The student activity meter for awareness and self-reflection
Open accessAbstract
Visualization of user actions can be used in Technology Enhanced Learning to increase awareness for learners and teachers and to support self-reflection. In this paper, we present our Student Activity Meter that visualizes learner actions. We present four design iterations and results of both quantitative and qualitative evaluation studies in real-world settings that assess the usability, use and usefulness of different visualizations. Results indicate that our tool is useful for a variety of teacher and learner needs, including awareness of time spent and resource use. Tools like SAM can also be deployed in other settings that require awareness and self-reflection, e.g. in personal informatics and health monitoring, where motivated users will value the flexible mechanisms to analyze trending data.
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- Authors
- Govaerts, S., Verbert, K., Duval, E., & Pardo, A.
- Affiliations
- KU Leuven (BE)
- Universidad Carlos III de Madrid (ES)
- Venue
- CHI '12 Extended Abstracts on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2012-05-05
- Pages
- 869-884
- OpenAlex
- W2127418831
- Cited by
- 193
- References
- 37
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 11 · 2023: 9 · 2022: 13 · 2021: 13 · 2020: 18 · 2019: 25 · 2018: 12 · 2017: 21 · 2016: 16 · 2015: 19 · 2014: 17 · 2013: 14 · 2012: 1
- FWCI
- 11.58
- Type
- conference paper
- Language
- en
- Open access
- green
- lirias.kuleuven.be
- Locations
- CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
- Lirias (submittedVersion, other-oa)
- TU/e Research Portal (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Funders
- European Commission (231396, 2007–2013, FP7 2007-2013, FP7/2007)
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- self-reflection, awareness, technology-enhanced learning, usability evaluation, personal informatics, health monitoring, data trends
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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