Speaker
Description
The study focuses on the teaching purposes and language choices of teachers’ embedded commentary on upper secondary school EFL students’ writing within a test-oriented Vietnamese context. Well-grounded in an adapted classification framework (Derham et al., 2022; Hattie & Timperley, 2007), the research explores how educators balance the dual roles of judging and guiding. To achieve this, a quantitative document analysis was conducted on 1,434 comments extracted from 55 students’ essays, utilizing the Linguistic Inquiry and Word Count (LIWC-22) software. The findings reveal that feedback is predominantly concentrated on surface-level editorial corrections, heavily overshadowing self-regulatory guidance. Linguistically, however, teachers shift from detached, impersonal phrasing when evaluating to more personalized, insight-driven language when providing developmental feedback. These results highlight a critical need for professional development that prepares teachers to implement cognitively engaging feedback.
Biography
Nguyen Nam Khanh is a dedicated English language educator and independent researcher specializing in English Language Teaching and Applied Linguistics. With over four years of teaching experience and a professional TESOL certification from Arizona State University, his daily classroom practice directly informs his academic pursuits. His primary research areas encompass technological integration, feedback and assessment, teacher career development, and curriculum design. Recently, his scholarly work has focused on analyzing the linguistic and cognitive dimensions of teacher commentary, exploring how educators can balance evaluative and developmental feedback to foster student autonomy. This research has been featured at prominent academic forums, including the ICTE, BLEND 2026, and KOTESOL 2026 conventions. In addition to his pedagogical research, Khanh actively pioneers the integration of artificial intelligence in education. He leverages platforms like Google AI Studio and automation tools such as n8n to streamline academic workflows, generate learning materials, and develop AI teaching assistants, aiming to enhance instructional efficacy and elevate student learning outcomes.
| Affiliate type | Vietnamese public school |
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