Understanding college students’ cross-device learning behavior in the wild: Device ecologies, physical configurations, usage patterns, and attention issues

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2025-02-04 DOI:10.1016/j.compedu.2025.105259
Qingchuan Li, Zhao Xu, Yang Chen
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Abstract

The use of multiple devices to access educational materials is becoming more prevalent, offering benefits for both formal and informal learning. However, research on college students' cross-device learning patterns and the challenges remains limited. This study employed a two-week diary study method and follow-up interviews with 36 college students. Comprehensive data were collected from 374 cross-device learning activities, including text, voice recordings, and photos, offering valuable insights into participants' cross-device learning behaviors in terms of the device ecologies, physical configurations, usage patterns, and attention issues. Regarding device ecology, students typically used two to three types of education devices, with laptops and desktops serving as primary tools, and smartphones, tablets and smartwatches as secondary aids. Physically, devices were often arranged vertically and positioned in ways that required body or head movement. The students’ usage patterns revealed a preference of completing tasks simultaneously rather than sequentially. Five key workflow patterns were identified, from most to least prevalent: integrated, partition, migrated, expanded and cloned. Common combinations of these workflows included the integrated-partition, integrated-expanded, and integrated-migrated patterns. Instant messaging applications were the most frequently used method for information and data transfer. In terms of attention issues, most participants prioritized their attention allocation. Endogenous attention shifts occurred slightly more frequently than exogenous shifts, though exogenous shifts were more disruptive to learning efficiency and motivation. These findings offer valuable insights for developing future cross-device learning platforms, particularly those focused on enhancing attention management and improving learning experiences.
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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