$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

K-평균 군집분석을 활용한 중학생의 군집화 및 특성 분석
Analysis of Characteristics of Clusters of Middle School Students Using K-Means Cluster Analysis 원문보기

한국과학교육학회지 = Journal of the Korean association for science education, v.42 no.6, 2022년, pp.611 - 619  

이재봉 (한국교육과정평가원)

초록
AI-Helper 아이콘AI-Helper

최근 교육에서 교육 데이터마이닝에 관한 관심이 높아지고 있는 시점에 과학교육에서 평가 결과를 활용하여 학생들에게 적합한 피드백을 제공하기 위해 빅데이터 분석의 적용 가능성을 탐색해 보고자 하였다. 연구에서는 국가수준 학업성취도 평가의 24문항에 응시한 2,576명의 평가 자료를 활용하여 비지도 기계학습의 한 가지 방법인 K-평균 군집분석을 이용하여 학생들을 군집화하였다. 학업성취도 평가 자료를 활용한 군집화 결과, 학생들을 6개의 군집으로 나누어 볼수 있었다. 상위권이나 하위권에 비해 중위권 학생들이 다양하게 다른 군집으로 구분됨을 알 수 있다. 군집분석의 결과를 보면, 군집화에서 가장 중요하게 영향을 주는 요인은 학업 성취였으며, 군집별로는 교육과정의 내용 영역별, 교과 역량별, 정의적 특성 면에서 서로 다른 특성을 보이고 있었다. 하위 군집에서는 정의적 영역 중에서 학습의욕이 중요하게 영향을 주고, 교과 역량 면에서는 과학적 탐구 및 문제 해결력과 과학적 의사소통 능력이 중요하게 영향을 주고 있었다. 내용 영역 면에서는 운동과 에너지와 물질 영역에 대한 성취가 군집의 특성을 구분하는 중요한 요인으로 작용하고 있었다. 따라서 평가 자료를 활용해 학생을 군집화한 후, 이러한 군집별 특성을 바탕으로 학생들에게 학습을 위한 맞춤형 피드백을 제공할 수 있을 것으로 판단된다. 본 연구에서는 이러한 연구 결과를 바탕으로 군집분석 연구 결과 활용의 가능성, 내용 영역별 균형 있는 학습, 교과 역량 증진, 과학적 태도의 향상 등 과학교육의 시사점을 제안하였다.

Abstract ▼ AI-Helper 아이콘AI-Helper

The purpose of this study is to explore the possibility of applying big data analysis to provide appropriate feedback to students using evaluation data in science education at a time when interest in educational data mining has recently increased in education. In this study, we use the evaluation da...

주제어

#국가수준 학업성취도 평가   #군집분석   #학업성취도   #맞춤형피드백  

표/그림 (9)

참고문헌 (44)

  1. Ahuja, R., Jha, A., Maurya, R., & Srivastava, R. (2019). Analysis of？educational data mining. In: Yadav, N., Yadav, A., Bansal, J., Deep,？K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization？Algorithms. Advances in Intelligent Systems and Computing, (pp.？897-907). Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_85 

    crossref

  2. Asif, R., Merceron, A., Ali, S. A., & Haider, N. G. (2017). Analyzing？undergraduate students' performance using educational data mining.？Computers & Education, 113, 177-194. 

    상세보기 crossref

  3. Baek, J. (2022). The characteristics of middle school students' understanding？about chemical equations and balancing process of chemical equations.？School Science, 15(5), 468-485. 

  4. Baek, J., Lee, J., & Choi, W. (2022). Analysis on the characteristics of？academic achievement of middle school students about 'composition？of matter': focusing on the results of the national assessment of？educational achievement(NAEA). Journal of the Korean Chemical？Society, 66(2), 136-149. 

  5. Cho, S., Ku, N., Kim, H., Lee, S., & Lee, I. (2019). OECD programme？for international students assessment : an analysis of PISA 2018 results.？Korea Institute for Curriculum and Evaluation(KICE) Research Report？RRE 2019-11. 

  6. Choi, J. & Chung, H. (2021). K-means clustering and random forest analysis？of factors In fluencing group classification by job preference. Korean？Journal of Educational Research, 59(8), 113-144. 

  7. Dong, H., Kim, G., Kang, M., Jang, E-S., Sung, K., Yang, S., Kim, S.,？Lee, J., Ku, J., Park, S., Kim, S., Choi, W., Kim, Y., Lee, K., &？Kim, H. (2018). A Study on the development of national assessment？of educational achievement according to the 2015 revised national？curriculum. Korea Institute for Curriculum and Evaluation(KICE)？Research Report RRE 2018-4. 

  8. Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A k-means？clustering algorithm. Journal of the royal statistical society. series c？(applied statistics), 28(1), 100-108. 

  9. Hyun, J. H., & Lee, J. W. (2015). A study on the effects of teachers' feedback？on high school students writing performance. The Journal of？Humanities Studies, 98, 431-455. 

  10. Joo, Y. J., Chung, Y. L., & Lee, Y. K. (2011). The structural relationship？and latent means analysis of gender among academic self-efficacy,？interest, external motivation and science achievement for high school？students. Journal of the Korean Association for Science Education,？31(6), 876-886. 

    원문보기 상세보기 crossref

  11. Kim, H., & Jung. H. (2020). A case study of yielding NAEA assessment？results of sub-domains in science applying the cognitive diagnosis？model. The Journal of Research in Education, 33(4), 89-113. 

  12. Kim, H., & Jung. H. (2021). Characterizing the academic achievement of？middle school students in science subject based on latent profile？analysis. The Journal of Curriculum and Evaluation, 24(2), 177-198. 

    상세보기

  13. Kim, K. (2017). A study on the functions of quality management of？curriculum by national assessment of educational achievement. Journal？of Curriculum Evaluation, 20(4), 145-173. 

    상세보기

  14. Kim, N. O., Park, M. A., Lee, B. N., & Sohn, W. S. (2018). The role of？teacher characteristics and feedback in developing elementary students'？affective and cognitive achievement. Journal of Curriculum and？Evaluation, 21(2), 129-151. 

    상세보기

  15. Kim, Y., & Kim, S. (2019). Finding an alternative model of the national？assessment of educational achievement based on the new trend of？academic ability and the 2015 revised curriculum. Journal of Education？& Culture, 25(2), 149-173. 

  16. Kim, Y., & Lee, S. (2021). Analysis of middle school students' responses？characteristics revealed in solving the problem related to blood？circulation in national assessment of educational achievement. Biology？Education, 49(4), 443-456. 

  17. Kim, S.-S. (2009). Automated K-means clustering and R implementation.？The Korean Journal of Applied Statistics, 22(4), 723-733. 

    원문보기 상세보기 crossref

  18. Ko, S. (2018). Predicting learning achievement using big data cluster analysis？- focusing on longitudinal study. Journal of Digital Contents Society, 19(9), 1769-1778. 

  19. Koo, D., & Jung, S. (2021). Analysis of academic achievement data using？AI cluster algorithms. Journal of The Korean Association of？Information Education, 25(6), 1005-1013. 

  20. Ku, J., Kim, K. J., Kim, J-S., Park, S. B., Park, J., Sung, K., Lee, K. S.,？Lee, S., Lee, J., Jang, E-S., Kang, J., Choi., W., Shim, K-C., & Shin,？M-K. (2019). The analysis of the characteristics and trends of academic？achievement based on the results of the national assessment of？educational achievement in the 2009 revised curriculum. Korea？Institute for Curriculum and Evaluation(KICE) Research Report RRE？2019-7. 

  21. Kwak, Y. (2017). Exploration of features of korean eighth grade students'？attitudes toward science. Journal of the Korean Association for Science？Education, 37(1), 135-142. 

  22. Kwak, Y. (2018). Effects of educational context variables on science？achievement and interest in TIMSS 2015. Journal of the Korean？Association for Science Education, 38(2), 113-122. 

  23. Lee, B. (2015). Analysis on the characteristics of national assessment of？educational achievement(NAEA) items for the science subject: with？a focus on classical mechanics. New Physics: Sae Mulli, 65(5),？485-495. 

    상세보기 crossref

  24. Lee, B., & Lee, I. (2015). Analysis on the characteristics of national？assessment of educational achievement(NAEA) items for science？subject: with a focus on optics. Journal of the Korean Association？for Science Education, 35(3), 465-475. 

  25. Lee, B., & Sohn, W. (2017). The effects of formative feedback on basic？psychological needs and classroom engagement: teacher-student？relationship as a moderator. Journal of Educational Evaluation, 30(1),？123-143. 

  26. Lee, D. N., & Lim, C. (2018). Statistical methods for testing tumor？heterogeneity. The Korean Journal of Applied Statistics, 32(3),？331-348. 

    원문보기 상세보기 crossref

  27. Lee, J. (2019). Analysis of middle school students' vision concepts by？achievement level. New Physics: Sae Mulli, 69(7), 727-736. 

    상세보기 crossref

  28. Lee, J. (2020). Analysis of middle school Students' characteristics of？understanding motion and energy: focused on analysis of national？assessment of evaluation achievement. The Journal of？Learner-Centered Curriculum and Instruction, 20(17), 815-835. 

  29. Lee, J., & Chung, H. (2019). The analysis of relations among PISA 2015？science achievement, teaching and learning on science, academic？self-efficacy: using multilevel structural equation modeling. Journal of？Research in Curriculum & Instruction, 23(2), 93-107. 

  30. Lee, J., & Chung, Y. (2014). An analysis of structural relationship among？the attitude toward science, science motivation, self-regulated learning？strategy, and science achievement in middle school students. Journal？of the Korean Association for Science Education, 34(5), 491-497. 

  31. Lee, J., & Ku, J. (2020). Analysis of the characteristics of middle school？students' science academic achievement based on the results of NAEA？in the 2009 revised curriculum. Journal of the Korean Association for？Science Education, 40(4), 429-436. 

  32. Lee, J., Ku, J. Choi, W, Shim, K. C., & Shin, M. K. (2020). Analysis of？achievement characteristics by achievement standard of the middle？school curriculum based on the national assessment of educational？achievement. Journal of the Korean Association for Science Education,？40(5), 473-483. 

    원문보기 상세보기 crossref

  33. Lee, J., & Shim, K. C. (2021). Analysis of the response characteristics on？constructed response items of national assessment of educational？achievement (NAEA) - life science domain -. Biology Education,？49(3), 431-441.？ 

    crossref

  34. Lee, M., Dong, H., Park, I., Kim, W., Seo, M., Jung, H., Kim, K., Kang,？M., Jang, E, Sung, K., Rim, H., Kim, S., Pae, J., Kim, S., Lee, J.,？Park, J., Yang, K., Kang, T., & Shin, Y. (2017). A study on the？enhancement of the NAEA system incorporating the aims of the 2015？revised national curriculum. Korea Institute for Curriculum and？Evaluation(KICE) Research Report CRE 2017-8. 

  35. Lim, S. A., & Lee, J. (2016). Affective factors as predictors of math？achievement: comparison of OECD high performing 10 countries in？math. Journal of Educational Evaluation, 29(2), 357-382. 

  36. Liou, P. Y. (2021). Students' attitudes toward science and science？achievement: An analysis of the differential effects of science？instructional practices. Journal of Research in Science Teaching, 58(3),？310-334. 

    상세보기

  37. MacQueen, J. (1967). Classification and analysis of multivariate？observations. In 5th Berkeley Symp. Math. Statist. Probability (pp.？281-297). 

  38. Ministry of Education (MOE). (2022). 1st comprehensive plan for？guaranteeing basic academic ability (2023-2027). 

  39. Park, H., & Cho, K. (2005). K-means clustering of social indicator survey？data. Journal of The Korean Data Analysis Society, 7(2), 465-476. 

  40. Park, M., & Heo, G. (2021). Development of prediction model for middle？school students' underachievement using machine learning？classification techniques: a focus on DELS. Journal of Educational？Technology, 37(3), 627-648. 

  41. R Core Team. (2022). R: A language and environment for statistical？computing. R Foundation for Statistical Computing, Vienna, Austria.？URL https://www.R-project.org/. 

  42. Sang, G., Kim, K., Park, S., Jeon, S., Park, M., Lee, J., & Min, Y. (2020).？The trends in international mathematics and science study (TIMSS):？finding from TIMSS 2019 for korea. Korea Institute for Curriculum？and Evaluation(KICE) Research Report RRE 2020-10. 

  43. Seo, M., Kang, M., Kim, G., Kim, M., Kim, S., Kim, S., Kim, H., Dong,？H., Park, S., Sung, K., Yang, S., Lee, J., Jang, E-S, Jung, H., & Seo,？E. (2018). Developing items for affective domain of national？assessment of educational achievement(NAEA) and verifying their？quality. Korea Institute for Curriculum and Evaluation(KICE) Research？Report ORM 2018-39-2. 

  44. Seo, M., Kim, K., Lee, J., Jeon, S., Kim, S., & Min, Y. (2021).？Comprehensive analysis on the results of TIMSS 2019 and its trends.？Korea Institute for Curriculum and Evaluation(KICE) Research Report？RRE 2021-5. 

저자의 다른 논문 :

관련 콘텐츠

오픈액세스(OA) 유형

FREE

Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로