Supporting Novice Researchers to Write Literature Review using Language Models
Kiroong Choe, Seokhyeon Park, Seokweon Jung, Hyeok Kim, Ji Won Yang, Hwajung Hong, and Jinwook Seo / 2024
Participants
- Kiroong Choe, Seoul National University
- Seokhyeon Park, Seoul National University
- Seokweon Jung, Seoul National University
- Hyeok Kim, Northwestern University
- Ji Won Yang, Seoul National University
- Hwajung Hong, KAIST
- Jinwook Seo, Seoul National University
Abstract
A literature review requires more than summarization. While language model-based services and systems increasingly assist in analyzing accurate content in papers, their role in supporting novice researchers to develop independent perspectives on literature remains underexplored. We propose the design and evaluation of a system that supports the writing of argumentative narratives from literature. Based on the barriers faced by novice researchers before, during, and after writing, identified through semi-structured interviews, we propose a prototype of a language-model-assisted academic writing system that scaffolds the literature review writing process. A series of workshop studies revealed that novice researchers found the support valuable as they could initiate writing, co-create satisfying contents, and develop agency and confidence through a long-term dynamic partnership with the AI.
Overview
Writing the Related Work section is not just a final step, yet is overwhelming task for novice researchers.
We integrated interaction with large language models atop Notion to encourage and enhance engagement with literature review writing.
LLMs not only helped initiate and develop narratives but also acted as supportive companions, boosting confidence and fostering a sense of agency.
Publications
- Kiroong Choe, Seokhyeon Park, Seokweon Jung, Hyeok Kim, Ji Won Yang, Hwajung Hong, and Jinwook Seo, Supporting Novice Researchers to Write Literature Review using Language Models, [PDF], CHI Conference on Human Factors in Computing Systems (CHI EA ’24)