Modern statistical literacy, data science, dashboards, and automated analytics and its applications
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
With regard to the internationalization of statistics education, this paper considers first a global context concerning modern statistical literacy, data science, and dashboards. Then, it examines data discovery using automated analytics, whereby data insights may be indicated by suitable signals generated by the computer environment used. This theoretical paper, directed towards statistics educators, as well as other educators in relevant high school subjects, should make them (more) aware of this context and such analytics, supporting them to identify issues that need be considered in their teaching (and research) in order to have their students better prepared for the jobs of tomorrow.
Ključne reči:
Automated analytics / data science / statistics education / upper secondaryIzvor:
Teaching of Mathematics, 2020, 23, 1, 71-80Izdavač:
- Društvo matematičara Srbije, Beograd
Finansiranje / projekti:
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200018 (Institut za pedagoška istraživanja, Beograd) (RS-MESTD-inst-2020-200018)
Institucija/grupa
IPITY - JOUR AU - Kadijević, Đorđe AU - Stephens, Max PY - 2020 UR - http://ipir.ipisr.org.rs/handle/123456789/322 AB - With regard to the internationalization of statistics education, this paper considers first a global context concerning modern statistical literacy, data science, and dashboards. Then, it examines data discovery using automated analytics, whereby data insights may be indicated by suitable signals generated by the computer environment used. This theoretical paper, directed towards statistics educators, as well as other educators in relevant high school subjects, should make them (more) aware of this context and such analytics, supporting them to identify issues that need be considered in their teaching (and research) in order to have their students better prepared for the jobs of tomorrow. PB - Društvo matematičara Srbije, Beograd T2 - Teaching of Mathematics T1 - Modern statistical literacy, data science, dashboards, and automated analytics and its applications EP - 80 IS - 1 SP - 71 VL - 23 UR - https://hdl.handle.net/21.15107/rcub_ipir_322 ER -
@article{ author = "Kadijević, Đorđe and Stephens, Max", year = "2020", abstract = "With regard to the internationalization of statistics education, this paper considers first a global context concerning modern statistical literacy, data science, and dashboards. Then, it examines data discovery using automated analytics, whereby data insights may be indicated by suitable signals generated by the computer environment used. This theoretical paper, directed towards statistics educators, as well as other educators in relevant high school subjects, should make them (more) aware of this context and such analytics, supporting them to identify issues that need be considered in their teaching (and research) in order to have their students better prepared for the jobs of tomorrow.", publisher = "Društvo matematičara Srbije, Beograd", journal = "Teaching of Mathematics", title = "Modern statistical literacy, data science, dashboards, and automated analytics and its applications", pages = "80-71", number = "1", volume = "23", url = "https://hdl.handle.net/21.15107/rcub_ipir_322" }
Kadijević, Đ.,& Stephens, M.. (2020). Modern statistical literacy, data science, dashboards, and automated analytics and its applications. in Teaching of Mathematics Društvo matematičara Srbije, Beograd., 23(1), 71-80. https://hdl.handle.net/21.15107/rcub_ipir_322
Kadijević Đ, Stephens M. Modern statistical literacy, data science, dashboards, and automated analytics and its applications. in Teaching of Mathematics. 2020;23(1):71-80. https://hdl.handle.net/21.15107/rcub_ipir_322 .
Kadijević, Đorđe, Stephens, Max, "Modern statistical literacy, data science, dashboards, and automated analytics and its applications" in Teaching of Mathematics, 23, no. 1 (2020):71-80, https://hdl.handle.net/21.15107/rcub_ipir_322 .