ChatGPT vs Teachers vs Students: Large-Scale Analysis of Generative AI Discourse in Education Communities on Reddit

• URL: http://arxiv.org/abs/2605.17712v1
• Date: Mon, 18 May 2026 00:26:33 GMT
• Title: ChatGPT vs Teachers vs Students: Large-Scale Analysis of Generative AI Discourse in Education Communities on Reddit
• Abstract summary: We analyse 270k AI-related Reddit posts and comments from 26 education-related subreddits.<n>Discourse evolves from an early detection-and-evasion arms race into a sustained enforcement regime.<n>Students initiate 68% of mixed threads, but faculty produce most cross-role replies.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generative Artificial Intelligence (GenAI) has prompted significant discussion in education, yet large-scale empirical evidence on how students and teachers perceive and navigate this shift remains limited. We analyse 270k AI-related Reddit posts and comments from 26 education-related subreddits spanning higher education, K-12 teaching, and professional training between November 2022 and April 2026. Topic modelling reveals seventeen themes covering academic integrity, teaching & pedagogy, career anxiety, policy, and niche professional contexts. Discourse evolves from an early detection-and-evasion arms race into a sustained enforcement regime that constructive integration only begins to challenge in mid-2024. Stakeholder communities differ sharply: K-12 teachers foreground cognitive dependency, academics focus on AI detection and deliberation, and professional-programme students concentrate on career anxiety. Sentiment correlates strongly negatively with engagement, showing adversarial enforcement themes mobilise communities far more than constructive integration discourse. Examining where faculty and students meet, we find 17% of threads are cross-role, and one third of such contact occurs in the adversarial themes AI Detection and Misconduct Enforcement. Students initiate 68% of mixed threads, but faculty produce most cross-role replies. Mixed threads contain 2-3 times more records and last 2-4 times longer than same-role threads, making adversarial integrity disputes the center of sustained faculty-student contact. We discuss implications for governance, pedagogical design, and cross-role contact design. The code and data is available at https://github.com/tugrulz/genai-edu

Related papers

• Exploring K-12 Teachers' Perceptions of Students' Relationships with AI Companions: Boundaries, Intervention Strategies, and Design Implications [14.751647093722399]
  Schools face growing expectations to teach AI literacy, yet existing frameworks treat AI as a tool rather than a relationship.<n>We conducted scenario-based interviews with 33 US K-12 teachers.<n>Teachers welcomed academic companions but worried that intimate companions remove the developmental friction through which students learn to sustain human relationships.
  arXiv  Detail & Related papers  (2026-09-11T19:49:06Z)
• Group-Differentiated Discourse on Generative AI in High School Education: A Case Study of Reddit Communities [12.603101932945995]
  We study how different Reddit communities discuss generative AI in high school education.<n>Using 3,789 posts from five education-related subreddits, we compare student, teacher, and mixed communities.<n>Teachers are more likely to articulate explicit pedagogical trade-offs, simultaneously framing AI as both beneficial and harmful for learning.<n>Students more often discuss AI tactically in relation to accusations, grades, and enforcement.
  arXiv  Detail & Related papers  (2026-03-26T03:06:21Z)
• ChatGPT-5 in Secondary Education: A Mixed-Methods Analysis of Student Attitudes, AI Anxiety, and Hallucination-Aware Use [0.0]
  Students used ChatGPT-5 during an eight-hour intervention in the course "Technology"<n>Students engaged in information seeking, CV generation, document and video summarization, image generation, quiz creation, and age-appropriate explanations.<n>After encountering hallucinations, many students reported restricting AI use to domains where they already possessed knowledge.
  arXiv  Detail & Related papers  (2025-11-30T19:28:48Z)
• EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus [59.693733170193944]
  We present EduDial, a comprehensive multi-turn teacher-student dialogue dataset.<n>EduDial covers 345 core knowledge points and consists of 34,250 dialogue sessions generated through interactions between teacher and student agents.
  arXiv  Detail & Related papers  (2025-10-14T18:18:43Z)
• Unpacking Generative AI in Education: Computational Modeling of Teacher and Student Perspectives in Social Media Discourse [0.5203732344753156]
  This study presents one of the most comprehensive analyses to date of stakeholder discourse dynamics on GAI in education using social media data.<n>Our dataset includes 1,199 Reddit posts and 13,959 corresponding top-level comments.<n>Our findings suggest a need for clearer institutional policies, more transparent GAI integration practices, and support mechanisms for both educators and students.
  arXiv  Detail & Related papers  (2025-06-19T15:50:08Z)
• "All Roads Lead to ChatGPT": How Generative AI is Eroding Social Interactions and Student Learning Communities [0.4188114563181615]
  We investigate the potential impacts of generative AI on social interactions, peer learning, and classroom dynamics.<n>Our findings suggest that help-seeking requests are now often mediated by generative AI.<n>Students reported feeling increasingly isolated and demotivated as the social support systems they rely on begin to break.
  arXiv  Detail & Related papers  (2025-04-14T00:40:58Z)
• Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment [75.59538732476346]
  We focus on the problem of generating such gap-focused questions (GFQs) automatically. We define the task, highlight key desired aspects of a good GFQ, and propose a model that satisfies these.
  arXiv  Detail & Related papers  (2023-07-06T22:21:42Z)
• MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems [74.73881579517055]
  We propose a framework to generate such dialogues by pairing human teachers with a Large Language Model prompted to represent common student errors. We describe how we use this framework to collect MathDial, a dataset of 3k one-to-one teacher-student tutoring dialogues.
  arXiv  Detail & Related papers  (2023-05-23T21:44:56Z)
• Exploring User Perspectives on ChatGPT: Applications, Perceptions, and Implications for AI-Integrated Education [40.38809129759498]
  ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training. On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation. On the other hand, there is a degree of apprehension among concerned users.
  arXiv  Detail & Related papers  (2023-05-22T15:13:14Z)
• Disadvantaged students increase their academic performance through collective intelligence exposure in emergency remote learning due to COVID 19 [105.54048699217668]
  During the COVID-19 crisis, educational institutions worldwide shifted from face-to-face instruction to emergency remote teaching (ERT) modalities. We analyzed data on 7,528 undergraduate students and found that cooperative and consensus dynamics among students in discussion forums positively affect their final GPA. Using natural language processing, we show that first-year students with low academic performance during high school are exposed to more content-intensive posts in discussion forums.
  arXiv  Detail & Related papers  (2022-03-10T20:23:38Z)
• Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI) Curriculum [58.86139968005518]
  The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
  arXiv  Detail & Related papers  (2021-01-19T11:26:19Z)
• Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms [50.19997675066203]
  We build an end-to-end neural framework that automatically detects questions from teachers' audio recordings. By incorporating multi-task learning techniques, we are able to strengthen the understanding of semantic relations among different types of questions.
  arXiv  Detail & Related papers  (2020-05-16T02:17:04Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.