AI evidence extraction

The Phenomenon of Artificial Intelligence in Assisting in Writing Maritime Student Papers

Darul Prayogo, Awel Suryadi, Mustholiq, Upik Suryandari, Prapti Utami, Juharis et al. · Journal of maritime research · 2026

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10

Relevance

1/4

Quality (LMQS)

Evidence

Citations

0.00

FWCI

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.22429/euc2026.jmr23.1.16

Methodology & findings

Study design

Qualitative research using in-depth semi-structured interviews with 107 maritime students from various universities in Indonesia.

Sample

N = 107, 3 groups

Primary method

Thematic analysis. Data was analyzed through: (1) transcription of interview data verbatim; (2) hand codification to establish major themes; (3) identification of relevant themes after codification; (4) data triangulation with observational data and literature; (5) contextualization of findings within broader literature. No quantitative statistical methods reported.

Main result

The study found that "85% of survey respondents said that AI speeds up the writing process" and "The findings suggest that A.I. can improve both the efficiency and quality of students' writing. Applications like ChatGPT and Grammarly are commonly employed to [help] organize thoughts more coherently, find pertinent citations or sources of information, and check for grammatical correctness." However, the research also identified significant concerns: "Over reliance on AI can curtail the ability of students to think critically and analytically. It raises issues related to originality in academic work as well."

Reports effect sizes.

Research paradigm

Qualitative/Interpretivist

Author conclusions

The authors conclude that "Provided with clear guidelines, students may be able to use AI as a tool that aids in development of their academic abilities without compromising the weight of authenticity and creativity." They further state: "Recommended students of the author are expected to use AI-based tools as a supportive device to accompany him/her in writing papers with the task just partly finished and not replace his/her feet, ideas and hands. AI should streamline work, not excuse basic academic skills." The authors emphasize that "Students need to know that while AI can lend a hand, they still have to get involved in both the learning and writing processes."

Risk of bias

Selection bias: Students were selected from maritime programs in one location (Semarang, Indonesia), limiting generalizability; Self-selection bias: Respondents were specifically "students who ever used AI in writing paper," introducing positive selection bias; No information on sampling method (convenience, random, or purposive) provided; No discussion of researcher positionality or potential interviewer bias; Data analysis performed by hand without inter-rater reliability checks mentioned; No clear description of how thematic saturation was determined; Selection bias: Sample limited to maritime students from Indonesia universities; may not be generalizable to other disciplines or geographic regions; Sampling bias: Participants self-selected as those who used AI; excludes non-users; Single discipline focus: Maritime programs only; findings may not transfer to other fields; No randomization or control group mentioned; Selection bias: participants were self-selected as students who had already used AI in writing papers; Potential social desirability bias in interview responses about AI use; No mention of researcher blinding or control for interviewer effects; Hand coding without inter-rater reliability checks mentioned

Open questions raised

The authors identify the need for: (1) clearer institutional guidelines on ethical AI use in higher education; (2) digital literacy training for both students and faculty; (3) integration of AI ethics into curriculum; (4) stronger plagiarism detection functions in AI tools; (5) better understanding of how different educational levels use AI differently; and (6) investigation of how AI use varies across different academic disciplines.
Need for more specific guidance and training on ethical use of AI in academic writing
Need to understand how AI adoption manifests as global trends in academia
Need to address digital literacy skills development for both students and lecturers
Need for institutions to integrate AI competencies into curriculum
Need for institutional guidance and training on ethical use of AI in academic writing

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