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ERIC Number: EJ1354521
Record Type: Journal
Publication Date: 2022
Pages: 25
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1570-1824
EISSN: EISSN-1570-1824
Available Date: N/A
Introducing High School Statistics Teachers to Predictive Modelling and APIs Using Code-Driven Tools
Fergusson, Anna; Pfannkuch, Maxine
Statistics Education Research Journal, v21 n2 Article 8 2022
Tasks for teaching predictive modelling and APIs often require learners to use code-driven tools. Minimal research, however, exists about the design of tasks that support the introduction of high school students and teachers to these new statistical and computational methods. Using a design-based research approach, a web-based task was developed. The task was constructed using our design framework and implemented within a face-to-face professional development workshop involving six high school statistics teachers. The teachers were guided through the process of developing a prediction model using: an informal approach; visual prediction intervals; data about movie ratings from an API; and R code that ran in the browser. Our findings from this exploratory study indicate that the web-based task supported the development of new statistical and computational ideas related to predictive modelling and APIs.
International Association for Statistical Education and the International Statistical Institute. PO Box 24070, 2490 AB The Hague, The Netherlands. Tel: +31-70-3375737; Fax: +31-70-3860025; e-mail: isi@cbs.nl; Web site: https://iase-web.org/ojs/SERJ
Publication Type: Journal Articles; Reports - Research; Tests/Questionnaires
Education Level: High Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: New Zealand
Grant or Contract Numbers: N/A
Author Affiliations: N/A