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Abstract This study introduces an intelligent, large language model (LLM)–driven feedback system designed to assess and enhance students’ programming tasks through semantic comparison and pedagogically contextualized...

Abstract The current English grammar error correction model still has low accuracy when dealing with complex sentences and long sentence dependencies. Therefore, this study proposes a Sequence-to-Sequence (Seq2Seq) model...

Abstract This study seeks to address persistent challenges in traditional music education, particularly the subjectivity inherent in assessment criteria and the frequent delays in feedback, by harnessing the capabilities...

Aims: Plants interact by modifying soil conditions in plant-soil feedback processes. Foliar endophytes of grasses exert multiple effects on host rhizosphere with potential consequences on plant-soil feedback. Here, we hy...

Abstract Matching college students with appropriate innovative training projects is a challenging task that often relies on static assignment techniques, which overlook individual interests, skills, and learning styles. ...

Abstract This research is concerned with the innovative use of AI in cross-cultural music learning, more particularly in the creation of a multimodal learning model that combines audio identification, image analysis, and...