[논문]프로그래밍 학습 경험에 따른 학습 태도 변화 사례 연구

이경숙

doi:10.15207/jkcs.2021.12.9.093

프로그래밍 학습 경험에 따른 학습 태도 변화 사례 연구
A case study of learning attitude change according to programming learning experience 원문보기

한국융합학회논문지 = Journal of the Korea Convergence Society, v.12 no.9, 2021년, pp.93 - 98

이경숙 (고려대학교 BK21)

초록
AI-Helper

프로그래밍 언어 학습 경험이 학습 동기에 미치는 변화를 분석하였다. 프로그래밍 언어 학습은 전공생에게도 어려운 과정으로 평가되는 것이 일반적이다. 비전공자에게로 확대되고 있는 현 시점에서 프로그래밍 학습과 관련된 심리적 태도 변화를 측정하는 것은 학습자 분석에 필요하다. 동기 관련 구인요인인 성취목표, 학업적 흥미, 학업적 자기효능감, 인지적 관여, 학업적 자기조절을 측정하여 전반적인 학습자 태도 변화를 알아보았다. 측정 결과 학습 태도 관련 모든 요인에서 사후 검사 값이 감소한 것으로 나타났다. 이 결과는 학습과정의 난이도가 프로그래밍 학습 의욕을 감소시킨 것으로 해석된다. 학습자가 인지하는 난이도가 클 수록 학습의욕이 더 크게 감소하는 것으로 나타났다. 이런 연구결과를 바탕으로 학습자가 느끼는 학습 난이도의 정도를 낮출 수 있는 상황과 피드백을 줄 수 있는 체계적인 학습환경과 학습과정의 중요성을 시사점으로 제시하고자 한다.

Abstract ▼ AI-Helper

The change of programming language learning experience on learning motivation was analyzed. Learning a programming language is generally evaluated as a difficult process even for majors. Measuring psychological changes related to programming learning at this point in expanding to non-majors is necessary for learner analysis. The overall learner attitude change was investigated by measuring achievement goals, academic interest, academic self-efficacy, cognitive involvement, and academic self-regulation, which are motivation-related factors. All factors related to learning attitude showed a decrease in the post-test results. This result is interpreted that the difficulty of the learning process decreased the motivation to learn programming. It was found that the greater the difficulty perceived by the learner, the greater the decrease in the motivation to learn. Based on the results of this study, it has implications that a learning environment and learning process that can give feedback and a situation that can reduce the level of learning difficulty felt by learners should be systematically given.

주제어

표/그림 (6)

그림 Fig. 1. Moderating effect
그림 Fig. 2. moderating effect
표 Table 1. Python Programming Studies (p > .05)
표 Table 2. C++ Programming Studies(p > .05)
표 Table 3. parameter estimates for TAMG
표 Table 4. parameter estimates for TASEP

참고문헌 (20)

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