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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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Cites
Becoming a Self-Regulated Learner: An Overview
Zimmerman, B. J. (2002) · Theory Into Practice · doi:10.1207/s15430421tip4102_2 · Cited by 10,197
(1993) · Cited by 9,879
SUS: A 'Quick and Dirty' Usability Scale
(1996) · Usability Evaluation In Industry · doi:10.1201/9781498710411-35 · Cited by 8,989
(1993) · Elsevier eBooks · doi:10.1016/c2009-0-21512-1 · Cited by 5,552
An Empirical Evaluation of the System Usability Scale
Bangor, A., Kortum, P. T., & Miller, J. T. (2008) · International Journal of Human–Computer Interaction · doi:10.1080/10447310802205776 · Cited by 5,181
The eyes have it: a task by data type taxonomy for information visualizations
Shneiderman, B. (2002) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vl.1996.545307 · Cited by 4,833
Usability Evaluation In Industry
(1996) · CRC Press eBooks · doi:10.1201/9781498710411 · Cited by 4,445
Visual Analytics: Definition, Process, and Challenges
Keim, D. A., Andrienko, G., Fekete, J., Görg, C., Kohlhammer, J., & Mélançon, G. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-70956-5_7 · Cited by 1,091
The Think Aloud Method: A Practical Guide to Modelling Cognitive Processes
van Someren, M. (1994) · Cited by 975
The think aloud method: A practical guide to modelling cognitive processes
Solomon, P. J. (1995) · Information Processing & Management · doi:10.1016/0306-4573(95)90031-4 · Cited by 762
Research works printed but not linked: 3
- 1st International Conference on Learning Analytics and Knowledge. 2011 , February 2011 . 1st International Conference on Learning Analytics and Knowledge. 2011, February 2011.
- Personal Informatics & HCI , CHI'11 workshop. Personal Informatics & HCI, CHI'11 workshop.
- J. Benedek and T. Miner . Measuring desirability: New methods for evaluating desirability in a usability lab setting . In Proc. of UPA Conf. , 2002 . J. Benedek and T. Miner. Measuring desirability: New methods for evaluating desirability in a usability lab setting. In Proc. of UPA Conf., 2002.
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Karaoglan Yilmaz, F. G., & Yilmaz, R. (2022) · Technology, Knowledge and Learning · doi:10.1007/s10758-021-09547-w · Cited by 71
Wise, A. F., Vytasek, J., Hausknecht, S. N., & Zhao, Y. (2016) · Online Learning · doi:10.24059/olj.v20i2.783 · Cited by 72
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Beheshitha, S. S., Hatala, M., Gašević, D., & Joksimovíc, S. (2016) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2883851.2883904 · Cited by 78
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Aguilar, D. A. G., García‐Peñalvo, F. J., & Therón, R. (2014) · El Profesional de la Informacion · doi:10.3145/epi.2014.may.03 · Cited by 58
Tan, J. P.-L., Koh, E., Jonathan, C. R., & Yang, S. (2017) · Journal of Learning Analytics · doi:10.18608/jla.2017.41.7 · Cited by 58
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Drachsler, H., Slavi Stoyanov, A., & Specht, M. M. (2014) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2567574.2567617 · Cited by 9
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SBGTool v2.0: An Empirical Study on a Similarity-Based Grouping Tool for Students’ Learning Outcomes
Mohseni, Z. A., Martins, R. M., & Masiello, I. (2022) · Data · doi:10.3390/data7070098 · Cited by 8
Metadata
- 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 Graphics and Computer-Aided Design › 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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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