TOWARDS APPLYING NATURAL LANGUAGE APPROACH IN IMPROVING STUDENTS' WRITING SKILLS: LECTURER FEEDBACK TOOLS (LEFT)

Abstract

Automatic text summarisation involves creating a concise and coherent description while preserving essential information and context. Time constraints faced by educators prompted this study. Writing is a crucial skill for students, especially in English; however, many need more feedback on their mistakes. Writing, akin to scaffolding, necessitates the involvement of proficient essay writers to assess and review students' work. Scaffolding facilitates student engagement and improves learning outcomes, making it an effective instructional strategy. To address this issue, Lecturer Feedback Tools (LeFT), a Natural Language Processing web application system, is introduced to educators to provide feedback to enhance students' writing skills. It utilises four summarisations SpaCy, Gensim, Natural Language Toolkit, and Sumy. What sets this tool apart is its ability to record all operations in a database, ultimately boosting educators' productivity and students' work. The evaluation results show a consensus among participants, with 66.7% expressing the system's usefulness and 83.3% finding it easy to use, reflecting their satisfaction with the study's outcomes.