{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T16:21:06Z","timestamp":1783441266097,"version":"3.54.6"},"reference-count":42,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T00:00:00Z","timestamp":1782086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>This study investigates how AI-assisted plagiarism changes dishonest academic behavior in a socially interactive learning environment under different educational conditions. To this end, this study develops a scenario-based simulation to examine how AI-assisted plagiarism influences dishonest academic behavior in socially interactive learning environments. The model represents students as autonomous agents embedded in local peer networks who adapt their weekly behavior under academic pressure, institutional intervention, and available cheating options. Two behavioral scenarios are considered: a conventional plagiarism environment, in which agents choose between honest submission and direct copying, and an AI-augmented environment, in which AI-assisted plagiarism is introduced as an additional dishonest strategy. Intervention is modeled through environmental and institutional conditions, specifically detection probability and sanction severity, rather than through direct internal reward manipulation. Q-learning is used as a simplified adaptive mechanism for repeated agent choice. Experimental results show that the possibility of producing and assessing a simulation to see the availability of AI-assisted plagiarism substantially changes the behavioral composition of misconduct by increasing total dishonest behavior and shifting a large share of it toward the AI-assisted category. In the simulation, active intervention reduces dishonest behavior overall but does not eliminate AI-assisted plagiarism as the dominant dishonest strategy in the AI-augmented environment. These observations in the simulation suggest that academic misconduct in the AI era should be understood not only as a problem of deterrence but also as a problem of behavioral adaptation under changing technological and institutional conditions. To support the realism assessment of the simulation design, the study also conducts a structured qualitative plausibility review using multiple large language models under a shared prompt. Across these reviews, the model is judged to be acceptable as a first-stage stylized baseline, while important limitations are identified in agent heterogeneity, social influence depth, and the use of Q-learning as a simplified adaptive heuristic to reproduce the behaviors of actors in there.<\/jats:p>","DOI":"10.3390\/systems14060721","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:02:56Z","timestamp":1783436576000},"page":"721","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling AI-Assisted Plagiarism in Academic Social Environments Using Qualitative Plausibility Assessment Supports of the Simulation by Large Language Models"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8861-3113","authenticated-orcid":false,"given":"Ihsan","family":"Ibrahim","sequence":"first","affiliation":[{"name":"Graduate School of Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan"},{"name":"Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1834-451X","authenticated-orcid":false,"given":"Anak Agung Putri","family":"Ratna","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5851-1984","authenticated-orcid":false,"given":"Prima Dewi","family":"Purnamasari","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7724-8782","authenticated-orcid":false,"given":"Naoki","family":"Fukuta","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Academic Institute, Shizuoka University, Hamamatsu 432-8011, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1515\/orga-2017-0002","article-title":"Reasons for Plagiarism in Higher Education","volume":"50","author":"Urh","year":"2017","journal-title":"Organizacija"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"94","DOI":"10.14429\/djlit.39.2.13622","article-title":"Plagiarism and Academic Misconduct: A Systematic Review","volume":"39","author":"Awasthi","year":"2019","journal-title":"DESIDOC J. Libr. Inf. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s40979-019-0044-2","article-title":"Understanding Plagiarism in Indonesia from the Lens of Plagiarism Policy: Lessons for Universities","volume":"15","author":"Akbar","year":"2019","journal-title":"Int. J. Educ. Integr."},{"key":"ref_4","first-page":"99","article-title":"Ten Principles of Academic Integrity","volume":"24","author":"McCabe","year":"1997","journal-title":"J. Coll. Univ. Law"},{"key":"ref_5","unstructured":"International Center for Academic Integrity (2025, June 22). Facts and Statistics. Available online: https:\/\/academicintegrity.org\/aws\/ICAI\/pt\/sp\/facts."},{"key":"ref_6","unstructured":"United Nations (2026, March 31). Goal 4: Quality Education. Available online: https:\/\/www.un.org\/development\/desa\/dpad\/sustainable-development-goal\/goal-4-quality-education\/."},{"key":"ref_7","unstructured":"Ibrahim, I., Ratna, A.A.P., Purnamasari, P.D., and Fukuta, N. (2025, January 21\u201323). Preliminary Implementation of Multi-Agent Based Plagiarism Behavior Modeling on Education Environment. Proceedings of the 6th International Conference on Nano Electronics Research and Education (ICNERE 2025), Hamamatsu, Japan. Poster presentation."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kandel, A., Ibrahim, I., and Fukuta, N. (2022, January 2\u20138). An Analysis of Educational Cloud Platforms using Multi-agent Learning. Proceedings of the 2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI), Kanazawa, Japan.","DOI":"10.1109\/IIAIAAI55812.2022.00053"},{"key":"ref_9","unstructured":"UNESCO, Miao, F., and Holmes, W. (2023). Guidance for Generative AI in Education and Research, UNESCO."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s41239-024-00453-6","article-title":"Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives","volume":"21","author":"Yusuf","year":"2024","journal-title":"Int. J. Educ. Technol. High. Educ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1111\/j.1475-682X.2004.00088.x","article-title":"Predicting Academic Misconduct: A Comparative Test of Four Sociological Explanations","volume":"74","author":"Vowell","year":"2004","journal-title":"Sociol. Inq."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1080\/01973530903539895","article-title":"Predicting Academic Misconduct Intentions and Behavior Using the Theory of Planned Behavior and Personality","volume":"32","author":"Stone","year":"2010","journal-title":"Basic Appl. Soc. Psychol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Bretag, T. (2016). Contract Cheating: The Outsourcing of Assessed Student Work. Handbook of Academic Integrity, Springer.","DOI":"10.1007\/978-981-287-098-8"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Alves, M., Martinho, D., Marc\u00e3o, R., and Sobreiro, P. (2026). Generative AI Adoption in B2B Firms: Ethical Governance, Innovation Capabilities, and Long-Term Competitive Performance. Systems, 14.","DOI":"10.3390\/systems14040410"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/EMR.2025.3534034","article-title":"Strategic Integration of Generative AI in Organizational Settings: Applications, Challenges, and Adoption Requirements","volume":"53","year":"2025","journal-title":"IEEE Eng. Manag. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yan, L., Wang, H., Xie, Z., Chiu, D.K.W., Choi, S.P.M., Ho, K.K.W., and Tian, R. (2026). The Impact of Artificial Intelligence Systems and Tools on Education: Comparative Social Media Analytics of Computing Versus Business Students. Systems, 14.","DOI":"10.3390\/systems14040451"},{"key":"ref_17","first-page":"1","article-title":"Academic Plagiarism Detection: A Systematic Literature Review","volume":"52","author":"Meuschke","year":"2019","journal-title":"ACM Comput. Surv."},{"key":"ref_18","first-page":"2131","article-title":"Plagiarism detection in academic writing: A review of software applications and detection methods","volume":"12","author":"Alzahrani","year":"2012","journal-title":"J. Appl. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Epstein, J.M., and Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up, Brookings Institution Press and MIT Press.","DOI":"10.7551\/mitpress\/3374.001.0001"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1146\/annurev.soc.28.110601.141117","article-title":"From factors to actors: Computational sociology and agent-based modeling","volume":"28","author":"Macy","year":"2002","journal-title":"Annu. Rev. Sociol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1103\/RevModPhys.81.591","article-title":"Statistical physics of social dynamics","volume":"81","author":"Castellano","year":"2009","journal-title":"Rev. Mod. Phys."},{"key":"ref_22","unstructured":"Sayama, H. (2015). Introduction to the Modeling and Analysis of Complex Systems, Open SUNY Textbooks."},{"key":"ref_23","unstructured":"Sutton, R.S., and Barto, A.G. (2018). Reinforcement Learning: An Introduction, MIT Press."},{"key":"ref_24","unstructured":"Watkins, C.J.C.H. (1989). Learning from Delayed Rewards. [Ph.D. Thesis, King\u2019s College]."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Canese, L., Cardarilli, G.C., Di Nunzio, L., Fazzolari, R., Giardino, D., Re, M., and Spano, S. (2021). Multi-Agent Reinforcement Learning: A Review of Challenges and Applications. Appl. Sci., 11.","DOI":"10.3390\/app11114948"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1007\/s40979-025-00199-2","article-title":"Exploring the nexus of academic integrity and artificial intelligence in higher education: A bibliometric analysis","volume":"21","author":"Avello","year":"2025","journal-title":"Int. J. Educ. Integr."},{"key":"ref_27","first-page":"e635","article-title":"Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond","volume":"20","author":"Perkins","year":"2023","journal-title":"J. Univ. Teach. Learn. Pract."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Katalinic, A., Slavuj, V., and Jaksic, D. (2026). Artificial Intelligence in Online Education: A Systematic Review of Its Impact on Learner Engagement and Satisfaction. Educ. Sci., 16.","DOI":"10.3390\/educsci16030389"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"102274","DOI":"10.1016\/j.lindif.2023.102274","article-title":"ChatGPT for good? On opportunities and challenges of large language models for education","volume":"103","author":"Kasneci","year":"2023","journal-title":"Learn. Individ. Differ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1080\/14703297.2023.2190148","article-title":"Chatting and cheating: Ensuring academic integrity in the era of ChatGPT","volume":"61","author":"Cotton","year":"2024","journal-title":"Innov. Educ. Teach. Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1007\/s10805-025-09639-7","article-title":"Governing Academic Integrity: Ensuring the Authenticity of Higher Thinking in the Era of Generative Artificial Intelligence","volume":"23","author":"Coates","year":"2025","journal-title":"J. Acad. Ethics"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s40979-024-00149-4","article-title":"Student perspectives on the use of generative artificial intelligence technologies in higher education","volume":"20","author":"Johnston","year":"2024","journal-title":"Int. J. Educ. Integr."},{"key":"ref_33","unstructured":"Hanneman, R.A., and Riddle, M. (2005). Introduction to Social Network Methods, University of California. Available online: http:\/\/faculty.ucr.edu\/~hanneman\/nettext\/."},{"key":"ref_34","first-page":"1113","article-title":"A review of tipping models and their application to influence spread in networks","volume":"3","author":"Shakarian","year":"2013","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_35","first-page":"7991","article-title":"Emergent Social Learning via Multi-agent Reinforcement Learning","volume":"Volume 139","author":"Meila","year":"2021","journal-title":"Proceedings of the 38th International Conference on Machine Learning"},{"key":"ref_36","unstructured":"Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P.S., and Wortman Vaughan, J. (2021). Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization In Advances in Neural Information Processing Systems, Curran Associates."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"106858","DOI":"10.1016\/j.neunet.2024.106858","article-title":"Coordinating Multi-Agent Reinforcement Learning via Dual Collaborative Constraints","volume":"182","author":"Li","year":"2025","journal-title":"Neural Netw."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Sugiyama, T., and Fukuta, N. (2018, January 8\u201313). A QS-learning-Based Patrol Behavior Learning for Avoiding Illegal Disposals. Proceedings of the 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI), Yonago, Japan.","DOI":"10.1109\/IIAI-AAI.2018.00122"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Rosenfeld, A., Taylor, M.E., and Kraus, S. (2017, January 19\u201325). Leveraging Human Knowledge in Tabular Reinforcement Learning: A Study of Human Subjects. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, Melbourne, Australia.","DOI":"10.24963\/ijcai.2017\/534"},{"key":"ref_40","first-page":"1297","article-title":"FHIR-AgentBench: Benchmarking LLM Agents for Realistic Interoperable EHR Question Answering","volume":"Volume 297","author":"Argaw","year":"2026","journal-title":"Proceedings of the Fifth Machine Learning for Health Symposium"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Michelon, F., Zhou, Y., and Morstyn, T. (2025). Large Language Model Interface for Home Energy Management Systems. Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, Association for Computing Machinery. E-Energy \u201925.","DOI":"10.1145\/3679240.3734586"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Tsuchiya, Y., and Baba, Y. (2026). More Isn\u2019t Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advice. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery. CHI \u201926.","DOI":"10.1145\/3772318.3791648"}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/14\/6\/721\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:27:08Z","timestamp":1783438028000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/14\/6\/721"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,22]]},"references-count":42,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["systems14060721"],"URL":"https:\/\/doi.org\/10.3390\/systems14060721","relation":{},"ISSN":["2079-8954"],"issn-type":[{"value":"2079-8954","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,22]]}}}