TL;DR
The results suggest that a fine-tuned transformer model can reliably code self-affirmation essays, thereby reducing the coding burden for future researchers and educators.
Although LLM-based benchmark ratings can approximate expert judgments and reduce the need for labor-intensive human triple coding, limitations remain regarding cost, genre- and task specificity, and sensitivity to text presentation and student grade level—factors that constrain immediate classroom use, particularly for...
—This longitudinal single-case study investigates the impact of DeepSeek, a Chinese-developed Large Language Model (LLM), on the English writing development and motivation of a Chinese EFL learner aged 15. Given the increasing importance of written communication in international professional contexts, particularly thro...
It is claimed that LLMs are the latest AI-generated product utilized in academic discourses, enriching the capacity of the user and could be minimized by careful attention, capacity, tactful utilization, and knowledge of the user.
Student-generated metaphors about mathematics can provide insights into students'attitudes, beliefs, identities, and experiences, but expert human assessment through thematic coding of these semantically complex metaphor responses is labor-intensive and difficult to scale. This study examines whether Low-Rank Adaptatio...
This study systematically evaluates generative pre-trained transformer (GPT)-based large language models for the automated writing evaluation of Italian as a second language (L2). Drawing on 1,832 learner texts, we compare six GPT-based experimental conditions: zero-shot and few-shot prompting with GPT-4.1 and GPT-5, a...
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