A Study on the Application and Issues of Generative AI-Based EduTech in Korean Languge Education : Focusing on University Korean Language Instructors’ Perceptions and the Characteristics of Generative AI

This study aims to explore the applicability and challenges of utilizing generative AI-based EduTech in Korean language education. It investigates the impact of generative AI technology on Korean classroom and presents the findings from a survey conducted among university Korean instructors. Generative AI, a cutting-edge technology capable of generating not only text but also diverse digital content, shows great potential for application in educational settings. It is particularly noted for its ability to provide personalized learning experiences and interactive opportunities. Despite the development of various teaching and learning tools incorporating this technology, their usage in actual educational contexts remains limited. A survey of 46 university Korean language instructors was conducted to analyze the implementation status of generative AI-based tools and instructors' perceptions of their educational effectiveness. The findings revealed that many instructors pointed to a lack of understanding about how to effectively utilize these tools, concerns about decreased learner concentration, and uncertainties about their educational impact. While some held optimistic views on the technology's potential, skepticism about its applicability also emerged. Based on these results, this study suggests that the effective integration of generative AI-based EduTech into Korean education requires the development of appropriate educational data, strengthening digital literacy competencies among teachers and learners, and a systematic approach that aligns technology with educational practices. Furthermore, the study examines the educational challenges related to the use of generative AI-based tools in education and proposes directions for their future development and roles in the field. By offering a balanced discussion on the educational potential and limitations of generative AI, this research seeks to contribute to identifying strategies and actionable plans for its effective use in Korean language education.

Authors

Publication Details

Journal
The Korean Association of General Education
Published
2024-12-31
DOI
https://doi.org/10.46392/kjge.2024.18.6.291
Citations
3
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
1.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on the Application and Issues of Generative AI-Based EduTech in Korean Languge Education : Focusing on University Korean Language Instructors’ Perceptions and the Characteristics of Generative AI

Bohyeon Kim
3 citations
The Korean Association of General Education
Diverse Approaches in Healthcare and Education Studies
1.63
article

A Study on the Application and Issues of Generative AI-Based EduTech in Korean Languge Education : Focusing on University Korean Language Instructors’ Perceptions and the Characteristics of Generative AI

Bohyeon Kim
article en
3 citations

Abstract

This study aims to explore the applicability and challenges of utilizing generative AI-based EduTech in Korean language education. It investigates the impact of generative AI technology on Korean classroom and presents the findings from a survey conducted among university Korean instructors. Generative AI, a cutting-edge technology capable of generating not only text but also diverse digital content, shows great potential for application in educational settings. It is particularly noted for its ability to provide personalized learning experiences and interactive opportunities. Despite the development of various teaching and learning tools incorporating this technology, their usage in actual educational contexts remains limited. A survey of 46 university Korean language instructors was conducted to analyze the implementation status of generative AI-based tools and instructors' perceptions of their educational effectiveness. The findings revealed that many instructors pointed to a lack of understanding about how to effectively utilize these tools, concerns about decreased learner concentration, and uncertainties about their educational impact. While some held optimistic views on the technology's potential, skepticism about its applicability also emerged. Based on these results, this study suggests that the effective integration of generative AI-based EduTech into Korean education requires the development of appropriate educational data, strengthening digital literacy competencies among teachers and learners, and a systematic approach that aligns technology with educational practices. Furthermore, the study examines the educational challenges related to the use of generative AI-based tools in education and proposes directions for their future development and roles in the field. By offering a balanced discussion on the educational potential and limitations of generative AI, this research seeks to contribute to identifying strategies and actionable plans for its effective use in Korean language education.

The Korean Association of General EducationVol. 18(6)
Openalex Percentile: Top 14%
Diverse Approaches in Healthcare and Education Studies
1.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Study on the Application and Issues of Generative AI-Based EduTech in Korean Languge Education : Focusing on University Korean Language Instructors’ Perceptions and the Characteristics of Generative AI — Bohyeon Kim · The Korean Association of General Education (2024) | TGRS Research Map | TGRS