AI-Assisted Academic Writing: Evaluating Postgraduate Students' AI Literacy and Skills

Given the significant increase in the use of AI tools in academic writing, this study aims to assess the AI literacy skills among postgraduate students in academic writing, focusing on their affective, behavioral, cognitive, and ethical competencies. Utilizing a descriptive quantitative approach, data were collected via a survey conducted among 54 postgraduate students from Muhammadiyah University of Pringsewu Lampung and the State Islamic Institute Ambon. The survey included 20 items measuring the four dimensions of AI literacy. Data analysis involved computing frequencies and percentages to evaluate the participants' demographic profile and AI literacy levels. Findings revealed a generally high level of AI literacy, with students demonstrating positive attitudes towards AI tools, active integration of these tools in their writing processes, and a strong understanding of AI's benefits. However, areas for improvement were identified, particularly in motivation and ethical considerations. This research provides insights into the current state of AI literacy among postgraduate students and highlights the need for a targeted AI literacy model to enhance their academic writing skills efficiently and ethically. In conclusion, the research underscores the need for a targeted AI literacy model to enhance students' academic writing skills while addressing motivational and ethical gaps, fostering more effective and responsible use of AI in academic settings.

Authors

Publication Details

Journal
JTP - Jurnal Teknologi Pendidikan
Published
2025-04-25
DOI
https://doi.org/10.21009/jtp.v27i1.48952
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Assisted Academic Writing: Evaluating Postgraduate Students' AI Literacy and Skills

Sangadji
1 citations
JTP - Jurnal Teknologi Pendidikan
Online Learning and Analytics
1.69
article

AI-Assisted Academic Writing: Evaluating Postgraduate Students' AI Literacy and Skills

Sangadji
article en
1 citations

Abstract

Given the significant increase in the use of AI tools in academic writing, this study aims to assess the AI literacy skills among postgraduate students in academic writing, focusing on their affective, behavioral, cognitive, and ethical competencies. Utilizing a descriptive quantitative approach, data were collected via a survey conducted among 54 postgraduate students from Muhammadiyah University of Pringsewu Lampung and the State Islamic Institute Ambon. The survey included 20 items measuring the four dimensions of AI literacy. Data analysis involved computing frequencies and percentages to evaluate the participants' demographic profile and AI literacy levels. Findings revealed a generally high level of AI literacy, with students demonstrating positive attitudes towards AI tools, active integration of these tools in their writing processes, and a strong understanding of AI's benefits. However, areas for improvement were identified, particularly in motivation and ethical considerations. This research provides insights into the current state of AI literacy among postgraduate students and highlights the need for a targeted AI literacy model to enhance their academic writing skills efficiently and ethically. In conclusion, the research underscores the need for a targeted AI literacy model to enhance students' academic writing skills while addressing motivational and ethical gaps, fostering more effective and responsible use of AI in academic settings.

JTP - Jurnal Teknologi PendidikanVol. 27(1)
Openalex Percentile: Top 14%
Online Learning and Analytics
1.69
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.