Acknowledgement
이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2022R1A2C1011366).
References
- 강정수, 김형범(2018). 물의 순환 시스템 장치 개발 및 수업 프로그램 효과 분석. 대한지구과학교육학회지, 11(1), 21-37. https://doi.org/10.15523/JKSESE.2018.11.1.21
- 교육부(2015a). 2015 개정 수학 교사용 지도서. 교육부.
- 교육부(2015b). 2015 개정 과학 교사용 지도서. 교육부.
- 교육부(2022). 초.중등학교 교육과정. 교육부 고시 2022-33호.
- 김태선, 김범기(2002). 중고등학생들의 과학 그래프 작성 및 해석 능력. 한국과학교육학회지, 22(4), 768-778.
- 김하늘, 김성희(2021). 데이터 시각화 리터러시 평가 테스트. 한국정보통신학회 여성 ICT 학술대회 논문집, 2021(8), 123-126.
- 김호연, 박기락, 김형범(2023). 3 차원 데이터 활용 웹기반 STEAM 프로그램의 효과: 지구과학 I 의'지질 단원'을 중심으로. 대한지구과학교육학회지, 16(2), 247-260. https://doi.org/10.15523/JKSESE.2023.16.2.247
- 이진봉, 이기영, 안희수(2007). 지구과학 교과에서 사용되는 그래프의 유형 및 특징 분석. 한국과학교육학회지, 27(4), 285-296. https://doi.org/10.14697/JKASE.2007.27.4.285
- 임현미(2008). 고등학생들의 생물 그래프 이해와 작성 능력 조사. 서울대학교 대학원 석사학위논문.
- 홍석영, 한신, 김형범(2020). 데이터 기반 STEAM 교육을 통한 문제 해결 과정 분석: 대기대순환과 표층 해류내용을 중심으로. 대한지구과학교육학회지, 13(3), 330-343. https://doi.org/10.15523/JKSESE.2020.13.3.330
- Ali, S. M., Gupta, N., Nayak, G. K., & Lenka, R. K. (2016). Big data visualization: Tools and challenges. 2nd International Conference on Contemporary Computing and Informatics, 656-660.
- Diamond, S. (2011). Data visualization: Materiality & mediation. ISEA2011 Istanbul Conference Proceedings.
- Elsden, C., Kirk, D. S., & Durrant, A. C. (2016). A quantified past: Toward design for remembering with personal informatics. Human-Computer Interaction, 31(6), 518-557. https://doi.org/10.1080/07370024.2015.1093422
- Embarak, D. O., & Embarak, O. (2018). The importance of data visualization in business intelligence. In Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI Systems (pp. 85-124).
- Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press.
- Fry, B. J. (2004). Computational information design. Doctoral Dissertation, Massachusetts Institute of Technology.
- Gerela, P., Mishra, P. N., & Vipat, R. (2022). Study on data visualization: It's importance in education sector. International Journal of Health Sciences, 6(S3), 6298-6305. https://doi.org/10.53730/ijhs.v6nS3.7393
- Gobert, J. D., Sao Pedro, M., Raziuddin, J., & Baker, R. S. (2013). From log files to assessment metrics: Measuring students' science inquiry skills using educational data mining. Journal of the Learning Sciences, 22(4), 521-563. https://doi.org/10.1080/10508406.2013.837391
- Goldman, S. R. (2016). Visualizing data in educational research: Guidelines, issues, and applications. Review of Educational Research, 86(2), 163-190.
- Huang, T. Y., & Zhao, B. (2020). Tidyfst: Tidy verbs for fast data manipulation. Journal of Open Source Software, 5(52), 2388.
- Hudiburgh, L., & Garbinsky, D. (2020). Data visualization: Bringing data to life in an introductory statistics course. Journal of Statistics Education, 28(3), 262-279. https://doi.org/10.1080/10691898.2020.1796399
- Imre, M., Chang, W., Wang, S., Trinter, C. P., & Wang, C. (2020). GraphVisual: Design and evaluation of a web-based visualization tool for teaching and learning graph visualization. Proceedings of American Society for Engineering Education Annual Conference.
- Kennedy, H., & Allen, W. (2017). Data visualisation as an emerging tool for online research. The Sage Handbook of Online Research Methods, 307-326.
- Kirk, A. (2016). Data visualisation: A handbook for data driven design. Sage Publications.
- Lindquist, E. (2011). Surveying the world of visualization. Australian National University.
- Murumba, J. (2022). Learning analytics and educational data visualization in the digital era. Journal of Innovations in Data Science and Big Data Management, 1(1), 1-7. https://doi.org/10.46610/JIDSBDM.2022.v01i01.001
- Rodrigues, S. (2020). Unexplored and familiar: Experiencing interactive spatio-temporal visualization. In 2020 15th Iberian Conference on Information Systems and Technologies, 1-6.
- Saraiya, P., & North, C. (2005). Understanding the role of visualizations in data science: An exploratory study. Journal of Visual Languages & Computing, 16(3), 215-233.
- Signer, J., & Fieberg, J. R. (2021). A fresh look at an old concept: Home-range estimation in a tidy world. PeerJ, 9, e11031.
- Stone, M. (2009). Challenge for the humanities. Working Together or Apart: Promoting the Next Generation of Digital Scholarship, 43.
- Tufte, E. R. (2001). The visual display of quantitative information. Graphics Press.
- Ullmer, B., & Ishii, H. (2019). Tangible interfaces for manipulating aggregates of digital information. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 632.
- Wang, Y. (2019). Tidy tools for supporting fluent workflow in temporal data analysis. Doctoral Dissertation, Monash University.
- Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59(10), 1-23. https://doi.org/10.18637/jss.v059.i10