Difference between revisions of "AI in education"

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=AI in Education=
 
=AI in Education=
 +
==Survey/study of==
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* 2023-08: [https://www.nature.com/articles/s41598-023-38964-3 Perception, performance, and detectability of conversational artificial intelligence across 32 university courses]
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* 2023-10: [https://www.bbc.com/worklife/article/20231017-the-employees-secretly-using-ai-at-work Employees] secretly using AI at work.
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* 2023-10: [https://www.insidehighered.com/news/tech-innovation/artificial-intelligence/2023/10/31/most-students-outrunning-faculty-ai-use?utm_source=Inside+Higher+Ed&utm_campaign=23419446b9-DNU_2021_COPY_02&utm_medium=email&utm_term=0_1fcbc04421-23419446b9-236889242&mc_cid=23419446b9&mc_eid=dae49d931a Survey] shows students using AI more than professors.
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* 2023-11: [https://www.nature.com/articles/d41586-023-03507-3 ChatGPT has entered the classroom: how LLMs could transform education]
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==AI improves learning/education==
 
==AI improves learning/education==
 
*  Mollick, Ethan R. and Mollick, Lilach and Bach, Natalie and Ciccarelli, LJ and Przystanski, Ben and Ravipinto, Daniel, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4871171 AI Agents and Education: Simulated Practice at Scale] (June 17, 2024). The Wharton School Research Paper. [http://dx.doi.org/10.2139/ssrn.4871171 doi: 10.2139/ssrn.4871171]
 
*  Mollick, Ethan R. and Mollick, Lilach and Bach, Natalie and Ciccarelli, LJ and Przystanski, Ben and Ravipinto, Daniel, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4871171 AI Agents and Education: Simulated Practice at Scale] (June 17, 2024). The Wharton School Research Paper. [http://dx.doi.org/10.2139/ssrn.4871171 doi: 10.2139/ssrn.4871171]
 
** Can enable personalized education.
 
** Can enable personalized education.
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* [https://arxiv.org/abs/2306.17156 Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors]
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** GPT4 can out-perform human tutors.
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*  Keppler, Samantha and Sinchaisri, Wichinpong and Snyder, Clare, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4924786 Backwards Planning with Generative AI: Case Study Evidence from US K12 Teachers] (August 13, 2024). [http://dx.doi.org/10.2139/ssrn.4924786 doi: 10.2139/ssrn.4924786]
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** Teachers benefit from using AI as a co-pilot to aid in tasks (planning, how to teach topic, explore ideas).
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** There is smaller utility in using AI purely as a text-generator (to make quizzes, workbooks, etc.).
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* [https://arxiv.org/abs/2402.09809 Effective and Scalable Math Support: Evidence on the Impact of an AI- Tutor on Math Achievement in Ghana]
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* [https://doi.org/10.21203/rs.3.rs-4243877/v1 AI Tutoring Outperforms Active Learning]
  
 
==AI harms learning==
 
==AI harms learning==
−
* [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study] ** Current grading systems cannot detect AI.
+
* [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study]
 +
** Current grading systems cannot detect AI.
 
*  Bastani, Hamsa and Bastani, Osbert and Sungu, Alp and Ge, Haosen and Kabakcı, Özge and Mariman, Rei, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895486 Generative AI Can Harm Learning] (July 15, 2024). The Wharton School Research Paper.[http://dx.doi.org/10.2139/ssrn.4895486 doi: 10.2139/ssrn.4895486]
 
*  Bastani, Hamsa and Bastani, Osbert and Sungu, Alp and Ge, Haosen and Kabakcı, Özge and Mariman, Rei, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895486 Generative AI Can Harm Learning] (July 15, 2024). The Wharton School Research Paper.[http://dx.doi.org/10.2139/ssrn.4895486 doi: 10.2139/ssrn.4895486]
 
** Access to ChatGPT harmed math education outcomes.
 
** Access to ChatGPT harmed math education outcomes.
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* 2024-09: [https://arxiv.org/abs/2409.09047 AI Meets the Classroom: When Does ChatGPT Harm Learning?]
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==Software/systems==
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* [https://devpost.com/software/gptutor GPTutor] ([https://github.com/mynamegabe/GPTutor code])
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* [https://arxiv.org/abs/2308.02773 EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education]
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* [https://eurekalabs.ai/ Eureka Labs] (founded by [https://en.wikipedia.org/wiki/Andrej_Karpathy Andrej Karpathy]) aims to create AI-driven courses (first course is [https://github.com/karpathy/LLM101n Intro to LLMs])
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===Individual tools===
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* Chatbot (OpenAI [https://chatgpt.com/ ChatGPT], Anthropic [https://www.anthropic.com/claude Claude], Google [https://gemini.google.com/app Gemini])
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* [https://notebooklm.google.com/ NotebookLM]: Enables one to "chat with documents".
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* Google [https://learning.google.com/experiments/learn-about/signup Learn About]
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==AI for grading==
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* [https://dl.acm.org/doi/10.1145/3657604.3664693 Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability To Mark Short Answer Questions in K-12 Education] ([https://arxiv.org/abs/2405.02985 preprint])
  
 +
==Detection==
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* [https://www.sciencedirect.com/science/article/pii/S2666920X24000109 Do teachers spot AI? Evaluating the detectability of AI-generated texts among student essays]
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** GenAI can simulate student writing in a way that teachers cannot detect.
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** AI essays are assessed more positively than student-written.
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** Teachers are overconfident in their source identification.
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** Both novice and experienced teachers could not identify texts generated by ChatGPT vs. students
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===AI Text Detectors Don't Work===
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* 2024-05: [https://arxiv.org/abs/2405.07940 RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors]
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* 2024-06: [https://arxiv.org/abs/2306.15666 Testing of Detection Tools for AI-Generated Text]
  
 
=AI/human=
 
=AI/human=
 
==AI out-performs humans==
 
==AI out-performs humans==
 
===Tests===
 
===Tests===
−
* [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study] ** AI scores higher than median students.
+
* 2023-07: [https://arxiv.org/abs/2307.10635 SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models]
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* 2024-06: [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study]  
 +
** AI scores higher than median students.
  
 
===Creativity===
 
===Creativity===
−
* TBD
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* 2023-09: [https://www.nature.com/articles/s41598-023-40858-3 Best humans still outperform artificial intelligence in a creative divergent thinking task]
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** Best humans out-perform AI at creativity. (By implication, median humans may not.)
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* 2024-02: [https://www.nature.com/articles/s41598-024-53303-w The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks]
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* 2024-02: Felin, Teppo and Holweg, Matthias, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4737265 Theory Is All You Need: AI, Human Cognition, and Causal Reasoning] (February 24, 2024). [http://dx.doi.org/10.2139/ssrn.4737265 doi: 10.2139/ssrn.4737265]
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** Argues that human "theory-based" creativity is better than AI "data-based".
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* 2024-07: [https://arxiv.org/abs/2407.01119 Pron vs Prompt: Can Large Language Models already Challenge a World-Class Fiction Author at Creative Text Writing?]
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** Top human (professional author) out-performs GPT4.
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* 2024-09: [https://arxiv.org/abs/2409.04109 Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers]
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** LLMs can be creative
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* 2024-09: [https://docs.iza.org/dp17302.pdf Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments]
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===Various===
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* 2024-11: [https://doi.org/10.1038/s41598-024-76900-1 AI-generated poetry is indistinguishable from human-written poetry and is rated more favorably]
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===Professions===
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* 2024-03: [https://www.medrxiv.org/content/10.1101/2024.03.12.24303785v1 Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study]
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** GPT4 improves medical practitioner work; surprisingly, GPT4 alone scored better than a human with GPT4 as aid (on selected tasks).
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* 2024-10: [https://doi.org/10.1001/jamanetworkopen.2024.38535 Perspectives on Artificial Intelligence–Generated Responses to Patient Messages]
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* [https://agi.safe.ai/submit Humanity's Last Exam]
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** [https://x.com/alexandr_wang/status/1835738937719140440 Effort to build] a dataset of challenging (but resolvable) questions in specific domain areas, to act as a benchmark to test whether AIs are improving in these challenging topics.
  
 
==AI improves human work==
 
==AI improves human work==
−
* TBD
+
* 2023-07: [https://www.science.org/doi/10.1126/science.adh2586 Experimental evidence on the productivity effects of generative artificial intelligence]
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* 2023-09:  Dell'Acqua, Fabrizio and McFowland III, Edward and Mollick, Ethan R. and Lifshitz-Assaf, Hila and Kellogg, Katherine and Rajendran, Saran and Krayer, Lisa and Candelon, François and Lakhani, Karim R., [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4573321 Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality] (September 15, 2023). Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-013, The Wharton School Research Paper [http://dx.doi.org/10.2139/ssrn.4573321 doi: 10.2139/ssrn.4573321]
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* 2023-11: [https://www.nber.org/papers/w31161 Generative AI at Work] (National Bureau of Economic Research)
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* 2023-12: [https://osf.io/hdjpk The Uneven Impact of Generative AI on Entrepreneurial Performance] ([https://doi.org/10.31219/osf.io/hdjpk doi: 10.31219/osf.io/hdjpk])
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* 2024-07: [https://www.microsoft.com/en-us/research/publication/generative-ai-in-real-world-workplaces/ Generative AI in Real-World Workplaces: The Second Microsoft Report on AI and Productivity Research]
 +
 
 +
===Coding===
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* 2023-02: [https://arxiv.org/abs/2302.06590 The Impact of AI on Developer Productivity: Evidence from GitHub Copilot]
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* 2024-09:  Cui, Zheyuan and Demirer, Mert and Jaffe, Sonia and Musolff, Leon and Peng, Sida and Salz, Tobias, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4945566 The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers] (September 03, 2024). [http://dx.doi.org/10.2139/ssrn.4945566 doi: 10.2139/ssrn.4945566 ]
 +
* 2024-11:  Hoffmann, Manuel and Boysel, Sam and Nagle, Frank and Peng, Sida and Xu, Kevin, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5007084 Generative AI and the Nature of Work] (October 27, 2024). Harvard Business School Strategy Unit Working Paper No. 25-021, Harvard Business Working Paper No. No. 25-021, [http://dx.doi.org/10.2139/ssrn.5007084 doi: 10.2139/ssrn.5007084]
 +
 
 +
===Forecasting===
 +
* 2024-02: [https://arxiv.org/abs/2402.07862 AI-Augmented Predictions: LLM Assistants Improve Human Forecasting Accuracy]
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===Creativity===
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* 2024-07: [https://www.science.org/doi/10.1126/sciadv.adn5290 Generative AI enhances individual creativity but reduces the collective diversity of novel content]
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* 2024-08: [https://www.nature.com/articles/s41562-024-01953-1 An empirical investigation of the impact of ChatGPT on creativity]
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* 2024-11: [https://conference.nber.org/conf_papers/f210475.pdf Artificial Intelligence, Scientific Discovery, and Product Innovation]: diffusion model increases "innovation" (patents), boosts the best performers, but also removes some enjoyable tasks.
 +
 
 +
===Counter loneliness===
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* 2024-07: [https://arxiv.org/abs/2407.19096 AI Companions Reduce Loneliness]
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 +
==AI passes Turing Test==
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* 2023-05: [https://arxiv.org/abs/2305.20010 Human or Not? A Gamified Approach to the Turing Test]
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* 2023-10: [https://arxiv.org/abs/2310.20216 Does GPT-4 pass the Turing test?]
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* 2024-05: [https://arxiv.org/abs/2405.08007 People cannot distinguish GPT-4 from a human in a Turing test]
 +
* 2024-07: [https://arxiv.org/abs/2407.08853 GPT-4 is judged more human than humans in displaced and inverted Turing tests]
  
 
=Uptake=
 
=Uptake=
−
TBD
+
* 2024-03: [https://arxiv.org/abs/2403.07183 Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews]
 +
* 2024-05:  Humlum, Anders and Vestergaard, Emilie, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4827166 The Adoption of ChatGPT]. IZA Discussion Paper No. 16992 [http://dx.doi.org/10.2139/ssrn.4827166 doi: 10.2139/ssrn.4827166]
 +
* 2024-06: Kellogg, Katherine and Lifshitz-Assaf, Hila and Randazzo, Steven and Mollick, Ethan R. and Dell'Acqua, Fabrizio and McFowland III, Edward and Candelon, Francois and Lakhani, Karim R., [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4857373 Don't Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics] (June 03, 2024). Harvard Business School Technology & Operations Mgt. Unit Working Paper 24-074, Harvard Business Working Paper No. 24-074, The Wharton School Research Paper [http://dx.doi.org/10.2139/ssrn.4857373 doi: 10.2139/ssrn.4857373 ]
 +
* 2024-06: [https://arxiv.org/abs/2406.07016 Delving into ChatGPT usage in academic writing through excess vocabulary]
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* 2024-09: [https://static1.squarespace.com/static/60832ecef615231cedd30911/t/66f0c3fbabdc0a173e1e697e/1727054844024/BBD_GenAI_NBER_Sept2024.pdf The Rapid Adoption of Generative AI]
 +
* 2024-10: [https://ai.wharton.upenn.edu/focus-areas/human-technology-interaction/2024-ai-adoption-report/ Growing Up: Navigating Generative AI’s Early Years – AI Adoption Report] ([https://ai.wharton.upenn.edu/wp-content/uploads/2024/10/AI-Report_Executive-Summary.pdf executive summary], [https://ai.wharton.upenn.edu/wp-content/uploads/2024/10/AI-Report_Full-Report.pdf full report])
 +
** 72% of leaders use genAI at least once a week (c.f. 23% in 2023); 90% agree AI enhances skills (c.f. 80% in 2023)
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** Spending on genAI is up 130% (most companies plan to invest going forward)
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 +
=See Also=
 +
* [https://www.google.com/books/edition/_/cKnYEAAAQBAJ?hl=en&gbpv=1&pg=PA2 UNESCO. Guidance for Generative AI in Education and Research]

Latest revision as of 11:32, 15 November 2024

AI in Education

Survey/study of

AI improves learning/education

AI harms learning

Software/systems

Individual tools

AI for grading

Detection

AI Text Detectors Don't Work

AI/human

AI out-performs humans

Tests

Creativity

Various

Professions

AI improves human work

Coding

Forecasting

Creativity

Counter loneliness

AI passes Turing Test

Uptake

See Also

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