micro-observation skills but highlighted the absence of institutional backup plans, emphasizing a need to shift from individual to 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.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Learning Orchestration: What Can Count as Learning in AI-Mediated Assessment?
James Wood
Proposes Learning Orchestration as a framework for credible AI-mediated assessment, arguing that evidence of learning must consider how learners coordinate cognitive, social, and technological resources, not just final artifacts. Distinguishes independent capability, AI-supported orchestration, and accountable verification as distinct claims requiring different evidence.
Original abstract
Responses to generative AI in higher education assessment have focused on the architecture of AI use: secured and open task designs, permission scales, declarations and process evidence. These approaches specify where and how AI may be used, but leave two harder questions unresolved: what capability an assessment claims the learner has, and what evidence could warrant that claim. This article argues that credible evidence of learning in AI-mediated assessment cannot be inferred from the artefact alone, but depends partly on the quality of the learner’s orchestration of the resources that shape it. Learning Orchestration is defined as the purposeful and accountable coordination of distributed cognitive, social, informational and technological resources, through cognitive-metacognitive, epistemic and ethical judgement, to advance learning, develop disciplinary judgement and produce work, decisions or claims that the learner can explain, justify and defend. The article distinguishes Learning Orchestration from self-regulated learning, evaluative judgement, AI literacy, epistemic agency, academic integrity and assessment validity. It contributes a learner-side account linking the quality of resource coordination to the claims about learning that assessment evidence can warrant. The resulting Assessment Claims Framework distinguishes independent capability, AI-supported orchestration and accountable verification of AI-shaped work as claims requiring different forms of evidence. Without these distinctions, universities risk certifying fluent AI-shaped performance while overstating what learners understand, can do independently or can responsibly verify and defend. Credible AI-mediated assessment therefore depends not only on regulating AI use, but on teaching, eliciting and judging the quality of learners’ orchestration.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Knowing Better, Staying Put: Bilateral Evidence of Status Quo Bias as the Primary Barrier to Educational Transformation
MAYYADAH MUHYE ALDEEN SAYYED ABUELOLA
A mixed-methods study (N=200) found that both students and teachers acknowledge their educational system is failing but remain due to status quo bias and loss aversion, not ideological support. The majority expressed ambivalence rather than resistance, suggesting change efforts should focus on making transitions safe and visible rather than arguing for change.
Original abstract
This paper reports a mixed-methods study (N = 200; 100 secondary students, 100 teachers; 80 qualitative interviews) examining why both students and teachers remain in educational systems they independently acknowledge are failing them — a pattern consistent with status quo bias and loss aversion operating at the institutional level. One-sample tests against the scale midpoint confirm that both populations score significantly below the neutral point on engagement, creativity, and autonomy (all p < .001), while both project significantly above-midpoint effectiveness under redesigned conditions — producing a statistically significant projected capacity gap (students: t(99) = 4.72, p < .001; teachers: t(99) = 7.91, p < .001). Qualitative coding achieved good inter-rater reliability (κ = .74) and found zero defenders of the traditional system across 80 interviews. The qualitative data suggest that fear rather than conviction sustains institutional inertia — 46% of students and 33% of teachers expressed ambivalence rather than outright resistance, a finding with direct implications for implementation strategy: if the dominant orientation is ambivalence rather than resistance, change agents should invest in making transition visible and safe rather than constructing arguments for why change is necessary. These findings reframe the educational change problem: the barrier to transformation is not ideological conviction in favour of the traditional system but a well-documented psychological preference for the known over the unknown, with direct implications for how educational change theory should approach implementation.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Beyond the Average: Analyzing Heterogeneity and Latent Profiles of Cognitive Involvement in Iranian Senior High School History Textbooks
Hossein Talebzadeh
This study analyzed cognitive involvement in Iranian high school history textbooks, finding that internal heterogeneity in cognitive demands, especially in higher grade levels, is a more serious pedagogical issue than low average involvement. Four distinct structural profiles were identified, with only 11.5% of lessons being balanced.
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 history textbooks. Utilizing a secondary data analysis of datasets derived from the Comparative Adjudication Protocol (CAP)—encompassing 61 lessons across 4 core textbooks—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 History 3 textbook exhibited the highest instructional irregularity ("CV"=144.50% in the question component), whereas the Contemporary History of Iran textbook possessed the most uniform structure ("CV"=81.58%). Levene’s test confirmed a statistically significant difference in variances across the textbooks specifically within the question component (p<0.01). Furthermore, cluster analysis uncovered four distinct structural profiles, revealing that a meager 11.5% of the analyzed lessons fell into a structurally "balanced" cluster. These findings demonstrate that internal content dispersion, particularly in higher grade levels, poses a more severe pedagogical challenge than low average involvement. Consequently, future curricular interventions must prioritize variance reduction over a simple inflation of baseline averages.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Beyond the Average: Analyzing Heterogeneity and Latent Profiles of Cognitive Involvement in Iranian Junior High School Social Studies
Hossein Talebzadeh
Analyzes intra-textbook heterogeneity in Iranian junior high school social studies textbooks using cognitive involvement indices. Reveals extreme textual irregularity in Grade 7 and three distinct profiles (Active-Question Dominant, Fully Passive, Hyper-Active), highlighting a disjuncture between passive content and demanding questions. Calls for structural alignment between narrative and assessment tasks.
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 junior high school social studies textbooks. Utilizing a secondary data analysis of datasets derived from the Comparative Adjudication Protocol (CAP)—encompassing 44 lessons across 2 core textbooks (Social Studies Grade 7 and Social Studies Grade 8)—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 Social Studies Grade 7 textbook exhibited the highest textual irregularity (CV = 186.84%), whereas the Social Studies Grade 8 textbook demonstrated more moderate text heterogeneity (CV = 134.78%). Levene's test confirmed a statistically significant difference in text variances across the two textbooks (p = 0.028), indicating that Grade 7 social studies is structurally more fragmented than Grade 8. However, cluster analysis uncovered three distinct structural profiles, revealing that 50.0% of the analyzed lessons fell into an "Active-Question Dominant" cluster, while 31.8% were classified as "Fully Passive" and 18.2% as "Hyper-Active." These findings demonstrate that middle school social studies textbooks—particularly at Grade 7—exhibit extreme textual heterogeneity and a persistent question-text disjuncture, 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 systematic reduction of textual variance across grade levels.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
The Forcing Function: Ownership, Provenance, and Oral Defense in AI-Assisted Student Work
Greg O'Keefe
This paper presents an assessment redesign using oral defense to ensure student ownership in AI-assisted work. The framework assigns AI a narrow role (locating material) while requiring students to verify sources and construct an independent position, tested via a two-probe oral defense. The approach is designed for secondary classrooms with small class sizes and instructor familiarity.
Original abstract
Institutional responses to generative AI have largely relied on detection. Detection has failed, and Papers One and Two of this series argue that the failure is structural rather than technical: a finished piece of writing does not carry reliable evidence of the process that produced it, and no improvement in detection tools alters this. This paper proposes a different response. Rather than attempting to establish after the fact whether a student used AI, it redesigns the assessment so that success depends on a capacity AI cannot supply on the student's behalf. The instrument is oral defense, though not as a means of detecting deception. Oral defense is analyzed here as a forcing function: it alters what a student must do in advance in order to succeed, and therefore shapes behaviour before the assessment rather than adjudicating it afterward. The paper develops three connected components. The first is a research protocol that assigns AI a narrow role, the location of material, and reserves for the student the two operations that constitute ownership: verifying what each source argues, and constructing a position from the verified set. The second is a rule of exclusion: a claim whose primary source the student cannot obtain and read may not function as a premise in the argument, even in hedged form. The third is a two-probe defense that tests these two operations separately, incorporating a live friction point that cannot be anticipated and scripted. Ownership, on this account, is not authorship of the prose. It is verified provenance together with demonstrated independent synthesis. A student who used AI extensively and satisfies both conditions passes; a student who used no AI and satisfies neither fails. This is not a loophole in the framework but its central commitment. The paper is addressed to the secondary classroom rather than the university lecture hall, and the scope is integral to the argument rather than incidental. The mechanism developed here depends on an instructor who knows their students across a term, on class sections of roughly twenty to thirty, and on a developmental stage at which the knowledge being assessed is still forming rather than already established and merely being applied. Existing AI-resilient assessment frameworks, examined in Section 5, are designed for university cohorts in the hundreds, where that knowledge is assumed largely in place. The two scopes are not competing solutions to a single problem; they are solutions to different problems, and this paper claims only its own.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Beyond Paper Mills and Product Doctorates: Regulated Doctoral Economies, Knowledge Continuity and Higher Education Policy Across Geopolitical Fragile Frontiers: A Comparative Policy Analysis of China, India and Europe
Savio Vogt
Doctoral education is increasingly shaped by a false binary between publication-driven academic productivity and innovation-oriented industrial relevance. This paper introduces the concept of Regulated Doctoral Economies to propose a balanced framework that preserves knowledge continuity, methodological integrity, and institutional resilience across geopolitical frontiers. A comparative policy analysis of China, India, and Europe (2024–2026) illustrates how resilient doctoral systems emerge from institutional constraint rather than maximized outputs.
Original abstract
The global doctoral economy is undergoing profound structural transformation driven by geopolitical competition, technological change, artificial intelligence, industrial policy and strategic innovation (OECD, 2025; UNESCO, 2021). Doctoral education increasingly functions at the intersection of national innovation, scientific capability, technological sovereignty and economic resilience rather than solely as a mechanism of academic credential formation. Contemporary reforms consequently oscillate between two competing institutional logics: publication-driven academic productivity and innovation-oriented industrial relevance. Whilst both respond to legitimate policy pressures, neither adequately addresses the long-term problem of preserving knowledge continuity, methodological integrity and institutional resilience under conditions of geopolitical uncertainty. This paper argues that doctoral policy has become constrained by a false binary between publication accumulation and innovation acceleration. Rather than interpreting doctoral education as either a publication economy or an innovation economy, it introduces the concept of Regulated Doctoral Economies, developed within the broader Regulated Accumulation Policy (RAP) framework. Doctoral systems are conceptualised as dynamic knowledge ecosystems whose resilience depends upon regulating expansion through institutional constraint rather than publication metrics or commercial outputs alone. Drawing upon comparative policy developments across China, India and Europe (2024–2026), the study integrates higher education governance, innovation systems, research integrity, comparative policy analysis, Fisherian variance and volatility assessment to examine the institutional conditions under which doctoral systems preserve equilibrium whilst avoiding both publication inflation and innovation concentration. The analysis further explores the risks of policy imitation across South Asia, arguing that resilient doctoral systems emerge not through maximising publications or products independently, but through maintaining a dynamic balance between scholarly originality, supervisory capacity, methodological rigour, industrial relevance and long-term knowledge continuity. The paper concludes by proposing the Regulated Doctoral Framework as a comparative policy architecture for strengthening doctoral resilience across increasingly geopolitically fragile frontiers, positioning doctoral education as a critical component of scientific sovereignty, institutional stability and long-term civilisational knowledge continuity.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
A Dimensional Analysis Of Self-Regulated Learning Among Arabic Language Education Students
Muhammad Azhar
A study of 177 Arabic language education students found overall moderate-to-high self-regulated learning (SRL), with final-semester students showing the highest levels. Weakest dimensions were learning planning and language learning strategies; no gender differences were found. The findings suggest a need to strengthen planning and cognitive-linguistic strategies for more balanced SRL development.
Original abstract
Self-Regulated Learning (SRL) is a critical factor in successful foreign language learning, particularly in Arabic, which is characterized by high linguistic complexity and limited exposure outside the classroom. This study aims to comprehensively examine the level and characteristics of self-regulated learning among students enrolled in an Arabic Language Education program within the context of higher education. A quantitative approach with a descriptive–explanatory design was employed. Data were collected using a five-point Likert-scale SRL questionnaire encompassing eight dimensions: learning planning, language learning strategies, self-monitoring, regulation of motivation and perseverance, time management and learning environment, utilization of learning resources, help-seeking and feedback, and self-reflection and evaluation. The participants consisted of 177 active students from the Arabic Language Education program. Data analysis was conducted using descriptive statistics and the Kruskal–Wallis test. The findings indicate that students’ overall SRL levels range from moderately high to high; however, considerable variation exists across dimensions and academic semesters. The highest levels of SRL were observed among students in the final semesters, whereas students in the early and middle semesters demonstrated relatively lower levels. No statistically significant gender differences in SRL were identified. The most dominant dimension was the utilization of learning resources, followed by self-monitoring and motivational regulation, while learning planning and Arabic language learning strategies emerged as comparatively weaker dimensions. These findings highlight the need to strengthen operational planning skills and cognitive-linguistic strategies to promote a more balanced and sustainable development of SRL among Arabic Language Education students.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Student Learning Rates When Practicing with an Intelligent Tutoring System Versus On Paper
Conrad Borchers, Qianru Lyu, Ritesh Kanchi, Kenneth R. Koedinger et al.
This study compared learning rates and gains between middle-school students practicing math problems with an intelligent tutoring system (ITS) versus on paper. Results showed significantly higher learning rates and gains with ITS, especially for lower-proficiency students, while paper-based practice showed little measurable learning. The findings emphasize the importance of immediate feedback and adaptive support in learning.
Original abstract
Intelligent tutoring systems (ITSs) are widely used in K-12 education and are known to improve learning outcomes compared to traditional instruction. However, prior work has focused primarily on end-of-test performance, with little attention to learning processes, such as how much students learn at each practice opportunity. In particular, learning rates have been extensively studied in ITS environments but not for paper-based problem solving. We conducted a within-subjects classroom experiment with 97 middle-school students solving matched mathematics problems either with an ITS or on paper. We compared both overall learning gains and process-level learning rates, defined as improvement per problem-solving step. To enable this comparison, we introduce a novel method for converting paper-based work into step-level transaction data compatible with learning-curve modeling. Results show that ITS-supported practice led to significantly higher learning gains and substantially higher learning rates than paper-based practice. While students in the ITS condition exhibited consistent positive learning rates, learning rates in the paper condition were indistinguishable from zero, indicating little measurable learning during problem solving without feedback. These differences were especially pronounced for students with lower prior proficiency. This study provides the first direct comparison of learning rates between ITS and paper-based practice and introduces a generalizable methodology for analyzing learning processes in non-digital environments. The findings highlight the critical role of immediate feedback and adaptive support in enabling learning during practice and support the broader adoption of ITS in K-12 education.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Teaching Formula-Based Garment Pattern Drafting: An Illustrated Guide for Beginners and Tailoring Students
Basker Palaniswamy
This paper presents a formula-based guide for drafting garment patterns for adults and children, with step-by-step instructions and illustrations. It extends to early childhood education, demonstrating how pattern making can support mathematics, motor skills, and teacher-made resources. Despite its educational applications, the content is unrelated to language teaching.
Original abstract
Pattern making is a way of changing body measurements into shapes that can be cut from cloth and stitched into clothes. Many books explain pattern making, but they are often difficult for beginners to understand. This article explains the steps in a simple and clear way. It teaches how to make patterns for common clothes such as shirts, T-shirts, pants, shorts, cargo pants, churidar pants, chudithar tops, blouses, vests, trunks, bras and panties. For each dress type, the article explains what measurements are needed, how to take them, how to use simple formulas, and how to draw the pattern step by step. The article also explains how to draw parts such as sleeves, collars, cuffs, pockets, belts and waistbands. Twenty-three labelled drawings are included to make the steps easy to follow. At the end, common stitching mistakes are shown with simple ways to correct them. This article is useful for students, beginners, home sewers and small tailoring shops who want to learn pattern making in an easy and practical way. This edition extends the adult wardrobe with material written for early childhood education and care (ECEC) settings. It explains how to measure young children safely and respectfully, gives a height-based size chart for ages one to six, and adds two fully worked children’s drafts — an elastic-waist play short and a classroom art smock — that follow the same formula style as the adult blocks. A dedicated section then shows how educators, pre-service teachers and family-engagement programmes can use pattern making: as a source of teacher-made resources (dress-up costumes, doll clothes, puppets and dramatic-play props), as embedded early mathematics (measuring, halving and quartering, symmetry, and turning flat shapes into three-dimensional objects), as support for fine motor development and practical-life dressing skills in the tradition of Froebel and Montessori, and as low-cost professional development for practitioners. Safety rules for children’s garments, including the restriction of cords and drawstrings, are summarized so that everything an educator makes from this guide is safe for young children to wear and use.
- PaperEdArXiv (OSF Preprints)20 Jul 2026
Teachers’ Professional Noticing as a Mediating Mechanism in the Development of Students’ Mathematical Reasoning: A Conceptual Analysis
Andrew Oluwashijibomi Adegoju, Sukurat Olabisi Kofoworola, Emmanuel Tomiwa siyanbola, Nurudeen Kolade Gbadegisin
This conceptual analysis synthesizes research on teachers' professional noticing—attending to, interpreting, and responding to students' thinking—and articulates how it mediates classroom interactions and students' mathematical reasoning. The paper proposes an integrative framework linking dimensions of noticing to forms of reasoning, reframing professional noticing as a relational instructional practice rather than a purely cognitive skill.
Original abstract
Teachers’ professional noticing - the capacity to attend to, interpret, and respond to students’ mathematical thinking has become a central construct in mathematics education research. While substantial scholarship has documented how teachers notice students’ ideas, considerably less theoretical work has examined how professional noticing functions as a mechanism that shapes students’ opportunities for mathematical reasoning. This paper advances a non-empirical, theory-forward analysis that synthesizes research on professional noticing, professional vision, and mathematical reasoning to articulate how teachers’ noticing practices mediate classroom interactions and reasoning processes. Drawing on established conceptualizations of professional noticing (Jacobs et al., 2010; Sherin & van Es, 2009) and theories of mathematical reasoning and discourse (Lobato et al., 2013; Sfard, 2008), the paper proposes an integrative framework linking dimensions of noticing to forms of student reasoning. By reframing professional noticing as a relational and interpretive instructional practice rather than a purely cognitive skill, this paper clarifies its significance for mathematical reasoning and outlines implications for research, teacher education, and professional development.
- PaperComputers & Education20 Jul 2026
The experience of using AI-generated social stories as a behavioral intervention tool for children
Nechami Zaklas, Tali Gazit
This paper explores the use of AI-generated social stories as a behavioral intervention tool for children, examining their effectiveness in modifying behavior.
- PaperOpenAlex — TESOL research20 Jul 2026
The Role of Lexical Background in English Vocabulary Acquisition in Mexico
Claudia Andrea Durán Montenegro, Alicia Marcela Rendón Castro, Mabel González Jiménez
A study of Mexican learners found that vocabulary instruction often ignores the English-related words and cognates students already know from media exposure. The authors propose activating this prior lexical knowledge to make vocabulary learning more meaningful and efficient.
Original abstract
This study examines the role of prior lexical knowledge in English vocabulary acquisition among Mexican learners.It argues that vocabulary instruction often underestimates the English-related words, cognates, and culturally familiar lexical items that students have already internalized through everyday exposure to media, technology, music, sports, and popular culture.Rather than treating learners as if they had no previous contact with English, the study proposes that teachers should identify and activate this existing knowledge to support more meaningful and efficient vocabulary learning.By connecting new lexical input with words students already recognize and use, instruction can promote comprehension, confidence, and motivation.The study concludes that recognizing learners' linguistic resources has important pedagogical implications for English language teaching in Mexico.
- PaperOpenAlex — TESOL research20 Jul 2026
Teaching with Technology, Leading with Values: ELT Teachers and the Future of AI in Education
Senem Zaimoğlu
The study examines how ELT teachers can integrate AI into their practice while upholding pedagogical and ethical values, focusing on the teacher's role in shaping the future of AI in education.
- PaperOpenAlex — TESOL research20 Jul 2026
Edutainment Through Translanguaging Practices: A Multimodal Discourse Analysis of Short‐Form English Instructional Videos on Douyin
Yongli Qin, Baizhi Yin
The study analyzed song and role-play English teaching videos on Douyin using translanguaging theory and multimodal discourse analysis. It found that creators combine multilingual and multimodal resources to achieve edutainment and stimulate positive emotions. The findings extend translanguaging research to short-form video contexts and reconceptualize edutainment.
Original abstract
Recent research in applied linguistics has increasingly attended to translanguaging practices in digitally mediated contexts, yet relatively little is known about how translanguaging practices achieve edutainment within the context of the highly compressed short‐form videos as dynamic discourse on Douyin, China's localized counterpart to TikTok. Drawing on translanguaging theory and multimodal discourse analysis, the study analyzes a song video and a role‐play video for English language teaching. The findings show that content creators flexibly draw on diverse multilingual and multimodal resources. The orchestration of these translanguaging resources has created unique ways for the realization of edutainment in the song video and role‐play video, respectively. The findings also indicate that the use of diverse translanguaging resources in each type of video stimulates positive emotions. By providing the reconceptualization of edutainment, this study is positioned as a complementary study grounded in a specific empirical context. This study not only extends translanguaging scholarship into the dynamic context of short‐form videos on Douyin but also re‐examines the relationship between education and entertainment, enriching existing scholarly understandings of edutainment.
- PaperAssessing Writing20 Jul 2026
Text quality and vocabulary in native and non-native Spanish analytical writing: From elementary education to university
Rocío Cuberos, Elisa Rosado, Iban Mañas Navarrete
This study compares text quality and vocabulary use in analytical writing by native and non-native Spanish speakers from elementary to university levels, examining developmental trends across education.
- PaperComputers and Education: Artificial Intelligence20 Jul 2026
AI adoption readiness among Ukrainian education managers: Barriers, typologies, and policy implications
Vasyl Kremen, Oleg M. Spirin, Олександр Ляшенко, Svitlana Lytvynova et al.
A study of Ukrainian education managers reveals barriers to AI adoption and develops typologies of readiness, with implications for policy.
- PaperLanguage Teaching Research20 Jul 2026
Motivation Through Extensive Reading: A Self-Determination Theory Perspective on Young Learners of English as a Foreign Language
Jing Zhou, Mark Feng Teng, Yuman Xiao
An extensive reading program for middle-school EFL learners significantly increased overall motivation, including intrinsic motivation and various forms of regulation, as measured by questionnaires and qualitative data. The study confirms extensive reading as an effective motivational approach.
Original abstract
This study investigates the impact of an extensive reading program on the English learning motivation of young middle-school learners of English as a foreign language, utilizing the self-determination theory framework. Eighty-one Grade 7 students participated in a semester-long extensive reading program designed to provide supportive conditions by allowing students to select reading materials that matched their proficiency levels and personal interests. Employing a mixed-methods approach, quantitative data were collected through pre- and post-motivation questionnaires measuring intrinsic motivation, external regulation, introjected regulation, and identified regulation, whereas qualitative data were obtained from student interviews and teacher focus groups. This study identified a multi-factor structure of motivation. It also revealed a significant increase in overall motivation, with intrinsic motivation, identified regulation, introjection regulation, and external regulation notably enhanced. Qualitative findings identified key factors contributing to motivational changes, including heightened interest in English classes, English subject, and English language; a greater sense of achievement; improved academic performance; and increased social interactions during reading activities. The study confirms extensive reading as an effective approach for fostering motivation of learning English and suggests its broader implementation among middle school learners of English as a foreign language.
- PaperLanguage Learning & Technology20 Jul 2026
The development of EFL learners’ self-efficacy in technology use environments
Xuelian Li, Manzhen Yang
A mixed-methods study tracked 102 EFL university students over 15 weeks and found significant increases in overall, speaking, listening, and writing self-efficacy in technology-rich environments. Qualitative analysis revealed how technological affordances shaped the four sources of self-efficacy, explaining why reading self-efficacy did not increase. Pedagogical implications focus on strengthening reading self-efficacy and optimizing technology use.
Original abstract
Self-efficacy plays a critical role in language learning motivation, performance, and achievement. However, limited research has examined how different dimensions of English self-efficacy evolve over time and the mechanisms underlying such development in technology use environments. To address these gaps, the present study adopted a mixed-methods design. A total of 102 university students completed questionnaires at three time points over a 15-week period, and 10 participants subsequently took part in semi-structured follow-up interviews. Quantitative findings revealed a significant increase in overall English self-efficacy, as well as in three specific dimensions: speaking, listening, and writing self-efficacy. Qualitative findings further demonstrated how the four sources of self-efficacy, shaped by technological affordances, were associated with students’ efficacy beliefs and helped explain why reading self-efficacy did not show a statistically significant increase within the same learning ecology. The study concluded by discussing pedagogical implications for strengthening reading self-efficacy and optimizing the use of technology in language learning, as well as limitations of the study and directions for future research.
- PaperAssessment & Evaluation in Higher Education19 Jul 2026
Shaping equity through assessment: a multi-institutional analysis of ethnic awarding gaps in UK higher education
Gabriella Cagliesi, Daniela Tavasci, Valeria Terrones Rodriguez, Luigi Ventimiglia
This study examines ethnic awarding gaps across multiple UK higher education institutions, highlighting disparities in assessment outcomes. The findings underscore the need for equitable assessment practices to address systemic biases.
- PaperLanguage Testing19 Jul 2026
Outcomes of One-Skill Retakes in a Four-Skills Proficiency Test: Evidence From Large-Scale Test Data
Hye-won Lee, Emma Bruce, Jan Langeslag, Reza Tasviri
The study analyzes over 20,000 test takers using IELTS One Skill Retake (OSR) and finds that average retake scores were higher than original scores, with overall band changes similar to short-interval full-test repeaters. Survey data from 578 test takers indicates factors like insufficient preparation, stress, and fatigue contributed to initial underperformance. The findings provide empirical evidence for interpreting one-skill retake scores and inform discussions on validity and equity in large-scale language testing.
Original abstract
A test taker may underperform for reasons not fully attributable to language proficiency, including psychological or contextual influences such as anxiety or illness. IELTS One Skill Retake (OSR) was launched in 2022, allowing test takers to retake, within 60 days, a single component in which their initial performance may have been affected by extenuating circumstances. This study examines outcomes associated with OSR by analysing test-taking patterns and score changes among over 20,000 OSR test takers from its launch through Spring 2024. It also reports survey findings from 578 OSR test takers on their experiences, including whether they achieved target scores and their perceived reasons for not achieving the desired score on the original full test. Across skills, average OSR component scores were higher than the corresponding scores on the original full test, and overall-band changes among OSR test takers were comparable to those observed among short-interval full-test repeaters (⩽60 days). Survey responses commonly cited factors such as insufficient preparation, stress and anxiety, and fatigue and lack of focus as perceived contributors to underperformance on the initial test. The findings contribute empirical evidence relevant to the interpretation and use of one-skill retake scores and to ongoing discussions of the validity and equity implications of retake policies in large-scale language testing.
- PaperTESOL Quarterly19 Jul 2026
Collaborative Development of a Research Agenda to Claim Language Teaching as a Site of Knowledge Production
Yoshiyuki Nakata, Xuesong (Andy) Gao
Proposes a collaborative, multi-step process for developing research agendas in TESOL that involve both researchers and practitioners. Argues that redefining research agendas as inclusive and practice-oriented strengthens the link between research and teaching, positioning language teaching as a site of knowledge production. Outlines six steps from understanding contextual needs to publishing in aligned forums.
Original abstract
The development of research agendas is a crucial component of the process of reclaiming teaching as a site of knowledge production in language education research. However, in the TESOL field, the research agenda (RA) has traditionally been defined in relation to a gap between research and practice. Researchers often justify their work by highlighting significant disciplinary knowledge gaps. Therefore, when developing an RA, we must ask ourselves: (1) Whose interests does the RA serve? (2) Who should be involved in setting the RA? And (3) how can the RA be created and promoted? Engaging proactively with these questions encourages collaboration with practitioners and strengthens the link between research and practice. This approach helps us establish inclusive research agendas that benefit knowledge producers, including teachers, students, policymakers, and researchers. An RA should emerge from a collaborative and consultative process involving both researchers and teachers as practice researchers. Collaborative RA development involves several steps: (1) understanding the needs of the educational context; (2) formulating a preliminary research design and questions that incorporate practitioners' perspectives; (3) conducting a literature review to help researchers and teachers as knowledge producers understand the research's significance; (4) selecting methods aligning with the research design and questions, ensuring consistency with the RA; (5) providing readers with detailed information about the RA to offer context; and (6) publishing in a medium and forum aligned with the RA. This article discusses these steps in detail, outlines strategies for their implementation, illustrating the collaborative process for developing research agendas in TESOL. From a practical perspective, this paper argues for the agentic involvement of both researchers and practitioners in developing RAs, highlighting the connections between their roles in the research process and raising researchers' awareness of research practices that foster a virtuous circle between research and practice.
- PaperLanguage Testing19 Jul 2026
Can an AI Agent Replace Human Examiners in High-Stakes Interactive Speaking Tests? A Debate
Jing Xu, Lynda Taylor, Xiaoming Xi, Yasin Karatay et al.
This viewpoint article presents arguments for and against replacing human examiners with AI agents in high-stakes interactive speaking tests, drawing on a debate at the 2025 LTRC. It examines construct theory, practicality, washback, fairness, and ethical uses of AI in language assessment.
Original abstract
Generative artificial intelligence (GenAI) is advancing at a remarkable speed, and its promise in transforming current practice in language assessment has been articulated by applied linguistics researchers. An emerging application of GenAI is to integrate the technology into Spoken Dialogue Systems (SDSs) to simulate human interlocutors for the purpose of speaking practice or assessment. Despite rapid technological advances, the issue of whether an AI agent can replace a human examiner in one-on-one, high-stakes interactive speaking tests remains contentious. Building on a lively academic debate on this topic at the 2025 Language Testing Research Colloquium (LTRC) in Bangkok, this Viewpoint presents arguments both for and against this proposition in terms of construct theory, practicality, washback, fairness, ethical uses of AI, and so forth.
- NewsEdSurge19 Jul 2026
These Hip-Hop Artists Were Already Teaching
A new partnership between College Unbound and the Hip-Hop Education Center offers a BA in organizational leadership and change for hip-hop educators, recognizing their community-based teaching expertise rather than requiring traditional credentials. The program asks who gets to define expertise in education, aiming to validate alternative pathways into teaching.
Original abstract
<p>For decades, hip-hop artists have been invited into schools as guest speakers, workshop leaders and visiting performers. They’ve mentored young people after school; started nonprofits; taught music production, poetry, history and entrepreneurship; and helped generations of students find their voices.</p><p>Yet many of these artists lack the one credential schools still value most: a bachelor’s degree.</p><p>But what if these artists have been teaching all along?</p><p>A new partnership between <a href="https://collegeunbound.edu/">College Unbound</a> and the <a href="https://www.hiphopeducation.org/">Hip-Hop Education Center</a> aims to answer that question, not by teaching artists how to become educators but by recognizing the expertise they’ve developed through decades of community leadership, cultural work and mentorship.</p><p>The program — a Bachelor of Arts in organizational leadership and change designed specifically for hip-hop educators and cultural leaders — isn’t a separate degree or a simplified version of one. Students complete the same degree requirements as every other College Unbound student. “It’s the same degree,” says College Unbound President Adam Bush. “It’s simply lived differently.”</p><p>The program is about more than hip-hop. It asks a question that reaches far beyond music: Who gets to decide what expertise looks like?</p><h2>A Degree Years in the Making</h2><p>Although the bachelor’s degree officially launched this year, its roots stretch back decades.</p><p>Hip-hop emerged outside traditional institutions, often in response to systems that excluded Black and Brown communities. As hip-hop education gained legitimacy, educators wrestled with a difficult question: How can we preserve the authenticity of the hip-hop culture while creating pathways that allow practitioners to teach at schools and colleges?</p><p>Long before there was a curriculum at College Unbound, there were conversations between Bush, educator and author Sam Seidel, and