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- PaperOpenAlex — TESOL researchForthcoming · 1 Jan 2031
Depth of Processing, learner aptitude, and the acquisition of L2 English grammatical structures
Shweta Nigam
This study investigated whether task-induced depth of processing (DoP) influences the acquisition of third conditionals and comparatives in EFL learners, and whether language aptitude predicts learning gains. Results showed a significant effect of processing condition on a grammaticality judgement test, with the High DoP Implicit group outperforming others on comparatives, but no significant group differences on an elicited imitation task after controlling for pretest scores. Overall, deeper processing benefits were structure-specific, favoring more salient structures on explicit measures, while complex low-salience forms showed increased frequency of use but limited accuracy change.
Original abstract
Depth of Processing (DoP) is central to several models of instructed second language acquisition (ISLA) (Leow, 2015). While DoP has been extensively examined in vocabulary learning (e.g., Laufer & Hulstijn, 2001), its role in the acquisition of grammatical structures, particularly through oral and audio-visual modalities remains comparatively underexplored. Drawing on the Levels of Processing framework (Craik & Lockhart, 1972), this study investigated whether task-induced processing depth influences the acquisition of third conditionals and comparatives, and whether language aptitude (LLAMA B, D, F) predicts learning gains. Using a pretest–posttest design, four intact classes involving 108 Grade 8 EFL learners in India were assigned to one of the three experimental conditions differing in level and type of processing: Low DoP, High DoP Explicit, and High DoP Implicit. The treatment task required the participants to listen to an audio-visual story containing the target structures (third conditionals and comparatives) and complete analytic tasks (varying in different groups) before listening to the story for a second time. The oral performance of the participants was analysed for accuracy, and frequency of use of the target structures. A grammaticality judgement test (GJT) and an elicited imitation task (EIT) were used to assess the participants’ gains in the knowledge of the target structures. In addition, language aptitude (LLAMA B, D, F) was measured and modelled as a predictor of gain scores. Results showed a significant effect of processing condition on GJT performance with the High DoP Implicit group outperforming the High DoP Explicit group on total scores and comparatives. In contrast, ANCOVA analyses indicated no significant group differences on EIT outcomes once pretest performance was controlled, with pretest scores strongly predicting posttest performance. In oral production, processing effects were structure-specific: the Low DoP group showed greater accuracy gains for comparatives, while both High DoP groups revealed increased frequency of use of third conditionals. However, across all four measures, multiple regression analyses indicated that LLAMA B, D, and F did not significantly predict gain scores. Overall, the findings support a processing-by-structure pattern: deeper processing benefits were most evident for the more salient structure (comparatives) on an explicit, written measure, whereas complex, low-salience forms (third conditionals) showed limited accuracy change but increased frequency of use under deeper processing.
- PaperLanguage Teaching Research22 Jul 2026
AI-Assisted Digital Storytelling in EFL Teacher Education: A Qualitative Case Study of Digital and Multimodal Literacy Development
Bessie Mitsikopoulou
A qualitative case study examined how EFL student teachers used generative AI tools (text-to-image, video editors, speech synthesis) to collaboratively design digital stories. Analysis of 69 reflective papers found that algorithmic limitations prompted students to become critical designers of meaning, with the human element remaining essential for narrative coherence.
Original abstract
This qualitative case study explores how English as a foreign language (EFL) student teachers engaged with generative artificial intelligence (GAI) in the collaborative design of digital stories within an advanced undergraduate course in 2024. During the semester, participants critically evaluated and applied various AI applications, such as text-to-image generators, automated video editors and speech synthesis tools, to support different stages of multimodal story production, including script drafting, visual design, audio narration and video editing. Drawing on a corpus of 69 reflective papers (approximately 75,000 words), the study examines how student teachers integrated visual, auditory and textual elements to achieve multimodal cohesion and narrative coherence. The analysis focuses on participants’ practices and strategies for aligning modes, maintaining consistency across media, and adapting to the constraints of AI-generated content. Findings indicate that the project’s primary pedagogical significance lay not in technical efficiency but in the productive ‘friction’ generated by algorithmic limitations, which led participants to move beyond passive tool use and become critical designers of meaning, demonstrating sophisticated multimodal awareness. While AI supported rapid content generation, the human element remained the narrative’s essential ‘emotional glue’, ensuring affective resonance and coherence. Overall, the study suggests that experiential engagement with AI-assisted composition may enable future educators to move beyond functional skills and develop into critically reflective architects of digital narratives.
- 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
A semester-long extensive reading program significantly increased English learning motivation among 81 Chinese middle school EFL students, particularly intrinsic and identified regulation. Qualitative data revealed heightened interest, sense of achievement, and social reading interactions as key drivers. Findings support broader implementation of extensive reading to foster motivation in young EFL learners.
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.
- PaperReCALL25 May 2026
A culturally responsive blended learning framework for technology-enhanced EFL contexts
Mengjia Liu, Harwati Hashim, Nur Ainil Sulaiman
A Culturally Responsive Blended Learning Success model was developed and validated for evaluating technology-enhanced EFL instruction in collective educational contexts, integrating three platforms and surveying 1,816 Chinese undergraduates. Learner and instructor quality significantly influenced satisfaction and usefulness, while cultural moderators (hierarchical relationships, collective learning, exam-driven motivation) enhanced model validity, explaining 71.4% of variance in perceived satisfaction and 64.7% in perceived learning benefits.
Original abstract
This quantitative study develops and validates a novel Culturally Responsive Blended Learning Success (CR-BLS) model for evaluating technology-enhanced EFL instruction effectiveness in collective educational contexts. Conducted at a Chinese university, the research examined an intelligent blended learning ecosystem integrating three widely adopted platforms (U-Campus, GradingNet, and Learning Hub) for content delivery, assessment, and collaboration in College English instruction. The CR-BLS model extends a widely recognized seven-factor quality framework by integrating three culturally grounded moderators: hierarchical teacher–student relationships, collective learning orientation, and examination-driven motivation. The proposed model was empirically validated through data collection from 1,816 non-English major undergraduates engaged with the blended learning ecosystem using partial least squares structural equation modeling (PLS-SEM). Results revealed that the proposed quality factors explained 71.4% of the variance in perceived satisfaction, 54.2% in perceived usefulness, and 34.1% in system use. Learner quality and instructor quality significantly influenced both perceived satisfaction and usefulness, while educational system quality primarily affected system use. Furthermore, perceived usefulness, satisfaction, and system use collectively accounted for 64.7% of the variance in perceived learning benefits. Cultural moderators demonstrated significant influence on the relationships between quality dimensions and learning outcomes, enhancing the proposed model’s contextual validity for collective educational environments. This study contributes to both theoretical advancement and practical implementation of blended learning systems in collective educational settings.