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Teachers’ Perspectives on Culturally-Relevant Computing: Principles and Processes

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Abstract

Culturally-relevant computing has been discussed as a way to promote K-12 Computer Science education and address ongoing challenges related to diversity, equity, and inclusion. What is not well understood about the practice of culturally-relevant computing, however, is how to bring together existing cultural frameworks and Computer Science curricula effectively. To help address this area, focus group interviews were conducted with ten (n = 10) in-service Computer Science teachers working in the multicultural context of Hawai’i. The focus group sessions were designed to reveal teachers’ perceptions of the principles and processes involved in designing and implementing culturally-relevant CS lessons and resources. Results revealed a number of key themes, including important variations in the practitioners’ philosophical and operational approaches to culturally-relevant computing. The paper ends with a detailed discussion of the findings and their implications for designers, practitioners, and researchers working in Computer Science education.

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Funding

This work was supported by the National Science Foundation through the Division of Research on Learning (Grant #2122874).

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Authors and Affiliations

  1. Department of Learning Design and Technology, University of Hawai‘i at Mānoa, 1776 University Ave, Honolulu, HI, 96822, USA

    Daniel L. Hoffman, Peter Leong & Seungoh Paek

  2. Kamakakūokalani Center for Hawaiian Studies, University of Hawai‘i at Mānoa, 2645 Dole Street, Honolulu, HI, 96822, USA

    Rochelle Piʻilani H. Ka’aloa

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  1. Daniel L. Hoffman
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Correspondence to Daniel L. Hoffman.

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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Human Studies Program at the University of Hawaii at Mānoa (November 22, 2021/No. 2021–00544).

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Hoffman, D.L., Leong, P., Ka’aloa, R.P.H. et al. Teachers’ Perspectives on Culturally-Relevant Computing: Principles and Processes. TechTrends 66, 423–435 (2022). https://doi.org/10.1007/s11528-022-00733-w

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