Correlation of M-IoU with Human Judgments for Outcome-Based Praise

by HighlighterMay 31st, 2025
Read on Terminal Reader
Read this story w/o Javascript
tldt arrow

Too Long; Didn't Read

This scatter matrix visualizes the strong positive correlation between M-IoU scores and human coder ratings for outcome-based praise in automated feedback analysis.

Coin Mentioned

Mention Thumbnail
featured image - Correlation of M-IoU with Human Judgments for Outcome-Based Praise
Highlighter HackerNoon profile picture
0-item

Abstract and 1 Introduction

2. Background

2.1 Effective Tutoring Practice

2.2 Feedback for Tutor Training

2.3 Sequence Labeling for Feedback Generation

2.4 Large Language Models in Education

3. Method

3.1 Dataset and 3.2 Sequence Labeling

3.3 GPT Facilitated Sequence Labeling

3.4 Metrics

4. Results

4.1 Results on RQ1

4.2 Results on RQ2

5. Discussion

6. Limitation and Future Works

7. Conclusion

8. Acknowledgments

9. References


APPENDIX

A. Lesson Principles

B. Input for Fine-Tunning GPT-3.5

C. Scatter Matric of the Correlation on the Outcome-based Praise

D. Detailed Results of Fine-Tuned GPT-3.5 Model's Performance

C. SCATTER MATRIX OF THE CORRELATION ON THE OUTCOME-BASED PRAISE

Figure 5: Scatter matrix of the correlation on the outcome-based praise


This paper is available on arxiv under CC BY 4.0 DEED license.

Authors:

(1) Jionghao Lin, Carnegie Mellon University (jionghal@cs.cmu.edu);

(2) Eason Chen, Carnegie Mellon University (easonc13@cmu.edu);

(3) Zeifei Han, University of Toronto (feifei.han@mail.utoronto.ca);

(4) Ashish Gurung, Carnegie Mellon University (agurung@andrew.cmu.edu);

(5) Danielle R. Thomas, Carnegie Mellon University (drthomas@cmu.edu);

(6) Wei Tan, Monash University (wei.tan2@monash.edu);

(7) Ngoc Dang Nguyen, Monash University (dan.nguyen2@monash.edu);

(8) Kenneth R. Koedinger, Carnegie Mellon University (koedinger@cmu.edu).


Trending Topics

blockchaincryptocurrencyhackernoon-top-storyprogrammingsoftware-developmenttechnologystartuphackernoon-booksBitcoinbooks