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Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning.
The Power of Feedback
John Hattie and Helen Timperley · 1935
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A Systematic Literature Review of Automated Feedback Generation for Programming Exercises
Hieke Keuning, Johan Jeuring, and Bastiaan Heeren · 1946
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Formative assessment and self-regulated learning: A model and seven principles of good feedback practice
David J. Nicol and Debra Macfarlane-Dick · 2006
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The feedback triangle and the enhancement of dialogic feedback processes
Min Yang and David Carless · 2012
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Do Learners Really Know Best? Urban Legends in Education
Paul A. Kirschner and Jeroen J.G. van Merriënboer · 2013
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Using multivariate statistics , volume 6
Barbara G Tabachnick, Linda S Fidell, and Jodie B Ullman · 2013
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Conceptual framework for feedback automation in sles
Estefanía Serral and Monique Snoeck · 2016
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Discovering statistics using R
Andy Field, Jeremy Miles, and Zoe Field · 2017
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Beyond the Chat: Executable and Verifiable Text-Editing with LLMs
Philippe Laban, Jesse Vig, Marti A Hearst, Caiming Xiong, and Chien-Sheng Wu · 2018
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Designing educational technologies in the age of AI: A learning sciences-driven approach
Rosemary Luckin and Mutlu Cukurova · 2019
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Designing translucent learning analytics with teachers: An elicitation process
Roberto Martinez-Maldonado, Doug Elliott, Carmen Axisa, Tamara Power, Vanessa Echeverria, and Simon Buckingham Shum · 2019
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What is AI Literacy? Competencies and Design Considerations
Duri Long and Brian Magerko · 2020
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The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research
Benedikt Wisniewski, Klaus Zierer, and John Hattie · 2020
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A review of automated feedback systems for learners: Classification framework, challenges and opportunities
Galina Deeva, Daria Bogdanova, Estefanía Serral, Monique Snoeck, and Jochen De Weerdt · 2020
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Automatic feedback in online learning environments: A systematic literature review
Anderson Pinheiro Cavalcanti, Arthur Barbosa, Ruan Carvalho, Fred Freitas, Yi-Shan Tsai, Dragan Gašević, and Rafael Ferreira Mello · 2021
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A Review of Feedback Models and Theories: Descriptions, Definitions, and Conclusions
Anastasiya A. Lipnevich and Ernesto Panadero · 2021
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Personalized feedback in digital learning environments: Classification framework and literature review
Uwe Maier and Christian Klotz · 2022
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Machine learning based feedback on textual student answers in large courses
Jan Philip Bernius, Stephan Krusche, and Bernd Bruegge · 2022
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Hai Dang, Lukas Mecke, Florian Lehmann, Sven Goller, and Daniel Buschek · 2022
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Opal: Multimodal image generation for news illustration
Vivian Liu, Han Qiao, and Lydia Chilton · 2022
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Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education
Thomas K.F. Chiu, Qi Xia, Xinyan Zhou, Ching Sing Chai, and Miaoting Cheng · 2022
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Beyond the Learning Analytics Dashboard: Alternative Ways to Communicate Student Data Insights Combining Visualisation, Narrative and Storytelling
Gloria Milena Fernandez Nieto, Kirsty Kitto, Simon Buckingham Shum, and Roberto Martinez-Maldonado · 2022
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Explainable Artificial Intelligence in education
Hassan Khosravi, Simon Buckingham Shum, Guanliang Chen, Cristina Conati, Yi-Shan Tsai, Judy Kay, Simon Knight, Roberto Martinez-Maldonado, Shazia Sadiq, and Dragan Gašević · 2022
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emmeans: Estimated marginal means, aka least-squares means
Russell V. Lenth · 2022
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A Model for Integrating Generative AI into Course Content Development, August 2023
Ethan Dickey and Andres Bejarano · 2023
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Scalable Educational Question Generation with Pre-trained Language Models, May 2023
Sahan Bulathwela, Hamze Muse, and Emine Yilmaz · 2023
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Assessing the Quality of Multiple-Choice Questions Using GPT-4 and Rule-Based Methods
Steven Moore, Huy A. Nguyen, Tianying Chen, and John Stamper · 2023
Cited alongside, same era.
Generative AI for Learning: Investigating the Potential of Learning Videos with Synthetic Virtual Instructors
Daniel Leiker, Ashley Ricker Gyllen, Ismail Eldesouky, and Mutlu Cukurova · 2023
Cited alongside, same era.
Learning gain differences between ChatGPT and human tutor generated algebra hints, February 2023
Zachary A. Pardos and Shreya Bhandari · 2023
Cited alongside, same era.
Learnersourcing in the age of AI: Student, educator and machine partnerships for content creation
Hassan Khosravi, Paul Denny, Steven Moore, and John Stamper · 2023
Cited alongside, same era.
FABRIC: Automated Scoring and Feedback Generation for Essays, October 2023
Jieun Han, Haneul Yoo, Junho Myung, Minsun Kim, Hyunseung Lim, Yoonsu Kim, Tak Yeon Lee, Hwajung Hong, Juho Kim, So-Yeon Ahn, and Alice Oh · 2023
Cognitive Mirage: A Review of Hallucinations in Large Language Models, September 2023
Hongbin Ye, Tong Liu, Aijia Zhang, Wei Hua, and Weiqiang Jia · 2023
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Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
Harsha Nori, Yin Tat Lee, Sheng Zhang, Dean Carignan, Richard Edgar, Nicolo Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, and Weishung Liu · 2023
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Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution, September 2023
Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, Simon Osindero, and Tim Rocktäschel · 2023
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DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines, October 2023
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts · 2023
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Cited alongside, same era.
Are LLMs Useful in the Poorest Schools? theTeacherAI in Sierra Leone, October 2023
Jun Ho Choi, Oliver Garrod, Paul Atherton, Andrew Joyce-Gibbons, Miriam Mason-Sesay, and Daniel Björkegren · 2023
Cited alongside, same era.
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT, February 2023
Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, and Douglas C. Schmidt · 2023
Cited alongside, same era.
Prompting Change: Exploring Prompt Engineering in Large Language Model AI and Its Potential to Transform Education
William Cain · 2023
Cited alongside, same era.
Conversing with copilot: Exploring prompt engineering for solving cs1 problems using natural language
Paul Denny, Viraj Kumar, and Nasser Giacaman · 2023
Cited alongside, same era.
Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators
Weng Marc Lim, Asanka Gunasekara, Jessica Leigh Pallant, Jason Ian Pallant, and Ekaterina Pechenkina · 2023
Cited alongside, same era.
Assigning AI: Seven Approaches for Students, with Prompts, June 2023
Ethan Mollick and Lilach Mollick · 2023
Cited alongside, same era.
ChainForge: An open-source visual programming environment for prompt engineering
Ian Arawjo, Priyan Vaithilingam, Martin Wattenberg, and Elena Glassman · 2023
Cited alongside, same era.
Michael Terry, Chinmay Kulkarni, Martin Wattenberg, Lucas Dixon, and Meredith Ringel Morris · 2023
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Bridging the Gulf of Envisioning: Cognitive Design Challenges in LLM Interfaces, September 2023
Hariharan Subramonyam, Christopher Lawrence Pondoc, Colleen Seifert, Maneesh Agrawala, and Roy Pea · 2023
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Elena L. Glassman · 2023
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Preparing Educators and Students for ChatGPT and AI Technology in Higher Education:Benefits, Limitations, Strategies, and Implications of ChatGPT & AI Technologies
Bo Zhang · 2023
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Programming Is Hard - Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation
Brett A. Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather, and Eddie Antonio Santos · 2023
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AI literacy in K-12: A systematic literature review
Lorena Casal-Otero, Alejandro Catala, Carmen Fernández-Morante, Maria Taboada, Beatriz Cebreiro, and Senén Barro · 2023
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Generative AI and the Workforce: What Are the Risks?, September 2023
Emmanuelle Walkowiak and Trent MacDonald · 2023
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Learning, teaching, and assessment with generative artificial intelligence: Towards a plateau of productivity
Elizabeth Koh and Shayan Doroudi · 2023
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Impact of AI assistance on student agency
Ali Darvishi, Hassan Khosravi, Shazia Sadiq, Dragan Gašević, and George Siemens · 2023
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Cross-document event coreference resolution: Instruct humans or instruct GPT?
Jin Zhao, Nianwen Xue, and Bonan Min · 2023
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“Your argumentation is good”, says the AI vs humans – The role of feedback providers and personalised language for feedback effectiveness
Theresa Ruwe and Elisabeth Mayweg-Paus · 2023
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Evaluating llm-generated worked examples in an introductory programming course
Breanna Jury, Angela Lorusso, Juho Leinonen, Paul Denny, and Andrew Luxton-Reilly · 2024
Closest in time.
A Survey on Evaluation of Large Language Models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie · 2024
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Computing education in the era of generative ai
Paul Denny, James Prather, Brett A. Becker, James Finnie-Ansley, Arto Hellas, Juho Leinonen, Andrew Luxton-Reilly, Brent N. Reeves, Eddie Antonio Santos, and Sami Sarsa · 2024
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From the Automated Assessment of Student Essay Content to Highly Informative Feedback: A Case Study
Sebastian Gombert, Aron Fink, Tornike Giorgashvili, Ioana Jivet, Daniele Di Mitri, Jane Yau, Andreas Frey, and Hendrik Drachsler · 2024
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Supporting Sensemaking of Large Language Model Outputs at Scale, January 2024
Katy Ilonka Gero, Chelse Swoopes, Ziwei Gu, Jonathan K. Kummerfeld, and Elena L. Glassman · 2024
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Explainable artificial intelligence (xai) 2.0: A manifesto of open challenges and interdisciplinary research directions
Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, et al · 2024
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Explainability for Large Language Models: A Survey
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, and Mengnan Du · 2024
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LLM-based NLG Evaluation: Current Status and Challenges, February 2024
Mingqi Gao, Xinyu Hu, Jie Ruan, Xiao Pu, and Xiaojun Wan · 2024
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Genaudit: Fixing factual errors in language model outputs with evidence
Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron C Wallace, Zachary C Lipton, and Jeffrey P Bigham · 2024
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Human-centred learning analytics and ai in education: a systematic literature review
Riordan Alfredo, Vanessa Echeverria, Yueqiao Jin, Lixiang Yan, Zachari Swiecki, Dragan Gašević, and Roberto Martinez-Maldonado · 2024
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