생성적 인공지능의 교육적 활용 방안 탐색

• 영문명: An Investigation of Generative AI in Educational Application: Focusing on the Usage of ChatGPT for Learning Biology
• 발행기관: 한국교원대학교 뇌·AI기반교육연구소
• 저자명: 변정호 권용주
• 간행물 정보: 『Brain, Digital, & Learning』제13권 제1호, 1~17쪽, 전체 17쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2023.03.31

영문 초록

Recently, generative AI could create new information and contents similar to the real, and the AI interacts like humans. The investigation of teaching and learning is essential to use generative AI in education. Therefore researchers performed a literature review of the characteristics and types of generative AI for the guide and direction of the educational application. ChatGPT is a representative example of generative AI, and it is an unsupervised learning model based on GPT(a deep learning-based language model). It can generate output like humans from pre-learned big data and experience similar to the teacher and student interaction. In particular, life science targets living organisms and must consider multidimensional perspectives. Therefore generative AI can use as an assistance tool for concept learning and inquiry activities in biology education. According to the theoretical considerations and use cases presented above, it was possible to learn with the help of generative AI without experts to verify learners' intuition concepts, inquiry performance, maintain safety, analysis of results, and etc. Researchers present a teaching-learning model using generative AI based on a literature review and examples for biological concept learning and inquiry activities using ChatGPT. It is necessary to shift the evaluation method from quantitative to qualitative to utilize generative AI. Also, it is essential to present a strategy for teaching and learning using AI in consideration of ethical aspects and to develop learners' decision-making capabilities.

목차

Introduction

AI for Education

New Paradigm of AI & Education

References

키워드

Artificial intelligence generative AI chatGPT biology education teaching and learning strategy