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Toward a new framework for teaching algorithmic literacy

Susan Gardner Archambault (William H. Hannon Library, Loyola Marymount University, Los Angeles, California, USA)

Information and Learning Sciences

ISSN: 2398-5348

Article publication date: 19 December 2023

Issue publication date: 15 January 2024

340

Abstract

Purpose

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.

Design/methodology/approach

Eleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.

Findings

The findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.

Originality/value

This study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

Keywords

Acknowledgements

This research was part of the dissertation of the corresponding author, Proquest Dissertations and Theses Global No. 29321394, chaired by Dr Philip Molebash and approved by the LMU Institutional Review Board.

Citation

Archambault, S.G. (2024), "Toward a new framework for teaching algorithmic literacy", Information and Learning Sciences, Vol. 125 No. 1/2, pp. 44-67. https://doi.org/10.1108/ILS-07-2023-0090

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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