پیاده‌سازی آموزش علم‌داده در مدرسه : فرصت ها و چالش ها

نوع مقاله : مقاله پژوهشی

نویسندگان

1 بخش آموزش ریاضی - دانشکده ریاضی و کامپیوتر- دانشگاه شهید باهنر کرمان پژوهشکده ریاضی ماهانی- پژوهشگاه افضلی پور - دانشگاه شهید باهنر کرمان

2 بخش آموزش ریاضی - دانشکده ریاضی و کامپیوتر- دانشگاه شهید باهنر کرمان

چکیده

حجم بسیار بالا و ذخیره داده‌ها در دنیای امروز، دسترسی مردم به داده‌ها را افزایش داده است. با این روند مشکلاتی از جمله تفسیر اشتباه داده‌ها، تصمیم‌گیری در تمام عرصه‌های تاثیرگذارِ کار با داده را با چالش مواجه می‌کند. نیاز به نیروی کار در این زمینه بسیار پر تقاضا است و تجزیه و تحلیلگری داده‌ها یکی از شغل‌های پر درآمد در جهان می‌باشد. بنابراین آموزش علم‌داده و تجزیه و تحلیل داده‌ها به دانش‌آموزان به‌عنوان نیروی کار آینده امری جدی است و بایستی در برنامه درسی مدارس جایگاه مناسبی داشته باشد. هدف این پژوهش بررسی چالش‌های اساسی آموزش علم‌داده در آموزش مدرسه‌ای که شامل برنامه درسی، داده‌ها و فناوری، می‌باشد. تعریف علم‌داده در بررسی این چالش‌ها مؤثر است. مهم‌ترین موضوعی که در تعریف علم‌داده دیده ‌می‌شود، کشف الگوها و ساختن دانش با استفاده از داده‌ها با توجه به توانایی مهارت در رشته‌های موضوعی از جمله ریاضی، آمار و علوم کامپیوتر است. با توجه به تعریف علم‌داده تغییر در برنامه درسی ‌می‌تواند در سه درس ریاضیات، آمار و علوم کامپیوتر مورد توجه قرار گیرد. بیشترین تغییرات در زمینه برنامه درسی، ‌می‌تواند در ریاضیات مدرسه ای انجام شود.

کلیدواژه‌ها

موضوعات


[1] I. O. Adisa, D. Herro, O. Abimbade and G. Arastoopour Irgens, Engaging elementary students in data science practices, Information and Learning Sciences, 125 no. 7/8 (2024) 513–544.
[2] A. Bargagliotti, C. Franklin, P. Arnold, R. Gould, S. Johnson, L. Perez and D. Spangler, Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report II: A Framework
for Statistics and Data Science Education, American Statistical Association and National Council of Teachers of Mathematics, 2020.
[3] B. Baumer, A data science course for undergraduates: thinking with data, Amer. Statist., 69 no. 4 (2015) 334–342.
[4] R. Biehler, D. Frischemeier, C. Reading and j. M. Shaughnessy, Reasoning about data, In: D. Ben-Zvi, K.Makar and J. Garfield, editors, International handbook of research in statistics education, Cham, Springer, (2017) 139–192.
[5] W. Burr, F. Chevalier, C. Collins, A. L. Gibbs, R. Ng and C. J. Wild, Computational skills by stealth in introductory data science teaching,Teach Stat., 43 (2021) S34–S51.
[6] G. Cattaneo, G. Micheletti, M. Glennon, C. La Croce and C. Mitta, The European data market monitoring tool: Key facts & figures, first policy conclusions, data landscape and quantified stories: d2.9 Final study report, European Commission, B-1049 Brussels, 2020.
[7] W. S. Cleveland, Data science: An action plan for expanding the technical areas of the field of statistics, International Statistics Review, 69 no. 1 (2001) 21–26.
[8] J. Engel, Statistical literacy for active citizenship: a call for data science education, Statistics Education Research Journal, 16 no. 1 (2017) 44–49.
[9] T. Erickson, M. Wilkerson, W. Finzer and F. Reichsman, Data Moves, Technology Innovations in Statistics Education, 12 no 1 (2019).
[10] W. Finzer, The data science education dilemma, Technology Innovations in Statistics Education, 7 no. 2 (2013) 1–9.
[11] D. Frischemeier, R. Biehler, S. Podworny, and L. Budde, A first introduction to data science education in secondary schools: Teaching and learning about data exploration with CODAP using survey data, Teach. Stat., 43 (2021) S182–S189.
[12] S. Gutta, Data science: The 5 V’s of big data, (2020), Available at: https://medium.com/analytics-vidhya/the-5-vsof-big-data-2758bfcc51d (accessed 28 July 2024).
[13] S. Hedges and K. Given, Addressing confirmation bias in middle school data science education, Found. Data Sci., 5 no. 2 (2023) 223–243.
[14] K. Holstein, B. M. McLaren and V. Aleven, Co-designing a real-time classroom orchestration tool to support teacher – AI complementarity, Journal of Learning Analytics, 6 no. 2 (2019) 27–52.
[15] IDSSP Curriculum Team. Curriculum Frameworks for Introductory Data Science, 2019.
[16] C. E. Konold, R. Coulter and A. Feldman, Engaging students with data, Learning & Leading with Technology, 28 no. 3 (2000) 50–55.
[17] D. Kadijevich, Interactive displays: Use of interactive charts and dashboards in education, In: A. Tatnall (Ed.), Encyclopedia of education and information technologies, Cham, Switzerland, Springer, 2019.
[18] D. Kadijevich and M. Stephens, Modern statistical literacy, data science, dashboards, and automated analytics and its applications, Teaching of Mathematics, 23 no. 1 (2020) 71–80.
[19] M. K. Kjelvik and E. H. Schultheis, Getting messy with authentic data: Exploring the potential of using data from scientific research to support student data literacy, CBE Life Sci. Educ., 18 (2019) 1–8.
[20] T. Lamar and J. Boaler, The importance and emergence of K-12 data science, Phi Delta Kappan, 103 (2021) 49–53.
[21] N. Lazar and C. Franklin, The Big Picture: Preparing Students for a Data-centric World, CHANCE, 28 (2015) 43–45.
[22] V. R. Lee and V. Delaney, Identifying the Content, Lesson Structure, and Data Use Within Pre-collegiate Data Science Curricula, J. Sci. Educ. Techno. 31 (2022) 81–98.
[23] H. S. Lee and T. Harrison, Trends in Teaching Advanced Placement Statistics: Results from a National Survey, Journal of Statistics and Data Science Education, 29 no.3 (2021) 317–327.
[24] V. R. Lee, D. R. Pimentel, R. Bhargava, and C. D’Ignazio, Taking data feminism to school: A synthesis and review of pre‐collegiate data science education projects, British Journal of Educational Technology, 53 no. 5 (2022) 1096–1113.
[25] V. R. Lee, M. H. Wilkerson and K. Lanouette, A call for a humanistic stance toward K–12 data science education, Educational Researcher, 50 no. 9 (2021) 664–672. https://doi.org/10.3102/0013189X211048810
[26] M. Liston, A. M. Morrin, T. Furlong and L. Griffin, Integrating Data Science and the Internet of Things Into Science, Technology, Engineering, Arts, and Mathematics Education Through the Use of New and Emerging Technologies, Front. Educ., 7 (2022) 757866.
[27] M. Loukides, What Is Data Science? Cambridge, MA: O’Reilly Press, 2012.
[28] W. Martinez and D. LaLonde, Data science for everyone starts in kindergarten: strategies and initiatives from the American statistical association, Harvard Data Science Review [Internet], 2 no. 3 (2020).
https://hdsr.mitpress.mit.edu/pub/wkhg4f7a
[29] R. Moeti, A. Rafiepour and M. R. Fadaee, The role of technology in school data science, In Thirteenth Congress of the European Society for Research in Mathematics Education (CERME13), no. 24, Alfréd Rényi Institute of Mathematics, ERME, 2023.
[30] L. Muñiz-Rodríguez, L. J. Rodríguez-Muñiz and A. Alsina, Deficits in the Statistical and Probabilistic Literacy of Citizens: Effects in a World in Crisis, Mathematics, 8 no. 11 (2020) 1872.
[31] G. Nadzinski, B. Gerazov, S. Zlatinov, T. Kartalov, M. M. Dimitrovska, H. Gjoreski, R. Chavdarov, Z. Kokolanski, I. Atanasov, J. Horstmann, U. Sterle and M. Gams, Data Science and Machine Learning Teaching Practices with Focus on Vocational Education and Training, Informatics in Education, 22 no. 4 (2023) 671–690.
[32] D. Rose, Data Science: Create Teams That Ask the Right Questions and Deliver Real Value, New York: Apress, 2016.
[33] E. H. Schultheis and M. K. Kjelvik, Data Nuggets:Bringing real data into the classroom to unearth students’ quantitative and inquiry skills,American Biology Teacher, 77 no. 1 (2015) 19–29.
[34] I. Song and Y. Zhu, Big data and data science: What should we teach? Expert Systems, 33 no. 4 (2016) 364–373.
[35] R. Thompson and G. Arastoopour Irgens, Data Detectives: A data science program for middle grade learners, Journal of Statistics and Data Science Education, 30 no. 1 (2022) 29–38.
[36] T. Weiland and A. Sundrani, Opportunities for K-8 Students to Learn Statistics Created by States’ Standards in the United States, Journal of Statistics and Data Science Education, 30 no.2 (2022) 165–178.
[37] M. B. Wilson and C. Turner, editors.The philosophy of Werner Herzog, Lexington Books, Washington, DC, 2020.
[38] M. S. Zakaria, Data science education programmes in Middle Eastern institutions: A survey study, IFLA Journal, 49 no. 1 (2023) 157–179.
[39] م. ق. وحیدی اصل، پنجاه ‌سال علم‌داده، فرهنگ و اندیشه ریاضی، 43 شماره 1 (1403) 273--327.