mlsanityData to 14 Oct 2026

Large Language Models Meet User Interfaces: The Case of Provisioning Feedback

arXiv 2404.11072 ↗First posted 17 Apr 2024cs.HC cs.AIcited by 4

Not on the map. Why?

Abstract (arXiv)

Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning. Current LLM usage involves conversational user interfaces (CUIs) for tasks like generating materials or providing feedback. However, this presents challenges including the need for educator expertise in AI and CUIs, ethical concerns with high-stakes decisions, and privacy risks. CUIs also struggle with complex tasks. To address these, we propose transitioning from CUIs to user-friendly applications leveraging LLMs via API calls. We present a framework for ethically incorporating GenAI into educational tools and demonstrate its application in our tool, Feedback Copilot, which provides personalized feedback on student assignments. Our evaluation shows the effectiveness of this approach, with implications for GenAI researchers, educators, and technologists. This work charts a course for the future of GenAI in education.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 37 of its 88 references that are in the map. First posted on arXiv 17 Apr 2024.

Builds on

37 of 88 references.

References · 37

  1. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  2. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 832
  3. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 619
  4. 2023Explainability for Large Language Models: A Surveycited by 333
  5. 2023Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicinecited by 329
  6. 2022Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionalscited by 191
  7. 2023Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directionscited by 125
  8. 2022Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generationcited by 99
  9. 2023Cognitive Mirage: A Review of Hallucinations in Large Language Modelscited by 84
  10. 2023Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Reviewcited by 83
  11. 2022Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Languagecited by 82
  12. 2023EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteriacited by 74
25 more
  1. 2024LLM-based NLG Evaluation: Current Status and Challengescited by 73
  2. 2023Graphologue: Exploring Large Language Model Responses with Interactive Diagramscited by 66
  3. 2023Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creationcited by 64
  4. 2023Computing Education in the Era of Generative AIcited by 52
  5. 2023Sensecape: Enabling Multilevel Exploration and Sensemaking with Large Language Modelscited by 48
  6. 2022How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Modelscited by 44
  7. 2023Learning gain differences between ChatGPT and human tutor generated algebra hintscited by 43
  8. 2022Opal: Multimodal Image Generation for News Illustrationcited by 36
  9. 2023Beyond the Chat: Executable and Verifiable Text-Editing with LLMscited by 35
  10. 2023Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Promptscited by 30
  11. 2024Supporting Sensemaking of Large Language Model Outputs at Scalecited by 27
  12. 2023Understanding Users' Dissatisfaction with ChatGPT Responses: Types, Resolving Tactics, and the Effect of Knowledge Levelcited by 26
  13. 2023Assessing the Quality of Multiple-Choice Questions Using GPT-4 and Rule-Based Methodscited by 24
  14. 2023Prompting for Discovery: Flexible Sense-Making for AI Art-Making with Dreamsheetscited by 22
  15. 2023Interactive AI Alignment: Specification, Process, and Evaluation Alignmentcited by 22
  16. 2023Scalable Educational Question Generation with Pre-trained Language Modelscited by 19
  17. 2023Evaluating ChatGPT's Decimal Skills and Feedback Generation in a Digital Learning Gamecited by 19
  18. 2023GenAssist: Making Image Generation Accessiblecited by 18
  19. 2023Assigning AI: Seven Approaches for Students, with Promptscited by 16
  20. 2024GenAudit: Fixing Factual Errors in Language Model Outputs with Evidencecited by 10
  21. 2023Human-Centred Learning Analytics and AI in Education: a Systematic Literature Reviewcited by 9
  22. 2023GAIDE: A Framework for Using Generative AI to Assist in Course Content Developmentcited by 7
  23. 2023Learnersourcing in the Age of AI: Student, Educator and Machine Partnerships for Content Creationcited by 6
  24. 2023Using Large Language Models to Provide Explanatory Feedback to Human Tutorscited by 6
  25. 2023Are LLMs Useful in the Poorest Schools? TheTeacher.AI in Sierra Leonecited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2025A Survey on Collaborative Mechanisms Between Large and Small Language Modelscited by 14
  2. 2025Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generationcited by 3
  3. 2026AgentLens: Adaptive Visual Modalities for Human-Agent Interaction in Mobile GUI Agentscited by 1
  4. 2025Dialogic Learning in Child-Robot Interaction: A Hybrid Approach to Personalized Educational Content Generationcited by 0