mlsanityData to 7 Oct 2026

RubiSCoT: A Framework for AI-Supported Academic Assessment

arXiv 2510.17309 ↗First posted 20 Oct 2025cs.AI cs.CLcited by 1

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Abstract (arXiv)

The evaluation of academic theses is a cornerstone of higher education, ensuring rigor and integrity. Traditional methods, though effective, are time-consuming and subject to evaluator variability. This paper presents RubiSCoT, an AI-supported framework designed to enhance thesis evaluation from proposal to final submission. Using advanced natural language processing techniques, including large language models, retrieval-augmented generation, and structured chain-of-thought prompting, RubiSCoT offers a consistent, scalable solution. The framework includes preliminary assessments, multidimensional assessments, content extraction, rubric-based scoring, and detailed reporting. We present the design and implementation of RubiSCoT, discussing its potential to optimize academic assessment processes through consistent, scalable, and transparent evaluation.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 46 references that are in the map. First posted on arXiv 20 Oct 2025.

Builds on

14 of 46 references.

References · 14

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  5. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  6. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  7. 2024LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Textscited by 81
  8. 2023Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preferencecited by 37
  9. 2024A Chain-of-Thought Prompting Approach with LLMs for Evaluating Students' Formative Assessment Responses in Sciencecited by 31
  10. 2024Grade Like a Human: Rethinking Automated Assessment with Large Language Modelscited by 16
  11. 2024Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoringcited by 13
  12. 2024Using Large Language Models for Automated Grading of Student Writing about Sciencecited by 12
2 more
  1. 2024Evaluating Students' Open-ended Written Responses with LLMs: Using the RAG Framework for GPT-3.5, GPT-4, Claude-3, and Mistral-Largecited by 6
  2. 2024"My Grade is Wrong!": A Contestable AI Framework for Interactive Feedback in Evaluating Student Essayscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026AI-Based Thesis Assessment: An Empirical Study of Human Evaluation Priorities and Their Impact on Automated Assessmentcited by 0

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