Understanding Personal Data Tracking and Sensemaking Practices for Self-Directed Learning in Non-Classroom and Non-Computer-Based Contexts

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationCHI '23
Subtitle of host publicationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems
EditorsAlbrecht Schmidt, Kaisa Väänänen, Tesh Goyal, Per Ola Kristensson, Anicia Peters, Stefanie Mueller, Julie R. Williamson, Max L. Wilson
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
ISBN (print)9781450394215
Publication statusPublished - 2023

Publication series

NameCHI
PublisherAssociation for Computing Machinery

Conference

Title2023 CHI Conference on Human Factors in Computing Systems (CHI ’23)
LocationHybrid
PlaceGermany
CityHamburg
Period23 - 28 April 2023

Abstract

Self-directed learning is becoming a significant skill for learners. However, learners may suffer from difficulties such as distractions, a lack of motivation, and so on. While self-tracking technologies have the potential to address these challenges, existing tools and systems mainly focused on tracking computer-based learning data in classroom contexts. Little is known about how students track and make sense of their learning data from non-classroom learning activities and which types of learning data are personally meaningful for learners. In this paper, we conducted a qualitative study with 24 users of Timing, a mobile learning tracking application in China. Our findings indicated that users tracked a variety of qualitative learning data (e.g., videos, photos of learning materials, and emotions) and made sense of this data using different strategies such as observing behavioral and contextual details in videos. We then provided implications for designing non-classroom and non-computer-based personal learning tracking tools. © 2023 ACM.

Research Area(s)

  • non-classroom-based learning, self-directed learning, non-computer-based learning, self-tracking, behavior change, personal informatics

Citation Format(s)

Understanding Personal Data Tracking and Sensemaking Practices for Self-Directed Learning in Non-Classroom and Non-Computer-Based Contexts. / Rong, Ethan Z.; Zhou, Mo Morgana; Gao, Ge et al.
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. ed. / Albrecht Schmidt; Kaisa Väänänen; Tesh Goyal; Per Ola Kristensson; Anicia Peters; Stefanie Mueller; Julie R. Williamson; Max L. Wilson. New York, NY: Association for Computing Machinery, 2023. 718 (CHI).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review