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Design of Handwriting-based Text Interface for Support of Mobile Platform Education Contents

모바일 플랫폼 교육 콘텐츠 지원을 위한 손 글씨 기반 텍스트 인터페이스 설계

  • Cho, Yunsik (Department of Computer Engineering, Graduate School, Hansung University) ;
  • Cho, Sae-Hong (Division of Computer Engineering, Hansung University) ;
  • Kim, Jinmo (Division of Computer Engineering, Hansung University)
  • 조윤식 (한성대학교 일반대학원 컴퓨터공학과) ;
  • 조세홍 (한성대학교 컴퓨터공학부) ;
  • 김진모 (한성대학교 컴퓨터공학부)
  • Received : 2021.11.19
  • Accepted : 2021.11.26
  • Published : 2021.12.01

Abstract

This study proposes a text interface for support of language-based educational contents in a mobile platform environment. The proposed interface utilizes deep learning as an input structure to write words through handwriting. Based on GUI (Graphical User Interface) using buttons and menus of mobile platform contents and input methods such as screen touch, click, and drag, we design a text interface that can directly input and process handwriting from the user. It uses the EMNIST (Extended Modified National Institute of Standards and Technology database) dataset and a trained CNN (Convolutional Neural Network) to classify and combine alphabetic texts to complete words. Finally, we conduct experiments to analyze the learning support effect of the interface proposed by directly producing English word education contents and to compare satisfaction. We compared the ability to learn English words presented by users who have experienced the existing keypad-type interface and the proposed handwriting-based text interface in the same educational environment, and we analyzed the overall satisfaction in the process of writing words by manipulating the interface.

본 연구는 모바일 플랫폼 환경에서 언어 기반의 교육 콘텐츠 지원을 위한 텍스트 인터페이스를 제안한다. 이는 손 글씨를 통해 단어를 작성하는 입력 구조로 딥 러닝을 활용한다. 모바일 플랫폼 콘텐츠의 버튼, 메뉴 등을 활용한 GUI (Graphical User Interface)와 화면 터치, 클릭, 드래그 등의 입력 방식을 기반으로 손 글씨를 사용자로부터 직접 입력하여 처리할 수 있는 텍스트 인터페이스를 설계한다. 이는 EMNIST (Extended Modified National Institute of Standards and Technology database) 데이터 셋과 훈련된 CNN (Convolutional Neural Network)을 사용하여 알파벳 텍스트를 분류하고 조합하여 단어를 완성한다. 최종적으로 영어 단어 교육 콘텐츠를 직접 제작하여 제안하는 인터페이스의 학습 지원 효과를 분석하고 만족도를 비교하기 위한 실험을 진행한다. 동일한 교육 환경에서 기존의 키 패드 방식의 인터페이스와 제안하는 손 글씨 기반 텍스트 인터페이스를 서로 체험한 사용자들이 제시하는 영어 단어를 학습하는 능력을 비교하고, 인터페이스를 조작하여 단어를 작성하는 과정에서의 전체적인 만족도를 분석, 확인하도록 한다.

Keywords

Acknowledgement

이 논문은 2021년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구임(연구개발과제번호: 2021-0-00884, 비대면 협업용 솔루션 및 블록체인 기반 디지털 워크 통합 플랫폼 개발, 기여율 30%, 조세홍). 그리고 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임 (No. 2020R1F1A1063442, 기여율 40%, 조윤식). 또한, 본 연구는 한성대학교 학술연구비 지원과제임 (기여율 30%, 김진모).

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