본문 바로가기
KERD
논문KCI 등재

인공지능을 활용한 생명과학 교수·학습 모델 개발

Development of Teaching and Learning Model for Biology Class using Artificial Intelligence

변정호
뇌·AI기반교육연구소 (Institute of Brain·AI based Education)|2022.03|Brain, Digital, & Learning|제12권 제1호|pp. 51-67|DOI https://doi.org/10.31216/BDL.20220004

4

조회

0

다운로드

2

인용

0

참고문헌

키워드

Artificial intelligencemachine learningteaching and learning strategybiology educationteachable machine

초록

Artificial intelligence was used in various fields, it is widely focused on education recently. Appropriate teaching and learning strategies are necessary for the application of artificial intelligence to science education, however, there is in poor one to able to use by the teacher. Therefore, the purpose of this study was focused on the generation of appropriate teaching and learning model for biology class using artificial intelligence. Also, the researcher investigated the effect of the learning model for affective domain on high school students according to the application of the learning program. As a result of this study, the researcher could develop the teaching and learning model of biology education using artificial intelligence by theoretical review, and composed a learning program for application in class. According to the result of analysis for the effect of the affective domain, the level of learning motivation, task commitment, and attitude for artificial intelligence on post-test significantly increased more than the result of the pre-test. Consequently, it could be checked that the teaching and learning model of biology learning using artificial intelligence can cause a positive effect on the student’s learning.

Abstract

Artificial intelligence was used in various fields, it is widely focused on education recently. Appropriate teaching and learning strategies are necessary for the application of artificial intelligence to science education, however, there is in poor one to able to use by the teacher. Therefore, the purpose of this study was focused on the generation of appropriate teaching and learning model for biology class using artificial intelligence. Also, the researcher investigated the effect of the learning model for affective domain on high school students according to the application of the learning program. As a result of this study, the researcher could develop the teaching and learning model of biology education using artificial intelligence by theoretical review, and composed a learning program for application in class. According to the result of analysis for the effect of the affective domain, the level of learning motivation, task commitment, and attitude for artificial intelligence on post-test significantly increased more than the result of the pre-test. Consequently, it could be checked that the teaching and learning model of biology learning using artificial intelligence can cause a positive effect on the student’s learning.

참고문헌 (60)

  1. Akter, S., "Algorithmic bias in data-driven innovation in the age of AI", International Journal of Information Management, 60, pp.102387~ (2021)
  2. Alpaydin, E., "Introduction to Machine Learning" (2010), MIT Press
  3. Anderson, J. R., "Situated learning and education", Educational Researcher, 25, pp.5~11 (1996)
  4. Ashton-James, C. E., "Social cues for creativity : The impact of behavioral mimicry on convergent and divergent thinking", Journal of Experimental Social Psychology, 45, pp.1036~1040 (2009)
  5. Bahar, M., "The relationship between some psychological factors and their effect on the performance of grid questions and word association tests", Educational Psychology, 20, pp.349~364 (2000)
  6. Barak, M., "Teaching methods for inventive problem-solving in junior high school", Thinking Skills and Creativity, 2, pp.19~29 (2007)
  7. Berestova, A., "Social networks to improve the creative thinking of students: How does it works?", Thinking Skills and Creativity, 41, pp.100912~ (2021)
  8. 변정호, "과학 중심 STEAM 프로그램과 인문학 중심 STEAM 프로그램이 고등학생의 정의적 특성에 미치는 영향", Brain, Digital, & Learning, 10(3), pp.307~319 (2020), 뇌기반교육연구소[DOI]
  9. 변정호, "창의적 문제해결과정 기반 생체모방 융합수업 모델 개발", 생물교육, 40(3), pp.327~343 (2012), 한국생물교육학회[DOI]
  10. Byrne, M. D. B., "Reducing bias in healthcare artificial intelligence", Journal of PeriAnesthesia Nursing, 36, pp.313~316 (2021)
  11. 홍옥수, "인공지능, 사물인터넷, 빅데이터, 확장현실 기술을 활용한 과학탐구의 특징: IDEA형 과학교사연구회를 중심으로", 현장과학교육, 15(5), pp.407~422 (2021), 한국현장과학교육학회
  12. Chen, S. Y., "The effect of a scientific board on improving creative problem solving skills", Thinking Skills and Creativity, 41, pp.100921~ (2021)
  13. Chen, X., "A multi-perspective study on artificial intelligence in education : Grants, conferences, journals, software tools, institutions, and researchers", Computer & Education : Artificial Intelligence, 1, pp.100005~ (2020)
  14. 조영생, "AI 분류 모델을 활용한 초등 AI · 과학 융합 교육프로그램 개발", Brain, Digital, & Learning, 11(2), pp.227~243 (2021), 뇌기반교육연구소[DOI]
  15. Cropley, A. J., "In praise of convergent thinking", Creativity Research Journal, 18, pp.391~404 (2006)
  16. Embarak, O., "A new paradigm through machine learning : a learning maximization approach for sustainable education", Procedia Computer Science, 191, pp.445~450 (2021)
  17. Guan, C., "Artificial intelligence innovation in education : A twenty-year datadriven historical analysis", International Journal of Innovation Studies, 4, pp.134~147 (2020)
  18. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning, "Holmes, W.", The Center for Curriculum Redesign, ~ (2019)
  19. Concept and use of artificial intelligence in school education, "Hong, S. J.", KICE, 1~38, pp.KICE Position Paper, 12 (2019)
  20. Hwang, G., "A conceptual map model for developing intelligent tutoring systems", Computers & Education, 40, pp.217~235 (2003)
  21. 장진아, "인공지능 챗봇 관련 국내 연구 동향 및 챗봇 활용 현황 분석: 과학 교육에서의 활용을 위한 시사점을 중심으로", 학습자중심교과교육연구, 21(13), pp.729~743 (2021), 학습자중심교과교육학회
  22. 전인성, "인공지능교육 역량 강화를 위한 교원 연수 프로그램과 교사 요구분석", 정보교육학회논문지, 24(4), pp.279~289 (2020), 한국정보교육학회[DOI]
  23. Keller, J. M., "Motivational Design for Learning and Performance : The ARCS Model Approach" (2009), Springer
  24. 김한성, "인공지능의 이해와 사회적 영향력에 관한 교육 프로그램 개발 및 적용", 컴퓨터교육학회 논문지, 23(2), pp.21~29 (2020), 한국컴퓨터교육학회[DOI]
  25. Kim, J. H., "The Best Class of AI" (2020), Maekyungbook
  26. Klaur, K. J., "Inducing inductive reasoning: Does it transfer to fluid intelligence?", Contemporary Educational Psychology, 27, pp.1~25 (2002)
  27. 채승철, "인공지능 융합교육을 위한 데이터 기반 교육자료 개발: 감쇠진동을 중심으로", 현장과학교육, 15(2), pp.121~134 (2021), 한국현장과학교육학회[DOI]
  28. 이재호, "초등 AI 교육 플랫폼에 대한 전문가 인식조사 연구", 정보교육학회논문지, 24(5), pp.483~494 (2020), 한국정보교육학회[DOI]
  29. 이영호, "블록형 프로그래밍 언어 기반 인공지능 교육이 학습자의 인공지능 기술 태도에 미치는 영향 분석", 정보교육학회논문지, 23(2), pp.189~196 (2019), 한국정보교육학회[DOI]
  30. Lee, Y., "Artificial intelligence education plan using teachable machine", Journal of the Korean Association of Information Education, 47, pp.913~915 (2020)
  31. Long, D., "What is AI literacy? competencies and design considerations", Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp.1~16 (2020)
  32. Luckin, R., "Intelligence Unleashed : An Argument for AI in Education" (2016), Pearson Education
  33. Magana, S., "Enhancing the Art and Science of Teaching with Technology" (2014), Solution Tree
  34. Matthews, M. R., "Constructivism in Education: Opinions and Second Opinion on Controversial Issues", pp.161~192 (2000), The University of Chicago Press
  35. Menon, H. K. D., "Machine learning approaches in education", Materialstoday : PROCEEDINGS, 43, pp.3470~3480 (2021)
  36. The Plan of Future Curriculum with the People, "Ministry of Education", ~ (2021)
  37. Science Mathematics Information Convergence Education Comprehensive Plan, "Ministry of Education", ~ (2020)
  38. Minstry of Education, "AI Class in School", KOFAC, ~ (2021)
  39. National Research Council, "Inquiry and the National Science Education Standards: A Guide for Teaching and Learning" (2000), National Academy Press
  40. Nemeth, C. J., "Creative collaborations from afar : The benefits of independent of correct solutions", Journal of Applied Social Psychology, 31, pp.48~58 (2005)
  41. The Future of Education and Skills: Education 2030, "OECD", ~ (2018)
  42. Ormrod, J. E., "Human Learning" (1999), Prentice Hall Inc
  43. Ouyang, F., "Artificial intelligence in education : the three paradigms", Computers and Education : Artificial Intelligence, 2, pp.100020~ (2021)
  44. Razoumnikova, O. M., "Functional organization of different brain areas during convergent and divergent thinking : an EEG investigation", Cognitive Brain Research, 10, pp.11~18 (2000)
  45. Ross, P., "Intelligent tutoring systems", Journal of Computer Assisted Learning, 3, pp.194~203 (1987)
  46. Russell, S., "Artificial Intelligence : A Modern Approach" (2018), Pearson Education Limited
  47. Russell, J., "A biology attitude scale", The American Biology Teacher, 37, pp.270~273 (1975)
  48. 류미영, "딥러닝 개념을 위한 인공지능 교육 프로그램", 정보교육학회논문지, 23(6), pp.583~590 (2019), 한국정보교육학회[DOI]
  49. Shamir, G., "Teaching machine learning in elementary school", International Journal of Child-Computer Interaction, 31, pp.100415~ (2022)
  50. 신희남, "SW교육 학습자 중심 평가 사례 분석을 통한 인공지능교육의 평가 방향 고찰", 정보교육학회논문지, 24(5), pp.511~518 (2020), 한국정보교육학회[DOI]
  51. 신원섭, "초등 생물분류 학습에서 인공지능 융합교육의 적용 사례 연구", 초등과학교육, 39(2), pp.284~295 (2020), 한국초등과학교육학회[DOI]
  52. 신원섭, "온라인 학습에서 머신러닝을 활용한 초등 4학년 식물 분류 학습의 적용 사례 연구", 초등과학교육, 40(1), pp.66~80 (2021), 한국초등과학교육학회
  53. Sternberg, R. J., "Investing in creativity", American Psychologist, 51, pp.677~688 (1996)
  54. Sternberg, R., "Handbook of Intelligence", pp.611~630 (2000), Cambridge University Press
  55. Talan, T., "Artificial intelligence in education : A bibliometric study", International Journal of Research in Education and Science, 7, pp.822~837 (2021)
  56. Wang, Y., "On the cognitive process of human problem solving", Cognitive Systems Research, 11, pp.81~92 (2010)
  57. Wartman, S. A., "Medical education must move from the information age to the age of artificial intelligence", Academic Medicine, 93, pp.1107~1109 (2018)
  58. Woolf, B. P., "AI grand challenges for education", AI Magazine, 34, pp.9~ (2013)
  59. Yang, S. J. H., "Human-centered artificial intelligence in education : seeing the invisible through the visible", Computers and Education : Artificial Intelligence, 2, pp.110008~ (2021)
  60. Yildiz, C., "Exploring the relationship between creative thinking and scientific process skills of preschool children", Thinking Skills and Creativity, 39, pp.100795~ (2021)

관련 논문AI추천

인공지능 기술을 적용한 생명 영역 수업이 초등학생의 과학긍정경험에 미치는 영향신동훈, 여한나한국생물교육학회 · 생물교육2022 · 제50권 제4호인공지능(AI) 융합 생명과학 수업에 관한 생명과학 교사의 인식과 실행 방안 연구배경석, 성세연, 손연아한국생물교육학회 · 생물교육2025 · 제53권 제1호초등 생물분류 학습에서 인공지능 융합교육의 적용 사례 연구신원섭한국초등과학교육학회 · 초등과학교육2020 · 제39권 제2호과학 교육에서 인공지능의 활용 방안 제안 : 과학 탐구 활동을 중심으로최종근대한지구과학교육학회 · 대한지구과학교육학회지2025 · 제18권 제1호생성적 인공지능의 교육적 활용 방안 탐색: 생물학습을 위한 ChatGPT 활용을 중심으로권용주, 변정호뇌·AI기반교육연구소 · Brain, Digital, & Learning2023 · 제13권 제1호인공지능을 도입한 과학과 교수.학습 연구 동향의 메타분석최영미한국생물교육학회 · 생물교육2023 · 제51권 제2호

이 간행물의 다른 논문 (11건)

가상현실(VR)과 서책형 기반 생명과학 학습에서 동기, 몰입, 사회성, 중독, 어지러움의 두뇌 연결망 – fMRI 연구권승혁, 권용주, 장은영pp. 1-15언어네트워크분석을 이용한 수학과 교육과정의 핵심역량 발현 연구김성문, 이광호pp. 17-36기하학적 도형 구성에서 나타난 아동의 사고 수준강민정pp. 37-49정오 및 조언 피드백 학습지를 활용한 중학교 과학 수업에서 전기 개념 변화와 피드백 수용도 특성 연구서지윤, 류광수pp. 69-79교육에서의 권위 관련 연구동향 분석을 통한 과학교육에서의 권위임수민pp. 81-95
원문 보기