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Erschienen in:
Introduction—What is This Guide About? Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

9. The Pedagogical Chasm in Data Science Education

verfasst von : Orit Hazzan, Koby Mike

Erschienen in: Guide to Teaching Data Science

Verlag: Springer International Publishing

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Abstract

As an interdisciplinary discipline, data science poses many challenges for teachers. This chapter presents the story of one of them, specifically of the adoption of a new data science curriculum developed in Israel for high school computer science pupils, by high school computer science teachers. We analyze the adoption process using the diffusion of innovation and the crossing the chasm theories. Accordingly, we first present the diffusion of innovation theory (Sect. 9.1) and the crossing the chasm theory (Sect. 9.2). Then, we present the data science for high school curriculum case study (Sect. 9.3). Data collected from teachers who learned to teach the program reveals that when a new curriculum is adopted, a pedagogical chasm might exist (i.e., a pedagogical challenge that reduces the motivation of the majority of teachers to adopt the curriculum) that slows down the adoption process of the innovation (Sect. 9.4). Finally, we discuss the implications of the pedagogical chasm for data science education (Sect. 9.5).

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Vorheriges Kapitel Data Science as a Research Method
Nächstes Kapitel The Data Science Workflow
Fußnoten
2
See Sect. 7.​3 for more details.
 
3
Full name appears with permission.
 
4
Full name appears with permission.
 
5
Full name appears with permission.
 
Literatur
Avidov-Ungar, O., & Eshet-Alkakay, Y. (2011). The islands of innovation model: Opportunities and threats for effective implementation of technological innovation in the education system. Issues in Informing Science and Information Technology, 8, 363–376.CrossRef
Bennett, J., & Bennett, L. (2003). A review of factors that influence the diffusion of innovation when structuring a faculty training program. The Internet and Higher Education, 6(1), 53–63.CrossRef
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Gal-Ezer, J., Beeri, C., Harel, D., & Yehudai, A. (1995). A high school program in computer science. Computer, 28(10), 73–80.CrossRef
Hazzan, O., Gal-Ezer, J., & Blum, L. (2008). A model for high school computer science education: The four key elements that make it! In Proceedings of the 39th SIGCSE technical symposium on computer science education, pp. 281–285.
Hazzan, O., & Zelig, D. (2016). Adoption of innovation from the business sector by post-primary education organizations. Management in Education, 30(1), 19–28.CrossRef
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Lee, J., Tan, E., Barrow, J., Bocala, C., & Seymour, B. (2021). Crossing the innovation chasm: Identifying facilitators and barriers to early adoption of the global health starter kit curriculum. Annals of Global Health, 87(1).
Mike, K., Hazan, T., & Hazzan, O. (2020). Equalizing data science curriculum for computer science pupils. In Koli Calling’20: Proceedings of the 20th Koli Calling international conference on computing education research, pp. 1–5.
Mike, K., & Hazzan, O. (2021). How can computer science educators benefit from data science education? In Proceedings of the 52nd ACM technical symposium on computer science education, pp. 1363–1363.
Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. The Teachers College Record, 108(6), 1017–1054.CrossRef
Rogers, E. M. (1962). Diffusion of innovations. Free Press.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Sahin, I. (2006). Detailed review of Rogers’ diffusion of innovations theory and educational technology-related studies based on Rogers’ theory. Turkish Online Journal of Educational Technology-TOJET, 5(2), 14–23.MathSciNet
Scott, S., & McGuire, J. (2017). Using diffusion of innovation theory to promote universally designed college instruction. International Journal of Teaching and Learning in Higher Education, 29(1), 119–128.
West, R. E., Waddoups, G., & Graham, C. R. (2007). Understanding the experiences of instructors as they adopt a course management system. Educational Technology Research and Development, 55(1), 1–26.CrossRef
Zelig, D. (2011). Adoption of innovation from the business sector by secondary educational organizations [PhD Thesis]. Technion.
Metadaten
Titel
The Pedagogical Chasm in Data Science Education
verfasst von
Orit Hazzan
Koby Mike
Copyright-Jahr
2023
Buch
Guide to Teaching Data Science

Print ISBN: 978-3-031-24757-6

Electronic ISBN: 978-3-031-24758-3

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-031-24758-3_9

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