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L@S 2024 — accepted papers

L@S 2024 is the 2024 edition of the ACM Conference on Learning @ Scale (L@S). OpenAlex lists 92 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

 92papers in the proceedings 1work in our library 66citations of these works

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

  1. Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study ↗Wenhan Lyu, Yimeng Wang, Tingting Rachel Chung et al.126 citations
  2. Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms ↗Harsh Kumar, Ruiwei Xiao, Benjamin Lawson et al.52 citations
  3. CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming ↗Xinying Hou, Zihan Wu, Xu Wang et al.45 citations
  4. AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and GuardrailsSankalan Pal Chowdhury, Vilém Zouhar, Mrinmaya Sachan44 citations · our summary
  5. Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability To Mark Short Answer Questions in K-12 Education ↗Owen Henkel, Libby Hills, Adam Boxer et al.42 citations
  6. Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS Course ↗Binglin Chen, Colleen M. Lewis, Matthew West et al.39 citations
  7. Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation ↗Xinyi Lu, Xu Wang37 citations
  8. Combining LLM-Generated and Test-Based Feedback in a MOOC for Programming ↗Hagit Gabbay, Anat Cohen36 citations
  9. GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation ↗Eason Chen, Jia-En Lee, Jionghao Lin et al.30 citations
  10. Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces ↗Tommaso Calò, Christopher J. MacLellan26 citations

All accepted papers (92)

The most cited first; 1 with our summary link to their page here, the others to the original.

  1. Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study ↗Wenhan Lyu, Yimeng Wang, Tingting Rachel Chung et al.126 citations
  2. Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms ↗Harsh Kumar, Ruiwei Xiao, Benjamin Lawson et al.52 citations
  3. CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming ↗Xinying Hou, Zihan Wu, Xu Wang et al.45 citations
  4. AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and GuardrailsSankalan Pal Chowdhury, Vilém Zouhar, Mrinmaya Sachan44 citations · our summary
  5. Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability To Mark Short Answer Questions in K-12 Education ↗Owen Henkel, Libby Hills, Adam Boxer et al.42 citations
  6. Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS Course ↗Binglin Chen, Colleen M. Lewis, Matthew West et al.39 citations
  7. Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation ↗Xinyi Lu, Xu Wang37 citations
  8. Combining LLM-Generated and Test-Based Feedback in a MOOC for Programming ↗Hagit Gabbay, Anat Cohen36 citations
  9. GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation ↗Eason Chen, Jia-En Lee, Jionghao Lin et al.30 citations
  10. Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces ↗Tommaso Calò, Christopher J. MacLellan26 citations
  11. Using Cipherbot: An Exploratory Analysis of Student Interaction with an LLM-Based Educational Chatbot ↗Joni O. Salminen, Soon‐gyo Jung, Johanne Medina et al.25 citations
  12. Prompting for Comprehension: Exploring the Intersection of Explain in Plain English Questions and Prompt Writing ↗David Horton Smith, Paul C. Denny, Max Fowler22 citations
  13. Simulating Climate Change Discussion with Large Language Models: Considerations for Science Communication at Scale ↗Ha Nguyen, Victoria Nguyen, Saríah López-Fierro et al.22 citations
  14. Is GPT-4 Alone Sufficient for Automated Essay Scoring?: A Comparative Judgment Approach Based on Rater Cognition ↗Seungju Kim, Meounggun Jo19 citations
  15. Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions ↗Steven Moore, Robin Schmucker, Tom M. Mitchell et al.18 citations
  16. Automated Quality Assessment of Multimodal Mathematical Stories Generated by Generative Artificial Intelligence ↗Hai Li, Rui Guo, Chenglu Li et al.18 citations
  17. Short answer scoring with GPT-4 ↗Lan Jiang, Nigel Bosch18 citations
  18. AI-Driven Content Creation: Revolutionizing Educational Materials ↗Miguel Morales, Héctor R. Amado-Salvatierra, Rocael Hernández-Rizzardini17 citations
  19. Nemobot: Crafting Strategic Gaming LLM Agents for K-12 AI Education ↗Yuchen Wang, Shangxin Guo, Lin Ling et al.16 citations
  20. Automatic Feedback Generation on K-12 Students' Data Science Education by Prompting Cloud-based Large Language Models ↗Sze Ching Evelyn Fung, Man Fai Wong, Chee Wei Tan15 citations
  21. Socratic Mind: Scalable Oral Assessment Powered By AI ↗Jui-Tse Hung, Christopher Cui, Diana M. Popescu et al.15 citations
  22. Comparing Feedback from Large Language Models and Instructors: Teaching Computer Science at Scale ↗Ha Nguyen, Nate Stott, Vicki H. Allan13 citations
  23. Ten Years, Ten Trends: The First Decade of an Affordable At-Scale Degree ↗David A. Joyner, Alex Simon Duncan13 citations
  24. CFlow: Supporting Semantic Flow Analysis of Students' Code in Programming Problems at Scale ↗Ge Zhang, Xiaohang Tang, Steve Oney et al.12 citations
  25. Scaling Up Mastery Learning with Generative AI: Exploring How Generative AI Can Assist in the Generation and Evaluation of Mastery Quiz Questions ↗Stephen J. Hutt, Grayson Hieb12 citations

See all 92 papers in L@S 2024 — accepted papers →

 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

  1. AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and GuardrailsACM Conference on Learning @ Scale (L@S)Sankalan Pal Chowdhury, Vilém Zouhar, Mrinmaya Sachan2024 · 66 citations

 Top topics

Topics of its works in our library, with the number of works on each.

Language models & pretraining (1)

 Fields

Computer Science (1)Medicine (1)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🧑‍🔬Mrinmaya Sachan1 work here · 66 citations🧑‍🔬Sankalan Pal Chowdhury1 work here · 66 citations🧑‍🔬Vilém Zouhar1 work here · 66 citations

 Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓ETH ZurichZurich · Switzerland1 work here

works and citations from OpenAlex and our library.

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