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- 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.
- PaperComputers and Education: Artificial Intelligence17 Jun 2026
Effects of an AI-supported inquiry model on AI literacy and authentic performance: A quasi-experimental study with preservice teachers
Dongyun Cao, Yuting Yan, Anyuan Xiong, David Wicks
A quasi-experimental study with 95 preservice teachers tested the QUEST + AI inquiry model, which integrates structured AI use across five phases. The experimental group showed higher overall AI literacy, particularly in applying AI and emotion regulation, and produced better research proposals compared to the control group. Results suggest that guided AI-supported inquiry can enhance applied AI skills and authentic performance in teacher education.
Original abstract
As generative AI becomes more common in teacher education, programs need instructional models that help preservice teachers use AI purposefully, critically, and productively in authentic academic work. However, evidence on how structured AI-supported inquiry improves both AI literacy and performance remains limited. Grounded in Deweyan Inquiry and the Practical Inquiry model, this quasi-experimental study examined the effects of QUEST + AI, an AI-supported inquiry model built around five phases: Question, Understand, Engage, Solve, and Teach. Ninety-five preservice teachers in an educational research methods course participated in a 10-week study using two intact classes (experimental n = 52; comparison n = 43). Both groups received the same in-class instruction, but the experimental group completed two QUEST + AI cycles with coached generative AI use, whereas the comparison group completed conventional homework. Outcomes included a multidimensional AI literacy measure and a capstone research proposal scored with a common rubric. After controlling for pretest, gender, and grade, the experimental group showed higher overall AI literacy, with small but meaningful gains concentrated in applying AI, AI-supported problem solving, and emotion regulation during AI use. No clear group differences were found for more concept-focused or evaluative dimensions. The experimental group also earned higher scores on the final research proposal, indicating a moderate advantage in authentic performance. These findings suggest that structured AI-supported inquiry can strengthen applied and self-regulatory aspects of AI literacy while improving discipline-relevant performance. Limitations include the modest single-site sample, intact-group design, brief intervention, and reliance on several self-report subscales. Future research should use larger and more diverse samples, longer interventions with follow-up measures, and more performance-based assessments triangulated with protocol-adherence data.
- PaperDOAJ — ELT & TESOL1 May 2026
Understanding EFL preservice teachers’ intentions and concerns of integrating AI in their future ELT
I Putu Indra Kusuma, Sandrotua Bali, Ehsan Namaziandost, Luh Gd Rahayu Budiarta et al.
This qualitative study investigated EFL preservice teachers' intentions and concerns about integrating AI in English language teaching. Results from questionnaires and interviews revealed strong intentions to use AI, along with both positive perceptions and constructive concerns. The study offers implications for teacher education programs and policymakers.
Original abstract
Research shows that English as a foreign language (EFL) in-service teachers are widely implementing AI in English language teaching (ELT). It remains unclear how novice pre-service teachers (PSTs) with limited teaching experience intend to integrate AI into ELT. At the same time, research addressing the concerns of PSTs is scarce. Nonetheless, they represent the forthcoming generation of teachers who will engage with AI in ELT. Given the above gaps, this study aimed to explore the intentions and concerns of EFL PSTs regarding the integration of AI in ELT. This research employed a basic qualitative approach and recruited EFL PSTs enrolled in an English teacher education program at a state university in Indonesia. The data was collected through an open-ended questionnaire and semi-structured interviews. Then, the data from the questionnaire was analyzed using the content analysis method, and the data from the interviews were analyzed using the inductive thematic analysis method. The open-ended questionnaire indicated that EFL PSTs demonstrated significant intentions to use AI. The interview findings also indicated an intention to integrate AI in future instructional design, alongside favorable perceptions of AI for teaching and its application by students in learning contexts. They also expressed both negative and constructive concerns regarding the integration of AI in ELT. Three new implications, such as one theoretical and two practical ones for EFL PSTs, teacher education programs, and policymakers, are drawn for English teacher education programs to enhance EFL PST preparation.