Efl Undergraduates’ Evaluative Judgement In Responding To AI-Generated Suggestions Throughout The Thesis Writing Process
Year: 2026
Type: dissertation
Abstract: Generative Artificial Intelligence (GenAI) has been widely used, especially in academic writing.This phenomenon has raised the concern of the disruption of thesis writing, especially in how ideas are generated and selected.In this context, students need the ability to judge AI-generated content before generating it in their academic work.This study aims to discover the criteria and logic behind students' evaluative judgement when responding to GenAI-generated suggestions in thesis writing.The study also seeks to answer how students respond to those suggestions through acceptance, modification, or rejection.This research employed a qualitative descriptive design, and the participants were six final-year students.The data were collected through a screening questionnaire and in-depth semi-structured interviews.The collected data were then analyzed using thematic analysis to identify the evaluative patterns in students' responses.The study shows that students' evaluative judgement is developed by several criteria, namely novelty, feasibility, theoretical alignment, personal interest, and credibility.These criteria influenced the students' decision to accept, modify, or reject the generated suggestions.The study concludes that human judgement remains dominant in determining the quality and integrating it into undergraduate thesis writing.
Author: MUKTI, YOHANES WISNU HARI
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7161212438