arXiv cs.CY· Robert Whyte, Manni Cheung, Katharine Childs, Jane Waite, Sue Sentance·· 3 天前AI 评分15
K-12 教育中的数据素养发展轨迹：一项 84 项研究的系统综述
Mapping data literacy trajectories in K-12 education
AI 导读
一项对 84 项研究的系统综述提出了数据范式框架，从逻辑（基于知识或数据驱动的系统）与可解释性（透明或不透明模型）两个维度对 K-12 学习活动进行分类，并据此描绘出学习者在不同范式间的四条学习轨迹。研究者希望这些轨迹能帮助研究者和教育者反思数据素养如何随学习情境而变化，并为 CS 教育内外的数据素养学习环境设计提供参考。
正文 · 原文
Abstract:Data literacy skills are fundamental in computer science education. However, understanding how data-driven systems work represents a paradigm shift from traditional rule-based programming. We conducted a systematic literature review of 84 studies to understand K-12 learners' engagement with data across disciplines and contexts. We propose the data paradigms framework that categorises learning activities along two dimensions: (i) logic (knowledge-based or data-driven systems), and (ii) explainability (transparent or opaque models). We further apply the notion of learning trajectories to visualize the pathways learners follow across these distinct paradigms. We detail four distinct trajectories as a provocation for researchers and educators to reflect on how the notion of data literacy varies depending on the learning context. We suggest these trajectories could be useful to those concerned with the design of data literacy learning environments within and beyond CS education.
| Comments: | Presented at the Data Literacy for the 21st Century: Perspectives from Visualization, Cognitive Science, Artificial Intelligence, and Education CHI '26 workshop |
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2603.28317 [cs.CY] |
| (or arXiv:2603.28317v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2603.28317 arXiv-issued DOI via DataCite |
Submission history
From: Robert Whyte [view email]
[v1]
Mon, 30 Mar 2026 11:38:07 UTC (595 KB)
[v2]
Wed, 14 Oct 2026 08:26:21 UTC (595 KB)
来源：arXiv cs.CY · arxiv.org