# Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education arXiv: https://arxiv.org/abs/2305.00290 ยท HTML: https://mlsanity.com/paper/2305.00290/ ## Key facts - Cited by 41 papers in the map (data through 14 Oct 2026). - Builds on 2 of its 56 references that are in the map. - First posted on arXiv 29 Apr 2023. ## Builds on (most cited first, 2 of 2) - [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022) - [What is in a Text-to-Image Prompt: The Potential of Stable Diffusion in Visual Arts Education](https://mlsanity.com/paper/2301.01902/) (2023) ## Built on by (most cited first, 30 of 41) - [Generative AI Literacy: Twelve Defining Competencies](https://mlsanity.com/paper/2412.12107/) (2024) - [The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?](https://mlsanity.com/paper/2305.02878/) (2023) - [The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment](https://mlsanity.com/paper/2312.07086/) (2023) - [Detecting LLM-Generated Text with Performance Guarantees](https://mlsanity.com/paper/2601.06586/) (2026) - [Constructing Dreams using Generative AI](https://mlsanity.com/paper/2305.12013/) (2023) - [Learn-to-Distance: Distance Learning for Detecting LLM-Generated Text](https://mlsanity.com/paper/2601.21895/) (2026) - [Generative AI and Teachers -- For Us or Against Us? A Case Study](https://mlsanity.com/paper/2404.03486/) (2024) - [The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment- A Preprint](https://mlsanity.com/paper/2403.14692/) (2024) - [CoTAL: Human-in-the-Loop Prompt Engineering for Generalizable Formative Assessment Scoring and Feedback](https://mlsanity.com/paper/2504.02323/) (2025) - [Is AI Changing the Rules of Academic Misconduct? An In-depth Look at Students' Perceptions of 'AI-giarism'](https://mlsanity.com/paper/2306.03358/) (2023) - [How Do Students Interact with an LLM-powered Virtual Teaching Assistant in Different Educational Settings?](https://mlsanity.com/paper/2407.17429/) (2024) - [Deconstructing Student Perceptions of Generative AI (GenAI) through an Expectancy Value Theory (EVT)-based Instrument](https://mlsanity.com/paper/2305.01186/) (2023) - [ChatGPT in Data Visualization Education: A Student Perspective](https://mlsanity.com/paper/2405.00748/) (2024) - [AI Rivalry as a Craft: How Resisting and Embracing Generative AI Reshape Writing Professions](https://mlsanity.com/paper/2503.09901/) (2025) - [BoilerTAI: A Platform for Enhancing Instruction Using Generative AI in Educational Forums](https://mlsanity.com/paper/2409.13196/) (2024) - [Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization](https://mlsanity.com/paper/2410.12700/) (2024) - [What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI](https://mlsanity.com/paper/2602.20547/) (2026) - ["ChatGPT, a Friend or Foe for Education?" Analyzing the User's Perspectives on the Latest AI Chatbot Via Reddit](https://mlsanity.com/paper/2311.06264/) (2023) - [Ethical Implications of ChatGPT in Higher Education: A Scoping Review](https://mlsanity.com/paper/2311.14378/) (2023) - [Students' Perceived Roles, Opportunities, and Challenges of a Generative AI-powered Teachable Agent: A Case of Middle School Math Class](https://mlsanity.com/paper/2409.06721/) (2024) - [A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment](https://mlsanity.com/paper/2507.11543/) (2025) - [Beyond Automation: Socratic AI, Epistemic Agency, and the Implications of the Emergence of Orchestrated Multi-Agent Learning Architectures](https://mlsanity.com/paper/2508.05116/) (2025) - [Pilot Study on Generative AI and Critical Thinking in Higher Education Classrooms](https://mlsanity.com/paper/2509.00167/) (2025) - [Understanding Critical Thinking in Generative Artificial Intelligence Use: Development, Validation, and Correlates of the Critical Thinking in AI Use Scale](https://mlsanity.com/paper/2512.12413/) (2025) - [A Comparative Study of Student Perspectives on Technical Writing Feedback Quality: Evaluating LLMs, SLMs, and Humans in Computer Science Topics](https://mlsanity.com/paper/2601.11541/) (2025) - [Towards Gaze-Informed AI Disclosure Interfaces: Eye-Tracking Attentional and Cognitive Load While Reading AI-Assisted News](https://mlsanity.com/paper/2605.14999/) (2026) - [The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes](https://mlsanity.com/paper/2408.01075/) (2024) - [AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities](https://mlsanity.com/paper/2409.02017/) (2024) - [Elementary School Students' and Teachers' Perceptions Towards Creative Mathematical Writing with Generative AI](https://mlsanity.com/paper/2409.06723/) (2024) - [Ensemble ToT of LLMs and Its Application to Automatic Grading System for Supporting Self-Learning](https://mlsanity.com/paper/2502.16399/) (2025) ## Abstract (arXiv) This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education, focusing on familiarity, their willingness to engage, potential benefits and challenges, and effective integration. A survey of 399 undergraduate and postgraduate students from various disciplines in Hong Kong revealed a generally positive attitude towards GenAI in teaching and learning. Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities. However, concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed. According to John Biggs' 3P model, student perceptions significantly influence learning approaches and outcomes. By understanding students' perceptions, educators and policymakers can tailor GenAI technologies to address needs and concerns while promoting effective learning outcomes. Insights from this study can inform policy development around the integration of GenAI technologies into higher education. By understanding students' perceptions and addressing their concerns, policymakers can create well-informed guidelines and strategies for the responsible and effective implementation of GenAI tools, ultimately enhancing teaching and learning experiences in higher education.