MuFIN: A Framework for Automating Multimodal Feedback Generation using Generative Artificial Intelligence-Reference-Cited by-同舟云学术

MuFIN: A Framework for Automating Multimodal Feedback Generation using Generative Artificial Intelligence

Published:2024-07-09 Issue: Volume: Page:550-552
ISSN:
Container-title:Proceedings of the Eleventh ACM Conference on Learning @ Scale
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Author:

Lin Jionghao¹^ORCID,Chen Eason²^ORCID,Gurung Ashish¹^ORCID,Koedinger Kenneth R.¹^ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Carnegie Mellon University, Pittsburgh, USA

Funder

Learning Engineering Virtual Institute

Richard King Mellon Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3657604.3664720

Reference7 articles.

1. Dan Jurafsky and James H Martin. 2022. Speech and Language Processing. 3rd.

2. Jionghao Lin, Eason Chen, Zifei Han, Ashish Gurung, Danielle R Thomas,Wei Tan, Ngoc Dang Nguyen, and Kenneth R Koedinger. 2024. How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses. International Conference on Educational Data Mining (2024).

3. How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses

4. Jionghao Lin, Danielle R Thomas, Feifei Han, Shivang Gupta,Wei Tan, Ngoc Dang Nguyen, and Kenneth R Koedinger. 2023. Using large language models to provide explanatory feedback to human tutors. AIED 2023 Workshop - Towards the Future of AI-augmented Human Tutoring in Math Learning (2023).

5. Danielle Thomas, Xinyu Yang, Shivang Gupta, Adetunji Adeniran, Elizabeth Mclaughlin, and Kenneth Koedinger. 2023. When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors. In LAK23: 13th International Learning Analytics and Knowledge Conference. 250--261.