Ethical use of ChatGPT in education—Best practices to combat AI-induced plagiarism

Frontiers in Education, Journal Year: 2025, Volume and Issue: 9

Published: Jan. 9, 2025

The emergence of ChatGPT, a high-performance artificial intelligence language model developed by OpenAI, has generated both excitement and concern in academia (Li, 2024). Equipped with advanced natural processing techniques, ChatGPT is able to generate human-like text that provides coherent contextually relevant responses wide range queries. This unprecedented capability raised optimism as it could fundamentally change traditional practices academia, industry everyday life (Cambra-Fierro et al., 2024).The basic function "ask me anything" "I might have good answer" no longer just many fields. scientific knowledge disseminated journals already struggling the role such technology will play. Questions arise about whether be, can coauthored (Tang, Professors who create immediately face challenge assessing students presence technology. These are practical legitimate questions.While benefits terms increased student engagement, collaboration accessibility outcomes, also very serious academic integrity implications: at its core plagiarism. paper offers comprehensive strategies on how educators help mitigate these risks promoting ethical use fairness within AI tools.ChatGPT was truly disruptive, which should surprised one. It be seen technologies being adopted quickly from university labs; reached one million users first five days now over 180 (Duarte, kind rapid adoption demonstrates remarkable property generative AI: persists text.One main problems models like threats they pose, including black box algorithms, discrimination, biases, vulgarity, copyright infringement -plagiarism -and others, generation fake content or media (Sloan, Powis & Tan, Therefore, organisations need disciplined risk management approaches effectively address threats. Considering continuous evolution algorithms due rapidity data sources, review heterogeneity variability bias periodic assessments weighed against considerations (Schwartz 2022).The experience resulting lacked an obvious logical structure, contained speculative information, did not elaborate critical data, provide original contributions (Giuggioli Pellegrini 2023). Any article topic would conventional, lack logic facts, critically engaging. In addition, references generally incorrect; titles authors, well other publication details, misstated. Such inaccuracies require careful double-checking, especially professional contexts journalism software development.Inaccuracy, poor flow, factual inaccuracies, analysis originality AI-generated result current state (Yang, based deep learning trained using extensive datasets prior information may outdated low quality. Although improvements training quality improve performance AIs, clear technical level necessarily lead significant gains innovation (Dwivedi 2023).The recent applications text, film music production all indicate platforms best partners process, complementing rather than replacing human intelligence. case complex activities requiring creativity emotional intelligence, well-formulated request alone sufficient for produce markedly different outputs. Human oversight remain essential (Liu, Research, practice, urgent policy decisions era rapidly evolving researchers, practitioners, policymakers engage changes. Building strengths AI, while aware limitations making efforts them, foster environment tools used responsibly effectively.Integrating into without challenges. primary possibility Students get essays assignments, then submit their own work. undermines educational process devalues credentials. Another potential inequality. access complete assignments much less time possibly better, giving them unfair advantage do ChatGPT. further increase existing inequalities outcomes. On hand, difficult distinguish created AI. Because generates human-like, difficulty distinguishing "original" makes detect AI-assisted plagiarism.While this work focuses addressing plagiarism, hold great promise improving outcomes stimulating creativity. Through adaptive tutoring systems, personalized learning, immediate feedback facilitate deeper interaction course material. Furthermore, AI-driven creative allow experiment problem-solving thinking new ways, ultimately more dynamic engaging environment.The rise large models, education led institutions develop ways prevent misuse. aim protect adapting AI-enhanced environments. Different been introduced settings varying degrees success.This probably reason why facilities started establish policies when employ Many often tend explain emphasis proper citation attribution student's For example, some universities mention what tool throughout assignment, similar citing sources literature.A number implemented high-tech, AI-detecting plagiarism-checking programs. Indeed, services Turnitin year flagging submissions out character and/or contain unnatural patterns speech. designed AIassisted implemented, complicating misrepresent own.Another effective strategy design increasingly high part student, effective. personal reflective nature, those research questions specific local contexts, make harder fall back only. minimizes only chances misuse but fosters skills among students.Some adopting oral examinations wherein made present defend ideas, projects. face-to-face virtual exchanges permit instructor directly determine depth understanding exams, almost impossible because involves real-time response justification.In where group fostered, teams projects, raises noticeable obstacles fit smoothly inside final product. Group-based nature communication, coordination, team members, aspects imitate. Moreover, mechanisms peer evaluate colleagues, thus automatically increasing identification inconsistencies any tools.Empirical evidence supports importance evaluation reduce AIrelated Successful pilot programs highly regarded colleges incorporate tasks highlighted Moorhouse al (2023). limit individualized tailored students. Dempere (2023) favor technology-based ethics-based interventions, showing campaigns combination recognition greatly compliance. Taken together, studies show integrating awareness assessment strong foundation successful prevention AIenabled plagiarism.To challenges education, Cotton (2024) highlight dual highlighting associated prospect engagement. They call proactive institutional measures integration AIrecognition technologies, creation explicit tools. By implementing tactics, encourage Zeb higher pointing engagement related integrity. recommend implement policies, thinking, guide use. measures, harness minimizing misuse.Strategies taking account opinions suggestions:Technological Solutions• There various plagiarism detectors find copied content. If there search texts match possible flagged. Educators invest intelligence-generated through stylistic anomalies. • Use analytics track learner progress unexplained performance. include sudden, improvement writing style, sign AI-enabled testing methods modified reformulated previous responses. with, predict correct answers incorporating approaches.• Educating most combat education. exactly damage does built name institutions. achieved teaching materials, classroom discussions, communication consequences Include exercises learners discuss encountered, insights gained. teachers assess credibility students' understand processes. Peer incorporated, asked each other's submitted allows detected. Encourage projects pupils individual, products multimedia presentations senses. podcasts digital unlikely replicable AI.• Design linking experiences, curricula. types general addition written essay, communicate learned variety media, slide shows, audio recordings, films, portfolios. replicating alternative methods, versatile skills.• Setting guidelines essential. know context tools, i.e., texts. Requiring outline instructors identify early process. approach timely guidance, reducing likelihood resorting Regularly checking thorough reading check understanding, detection devices flag suspicious content.• Large broken down smaller structured key points, appropriate deadlines. ensures build up gradually, whole project Oral sure test originality; justify arguments even answers, sense scenario.To minimize prone Some extended misuse:Critical Thinking Problem-Solving Tasks• Tasks problem solving performed satisfactorily presentations, interactive individual skills. Designing open-ended conditions useful. having formulate independent thinking. Refine focus areas short, in-depth responses.• Demonstrate applications: apply theoretical practical, real-world problems. Case studies, simulations, project-based AI's ability limited. replicate real-life situations authentic service-learning internships, community-based research. cannot easily outsourced Develop role-playing simulations take designated roles characters. way elements simulate.• Create cohort events, problems, reflections. Individualizing applicability Providing follow-up actions feedback, material reduces reliance portfolio-based assessment, collects done time. Portfolios challenging simulate.Collaborative Peer-Based Learning• Group together product, ensuring input requires coordination replicate. Peer-assisted activities, tutor mentor classmates. reinforces explanation justification, provide.• Real-time proctored exams assessments. represents abilities. Conduct timed assessments, in-class online tests, format emphasizes think respond knowledge.• mixed forms assessment: work, demonstrations.Multimodal diverse skills, handle elements. Interactive vary performance, personalization Frequent, low-level monitor ongoing basis. irregularities last-minute AI.Although above-mentioned tactic sound method curbing application difficulties.Some universities, limited resources, costs sophisticated prohibitive. effectiveness depends frequent updates keep pace capabilities, operational costs.Many solutions, testing, collection amounts data. security privacy, sensitive required. scope collected examined fact schools organizations must ensure compliance protection laws.Authentic mistaken AI-based certain distinctive style. false claims undermine confidence manual investigation teachers, time-and resource-intensive process.Teachers devote lot energy pedagogical policy-based dividing ones. support successfully integrate changes daily routines.A heavy techniques divert attention raising awareness. While resources helpful, remains developing long-lasting moral behavior.Since constantly changing, checked.Institutions regularly adjust evolves, necessitating regulatory teacher training.Administrative faculty burdened change.These discussed coincided globally begun start. next section point similarities between recommendations relative perhaps form prevention. Nothing works better incorrect usage. Institutions really involved culture integrity, taught future careers affected dishonestly passed practices. workshops modules teach ethics mind-reminding attribution.These adaptive, updated performance-real-time quizzes work-are important deterrents growing Adaptive tests responses, quite answers. Continuous approaches-including low-stakes assignments-help students, underlining discrepancies indicative As position follow iterations become vulnerable submissions.Multimodal becoming preferred fighter dishonesty demonstrations raise expectation demonstrate wider assessments-where collect body semester-offer panoramic view development probable spot style.Already, Trialling type Early suggests accuracy continuously systems perception. long-term impacts.Researchers, practitioners makers explore ever-changing technologies. moves direction providing environment.

Language: Английский

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Human-Centred Design Meets AI-Driven Algorithms: Comparative Analysis of Political Campaign Branding in the Harris–Trump Presidential Campaigns

Informatics, Journal Year: 2025, Volume and Issue: 12(1), P. 30 - 30

Published: March 18, 2025

This study compared the efficacy of AI neuroscience tools versus traditional design methods in enhancing viewer engagement with political campaign materials from Harris–Trump presidential campaigns. Utilising a mixed-methods approach, we integrated quantitative analysis employing AI’s eye-tracking consumer behaviour metrics (Predict, trained on 180,000 screenings) an AI-LLM neuroscience-based marketing assistant (CoPilot), 67,429 areas interest (AOIs). The original flyer, Al Jazeera article, served as baseline. Professional graphic designers created three redesigned versions, and one was done using recommendations CoPilot. Metrics including total attention, engagement, start end percentage seen were evaluated across 13–14 (AOIs) for each design. Results indicated that human-enhanced Design 1 achieved superior overall performance multiple metrics. While AI-enhanced 3 demonstrated strengths optimising specific AOIs, it did not consistently outperform human-touched designs, particularly text-heavy areas. underscores complex interplay between algorithms human-centred branding, offering valuable insights future research neuromarketing communication strategies. Python, Pandas, Matplotlib, Seaborn, Spearman correlation, Kruskal–Wallis H-test employed data visualisation.

Language: Английский

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Impact of Artificial Intelligence on SEO and Online Visibility

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 229 - 258

Published: April 18, 2025

This chapter examines the growing impact of Artificial Intelligence (AI) on Search Engine Optimization (SEO) in experience-driven economy. AI, defined as a set systems that simulate human cognitive functions, equips companies with powerful tools to analyze complex data and automate processes. As SEO remains crucial for capturing user attention search engines, it must continually adapt increasingly sophisticated algorithms. AI is transforming by enabling in-depth analysis behavior delivering personalized results. Tools such Google RankBrain ChatGPT are driving this evolution while also introducing new challenges. research analyzes fundamental principles its key components—including machine learning, deep natural language processing—and their distinct roles enhancement. Additionally, applications, benefits, challenges AI-driven evaluated, future trends could redefine relationship between an digital world examined.

Language: Английский

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