short-paper

Drafting a Data Science Curriculum for Secondary Schools

Authors:

Birte Heinemann,

Carsten Schulte,

Daniel Frischemeier,

Susanne Podworny,

Thomas WassongAuthors Info & Claims

Koli Calling '18: Proceedings of the 18th Koli Calling International Conference on Computing Education Research

Article No.: 17, Pages 1 - 5

https://doi.org/10.1145/3279720.3279737

Published: 22 November 2018 Publication History

Abstract

Data science as the art of generating information and knowledge from data is increasingly becoming an important part of most operational processes. But up to now, data science is hardly an issue in German computer science education at secondary schools. For this reason, we are developing a data science curriculum for German secondary schools, which first guidelines and ideas we present in this paper. The curriculum is designed as interdisciplinary approach between maths and computer science education, with also a strong focus on societal aspects. After a brief discussion of important concepts and challenges in data science, a first draft of the curriculum and an outline of a data science course for upper secondary schools accompanying the development are presented.

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Index Terms

Drafting a Data Science Curriculum for Secondary Schools
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Model curricula

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Koli Calling '18: Proceedings of the 18th Koli Calling International Conference on Computing Education Research

November 2018

207 pages

ISBN:9781450365352

DOI:10.1145/3279720

Conference Chairs:
Mike Joy
University of Warwick, United Kingdom
,
Petri Ihantola
University of Helsinki, Finland

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 22 November 2018

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Koli Calling '18

Koli Calling '18: 18th Koli Calling International Conference on Computing Education Research

November 22 - 25, 2018

Koli, Finland

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Overall Acceptance Rate 80 of 182 submissions, 44%

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Register J(2023)Design Considerations for Facilitating Equitable Participation in an Ethical Data Science Course for High School StudentsJournal of Urban Mathematics Education10.21423/jume-v16i2a52216:2(32-67)Online publication date: 31-Dec-2023
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https://dl.acm.org/doi/10.1145/3614100
Farrell KWatts JRobertson JLawson T(2023)A Flexible School and College Level Qualification in Data ScienceProceedings of the 18th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3605468.3609769(1-2)Online publication date: 27-Sep-2023
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Yang YZheng ZZhu GSalas‐Pilco S(2023)Analytics‐supported reflective assessment for 6th graders' knowledge building and data science practices: An exploratory studyBritish Journal of Educational Technology10.1111/bjet.1330854:4(1025-1045)Online publication date: 14-Mar-2023
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Peña-Ayala A(2023)Educational Data Science: An “Umbrella Term” or an Emergent Domain?Educational Data Science: Essentials, Approaches, and Tendencies10.1007/978-981-99-0026-8_3(95-147)Online publication date: 30-Apr-2023
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