teacher-education
Filtering by topic teacher-education(5)Clear all filters
- PaperLanguage Teaching Research23 Jul 2026
The Activity Design Typology: A Practitioner-Centered Approach to Understanding Task Structure
Lara Bryfonski, Caitlyn Pineault
An analysis of 114 activities created by world language teachers in a task-based teacher education program revealed that traditional task definitions inadequately capture their design intricacies. A directed content approach identified five distinct activity categories, leading to the Activity Design Typology, which offers a practitioner-centered framework for understanding, explaining, and evaluating instructional tools.
Original abstract
As the central construct in task-based language teaching (TBLT), “task” has been defined in a myriad of ways. Though popular criterion-based definitions offer a tantalizingly straightforward description of the construct, they have, at times, proved difficult to apply in practitioner contexts. With over 17 definitions identified in the literature, prominent scholars have advocated for efforts that offer a more unified understanding of “task” that may be better able to support task-based language teaching in implementation initiatives. This exploratory, qualitative study examines how two cohorts of K–16 U.S.-based world language teachers ( n = 35) approached task design in a task-based teacher education program from a materials development perspective. An analysis of the 114 activities teachers created revealed that although submissions had task characteristics, the intricacies of their designs were not adequately captured by traditional task criterion. Subsequent analysis following a directed content approach identified five distinct categories of activity design. Advancing previous interest in expanding the binary distinction of “task” versus “non-task,” we drew on these categories to develop the Activity Design Typology. The typology serves as a resource for understanding, explaining, and evaluating instructional tools for their pedagogic and empirical value. Use cases for the task typology are discussed in relation to initiatives aimed to further instructed second language acquisition research agendas and support TBLT implementation efforts.
- PaperTESOL Quarterly22 Jul 2026
Unveiling the AI Divide: A Comparative Study of Novice and Veteran EFL Teachers' Experience of Using Generative AI in Teaching
Qi Lin
A comparative study of novice and veteran EFL teachers reveals that the AI divide emerges mainly at the levels of AI capability and AI outcomes rather than access, shaped by factors such as perceived ease of use, educational background, social support, and professional development opportunities.
Original abstract
The rapid advancement of artificial intelligence (AI) has brought both opportunities and challenges to the field of education. Within this evolving landscape, the emergence of the AI divide has become a pressing concern, particularly in teacher education and EFL instruction. This study developed a three‐level three‐factor conceptual framework to explore the AI divide through the dimensions of AI access, AI capability, and AI outcomes, while also considering technological, personal, and institutional influences. Using this framework, the study employed a comparative research design to examine how novice and veteran EFL teachers integrated AI differently in their teaching practices. The findings revealed that the AI divide between novice and veteran EFL teachers mostly occurred at the second level (AI capability) and third level (AI outcomes), rather than the first level (AI access). These disparities were shaped by a combination of technological, personal, and institutional factors, including perceived ease of use of AI, educational background, social support, and access to AI‐related professional development. This study extends the concept of AI divide into the field of EFL education and offers valuable theoretical insights and practical implications for more equitable AI integration in EFL teaching.
- 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.
- NewsEdSurge24 Jun 2026
Who Is Really in Charge When Tech Enters the Classroom?
Two educators share experiences with technology outpacing institutional readiness: one observes student teachers referencing TikTok for professional knowledge, while another builds an AI grading assistant that returns accurate feedback but raises questions about teacher ownership of grades.
Original abstract
<p>What happens when the tools teachers build start making decisions teachers have not reviewed? And what happens when the knowledge shaping future educators does not come from research or curriculum, but from a social media feed? On <strong>This Week with EdSurge</strong>, two educators are wrestling with technology that is moving faster than their institutions are prepared to handle.</p><h2><strong>When TikTok Becomes the Teacher</strong></h2><p><a href="https://www.edsurge.com/author/evi-wusk"><u>Evi Wusk</u></a>, Ed.D., teaches the people who will become teachers, and she noticed something during final exams that she could not ignore: her students kept referencing TikTok videos and social media reels, then apologizing for it. Wusk wrote about the experience for <strong>EdSurge</strong>, and her conclusion is not what you might expect. She is not calling for a ban or a warning label. Rather, she is asking whether teacher prep programs need to reckon with where professional knowledge is actually forming right now, and what it means if those teaching are the last ones to find out.</p><h2><strong>The Grader Who Was Not in the Room</strong></h2><p><a href="https://www.edsurge.com/author/steven-swanson"><u>Steven Swanson</u></a> teaches high school engineering, and after two consecutive days of field trips he came back to 450 ungraded assignments. So he built a solution: an AI grading assistant that drafted grades, generated comments against his rubrics, and returned everything to students automatically. Then a student thanked him for feedback he had never read. Swanson wrote about what happened next for <strong>EdSurge</strong>, and the story is less about the technology malfunctioning than about what it revealed: even when the AI is accurate, the grade still needs to belong to someone.</p><p>Join us on <strong>This Week with EdSurge</strong> where we dig into what both of these educators decided to do next, and what their answers might mean for every teacher feeling
- PaperComputer Assisted Language Learning11 Jun 2026
AI as a collaborator: pre-service teachers’ perspectives on preparing multimodal language lessons
Lucas Kohnke, Di Zou
Pre-service teachers' perspectives on using AI as a collaborator for preparing multimodal language lessons were explored, highlighting potential benefits and challenges. The study contributes to understanding AI integration in language teacher education.