Revisiting Reflection in HCI: Four Design Resources for Technologies that Support Reflection
Open accessAbstract
Reflection is a commonly addressed design goal in commercial systems and in Human-Computer Interaction (HCI) research. Yet, it is still unclear what tools are at the disposal of designers who want to build systems that support reflection. Understanding the design space of reflection support systems and the interaction techniques that can foster reflection is necessary to enable building technologies that contribute to the users' well-being. In order to gain additional insight into how interactive artefacts foster reflection, we investigated past research prototypes and reflection-supporting smartphone applications (apps). Through a structured literature review and an analysis of app reviews, we constructed four design resources for reflection: temporal perspective, conversation, comparison and discovery. We also identified design patterns in past digital artefacts that implement the resources. Our work constitutes intermediate-level knowledge that is intended to inspire future technologies that better support reflection.
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Interventions that cue users to reflect on their goals and strategies via question prompts or conversational interfaces have been shown to improve outcomes in the workplace, education, and other domains.
“Interventions that cue users to reflect on their goals and strategies via question prompts or conversational interfaces have been shown to improve outcomes in the workplace [92,122,209], education [51], and other domains [17,147].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [17]
Section 5.2.2 describes conversational systems that ask questions to stimulate reflection, including a workplace chatbot. The Introduction also describes reflection-supporting systems across diverse settings. But the paper does not establish that prompts about goals and strategies improve outcomes in the workplace, education, and other domains; the Introduction says which techniques are likely to be effective remains unclear. (LLM, conf=0.85)
Experimental — accuracy not yet measuredSome HCI research on designing technology for reflection focuses on personal informatics, designing technology for self-improvement.
“Some HCI research on designing technology for reflection focuses on the domain of personal informatics, designing technology for the functional goal of supporting self-improvement [6,37].”
From Reflection Across AI-based Music Composition (2024) · cites this paper as [6]
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- Authors
- Bentvelzen, M., Woźniak, P. W., Herbes, P. S. F., Stefanidi, E., & Niess, J.
- Affiliations
- Utrecht University (NL)
- Chalmers University of Technology (SE)
- University of Bremen (DE)
- University of St.Gallen (CH)
- Venue
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
- Published
- 2022-03-29
- Volume
- 6
- Issue
- 1
- Pages
- 1-27
- ISSN
- 2474-9567 (ISSN-L)
- OpenAlex
- W4221112461
- Cited by
- 137
- References
- 103
- Citations by year
- 2026: 49 · 2025: 41 · 2024: 25 · 2023: 20 · 2022: 2
- FWCI
- 10.87
- Type
- journal article
- Language
- en
- Open access
- green
- research.chalmers.se
- Locations
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (publishedVersion)
- Alexandria (UniSG) (University of St.Gallen) (acceptedVersion)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Keywords
- reflection, design space, interaction techniques, mobile application, app reviews, time perspective, conversation, comparison, discovery, design patterns, user well-being, digital artifacts
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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