The study examined the relationship between AI literacy, responsible AI use, and academic integrity among university students in Indonesia and Thailand. The findings show that students with stronger AI literacy tend to evaluate AI-generated information more critically and better understand the appropriate boundaries of AI use in academic work.
However, this relationship is not automatic. Academic pressure, dependence on AI, institutional accountability, assessment design, and academic culture can influence whether students actually use AI responsibly.
AI Is Changing How Students Learn
The rapid development of generative AI has changed how university students search for information, develop ideas, write assignments, and complete academic work.
AI tools can support learning when they are used appropriately. Students may use them for brainstorming, language assistance, or developing ideas. The problem arises when AI-generated output replaces the student's own intellectual contribution.
The authors describe AI literacy as more than simply knowing how to operate AI tools. It includes understanding how AI works, evaluating its outputs, recognizing its limitations, and considering ethical consequences before using AI-generated content in academic work.
The study also emphasizes that responsible AI use requires students to maintain intellectual responsibility rather than allowing AI to become a substitute for their own thinking.
The Researchers Reviewed 22 Sources from 2021–2025
The researchers used a descriptive qualitative approach through a systematic literature review. They examined academic publications and policy documents addressing AI literacy, generative AI, academic dishonesty, plagiarism, detection systems, and academic integrity governance.
The literature was collected from five major academic databases: Scopus, ERIC, ScienceDirect, Google Scholar, and SINTA.
The search initially identified 87 sources. After screening titles and abstracts, 41 sources remained. A full-text review and quality assessment then produced a final sample of 22 sources for thematic synthesis.
The researchers compared evidence from Indonesia and Thailand to identify common patterns and differences in AI literacy, responsible AI use, and academic integrity.
AI Literacy Matters, but It Is Not the Only Solution
One of the study's central findings is that AI literacy is a necessary foundation, but it does not guarantee ethical behavior.
Students with strong knowledge of AI may still engage in academic misconduct when they face academic pressure, develop dependence on AI tools, or operate in institutions with weak accountability mechanisms.
In other words, knowing how to use AI does not automatically mean knowing when and how it should be used ethically.
The authors therefore argue that AI literacy needs to be developed alongside academic integrity education, institutional policies, appropriate assessment methods, and accountability systems. AI literacy should also become part of the curriculum rather than being limited to occasional workshops or awareness campaigns.
Indonesia and Thailand Take Different Approaches
The study identifies important differences in how Indonesia and Thailand address academic integrity in the age of AI.
Indonesia places greater emphasis on integrity education and detection technologies. Academic integrity education is viewed as an institutional responsibility, while plagiarism detection and other technical systems provide additional mechanisms for identifying potential violations.
Thailand places greater emphasis on governance, assessment security, and monitoring. Examination proctoring and identity authentication are among the mechanisms used to address vulnerabilities associated with remote and hybrid assessments. The Thai approach also incorporates moral and values-based factors as potential deterrents to academic misconduct.
According to the researchers, these approaches should not be viewed as competing models. Instead, they can complement each other. Indonesia could strengthen its governance and assessment security, while Thailand could further strengthen AI ethics education and literacy.
Assessment Design Needs to Change
The study highlights assessment design as an important but sometimes overlooked tool for protecting academic integrity.
Assignments that focus only on final answers can be more vulnerable to AI-assisted misconduct. By contrast, assessments that require students to demonstrate their reasoning, document the process of completing an assignment, explain their work orally, or defend their academic decisions can make misuse of AI more difficult.
This does not mean universities need to prohibit AI altogether. Instead, students need to learn how to use AI as a learning support tool while maintaining responsibility for their own intellectual work.
Future Teachers Also Need AI Ethics Training
The findings are particularly relevant to teacher education. Future teachers will not only use AI themselves but may also influence how younger generations understand and use the technology.
For this reason, teacher preparation programs should include responsible AI use, ethical reflection, and learning practices designed to protect academic integrity.
The researchers argue that developing these habits during teacher education could help establish responsible AI practices in future classrooms and educational institutions.
More broadly, Septiani and her colleagues recommend standardized AI literacy curricula, the integration of academic integrity education across disciplines, and multilayered safeguards combining education, technology, governance, and assessment reform.
They also encourage Indonesia and Thailand to cooperate in developing a joint AI literacy framework and conducting further cross-national research on academic integrity.
Author Profiles
The article was written by Sisca Septiani, Lisa Virdinarti Putra, Nur Intan Rochmawati, Wiwik Pudjaningsih, and Ridwan Ali from Universitas Ngudi Waluyo, Indonesia, together with Prattana Srisuk, Marlon Rael Astillero, and Nico Irawan from Thai Global Business Administration College, Thailand.
Sisca Septiani is listed as the corresponding author and is affiliated with Universitas Ngudi Waluyo. The source article does not provide the academic degrees or individual areas of expertise of each author, so those details are not added here to avoid unsupported information.
Research Source
The study delivers a clear message for universities entering an AI-driven era: students need more than the technical ability to use artificial intelligence. They also need the ability to evaluate, limit, and take responsibility for how they use it.
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