교수자 중심의 강의식 교수법이 갖는 한계점을 극복하고자 최근 학습자 중심의 교수법인 플립러닝이 널리 도입되고 있다. 하지만 플립러닝이 갖는 여러 장점에도 불구하고 학습자가 선행 학습 시 발생하는 질문들을 실시간 해결할 수 없다는 문제가 존재한다. 따라서 본 연구에서는 이러한 문제를 해결하기 위해 플립러닝 방식으로 운영하는 데이터베이스 설계 교과목을 위한 수업 도우미 챗봇인 디비봇을 개발하였다. 디비봇은 크게 학습자용 챗봇 앱과 교수자용 챗봇 관리 앱으로 구성되며, 수업 운영 관련 질문과 학습 내용 관련 매학기 반복되는 질문처럼 교수자가 미리 예상할 수 있는 질문은 구글의 다이얼로그 플로우(DialogFlow)를 활용해서 답변할 수 있도록 구현하였다. 또한, 팀 프로젝트와 관련된 질문처럼 교수자가 미리 예상하기 어려운 질문은 질의/응답 DB와 유사도 비교 알고리즘인 BM25 알고리즘을 활용해서 답변할 수 있도록 구현하였다.
교수자 중심의 강의식 교수법이 갖는 한계점을 극복하고자 최근 학습자 중심의 교수법인 플립러닝이 널리 도입되고 있다. 하지만 플립러닝이 갖는 여러 장점에도 불구하고 학습자가 선행 학습 시 발생하는 질문들을 실시간 해결할 수 없다는 문제가 존재한다. 따라서 본 연구에서는 이러한 문제를 해결하기 위해 플립러닝 방식으로 운영하는 데이터베이스 설계 교과목을 위한 수업 도우미 챗봇인 디비봇을 개발하였다. 디비봇은 크게 학습자용 챗봇 앱과 교수자용 챗봇 관리 앱으로 구성되며, 수업 운영 관련 질문과 학습 내용 관련 매학기 반복되는 질문처럼 교수자가 미리 예상할 수 있는 질문은 구글의 다이얼로그 플로우(DialogFlow)를 활용해서 답변할 수 있도록 구현하였다. 또한, 팀 프로젝트와 관련된 질문처럼 교수자가 미리 예상하기 어려운 질문은 질의/응답 DB와 유사도 비교 알고리즘인 BM25 알고리즘을 활용해서 답변할 수 있도록 구현하였다.
In order to overcome the limitations of the instructor-centered lecture-style teaching method, recently, flipped learning, a learner-centered teaching method, has been widely introduced. However, despite the many advantages of flipped learning, there is a problem that students cannot solve questions...
In order to overcome the limitations of the instructor-centered lecture-style teaching method, recently, flipped learning, a learner-centered teaching method, has been widely introduced. However, despite the many advantages of flipped learning, there is a problem that students cannot solve questions that arise during prior learning in real time. Therefore, in order to solve this problem, we developed DBbot, an assistant chatbot for database design course managed in the flipped learning method. The DBBot is composed of a chatbot app for learners and a chatbot management app for instructors. Also, it's implemented so that questions that instructors can anticipate in advance, such as questions related to class operation and every semester repeated questions related to learning content, can be answered using Google's DialogFlow. It's implemented so that questions that the instructor cannot predict in advance, such as questions related to team projects, can be answered using the question/answer DB and the BM25 algorithm, which is a similarity comparison algorithm.
In order to overcome the limitations of the instructor-centered lecture-style teaching method, recently, flipped learning, a learner-centered teaching method, has been widely introduced. However, despite the many advantages of flipped learning, there is a problem that students cannot solve questions that arise during prior learning in real time. Therefore, in order to solve this problem, we developed DBbot, an assistant chatbot for database design course managed in the flipped learning method. The DBBot is composed of a chatbot app for learners and a chatbot management app for instructors. Also, it's implemented so that questions that instructors can anticipate in advance, such as questions related to class operation and every semester repeated questions related to learning content, can be answered using Google's DialogFlow. It's implemented so that questions that the instructor cannot predict in advance, such as questions related to team projects, can be answered using the question/answer DB and the BM25 algorithm, which is a similarity comparison algorithm.
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