The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
A conceptual framework for context-driven self-adaptive intelligent user interface based on Android
Open accessAbstract
Adaptive User Interface (AUI) can change its layout, appearance, and/or elements based on the needs of its user requirements and current usage context. The AUIs are used in state-of-the-art software products, applications for mobile devices, and websites. Moreover, AUI is an emerging research field in a mobile context, as it can enhance usability, performance, and user satisfaction. This study aims to propose a conceptual framework for developing a real-time self-adaptive user interface based on the Android Operating System (OS). Furthermore, the focus is on developing the core algorithms for the modules of the proposed framework. To evaluate the performance of the proposed framework, three case studies have been designed based on the daily and weekly activities of the user. Moreover, an expert-based validation approach is employed to obtain the expert’s feedback regarding the proposed framework. The result indicates that the proposed framework helps improve user satisfaction and experience by making an intelligent mobile device interface. The results of the framework’s evaluation and validation show the proposed framework’s feasibility and effectiveness. We conclude that the current work is beneficial in filling the identified research gap. Moreover, this research shows the significance of an adaptive interface in an Android OS-based context. In addition, it not only helps in improving the user interest and satisfaction but also enhances the overall performance of the mobile device.
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“Furthermore, current research often lacks comprehensive validation processes for proposed AUI models, tending to focus more on single-product solutions (Ali et al. 2024).”
From AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems (2024) · cites this paper as Ali et al. 2024
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“An observation also found in recent research (Ali et al. 2024) reinforces the existing gap in the field; many studies in this domain have failed to conduct a validation process for their proposed models or frameworks and have often focused exclusively on a single specific product.”
From AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems (2024) · cites this paper as Ali et al. 2024
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1 retracted
Khan, I. U., & Khusro, S. (2022) · Soft Computing · doi:10.1007/s00500-021-06705-1 · Cited by 10
RetractedModeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation
Arcaini, P., Riccobene, E., & Scandurra, P. (2015) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1109/seams.2015.10 · Cited by 242
Applying Machine Learning in Self-adaptive Systems
Gheibi, O., Weyns, D., & Quin, F. (2020) · ACM Transactions on Autonomous and Adaptive Systems · doi:10.1145/3469440 · Cited by 233
Model-based adaptive user interface based on context and user experience evaluation
Hussain, J., Hassan, A. U., Bilal, H. S. M., Ali, R., Afzal, M., Hussain, S., Bang, J., Baños, O., & Lee, S. (2018) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-018-0258-2 · Cited by 178
Integrated model-driven development of self-adaptive user interfaces
Yigitbas, E., Jovanovikj, I., Biermeier, K., Sauer, S., & Engels, G. (2020) · Software & Systems Modeling · doi:10.1007/s10270-020-00777-7 · Cited by 69
Khan, A., & Khusro, S. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-018-7094-y · Cited by 63
Software development with feature toggles: practices used by practitioners
Mahdavi-Hezaveh, R., Dremann, J., & Williams, L. A. (2021) · Empirical Software Engineering · doi:10.1007/s10664-020-09901-z · Cited by 47
BlindSense: An Accessibility-inclusive Universal User Interface for Blind People
Khan, A., Khusro, S., & Alam, I. (2018) · Engineering, Technology & Applied Science Research · doi:10.48084/etasr.1895 · Cited by 44
A Conceptual framework for Adaptive User Interfaces for older adults
Machado, E., Singh, D., Cruciani, F., Chen, L., Hanke, S., Salvago, F., Kropf, J., & Holzinger, A. (2018) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2018.8480407 · Cited by 39
Mobile Devices Interface Adaptivity Using Ontologies
Iqbal, M. W., Naqvi, M. R., Khan, M. A., Khan, F. N., & Whangbo, T. K. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.023239 · Cited by 37
Research works printed but not linked: 1
- Braham A, Buendía F, Khemaja M, Gargouri F (2019) Generation of adaptive mobile applications based on design patterns for user interfaces. Multidiscip Digit Publ Inst Proc 31(1):19
Cited by
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Grand Challenges of Smart Technology for Older Adults
Zhou, J., Salvendy, G., Boot, W. R., Charness, N. H., Czaja, S. J., Gao, Q., Holzinger, A., Ntoa, S., Rau, P. P., Rogers, W. A., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2457003 · Cited by 54
Carrera-Rivera, A., Larrinaga, F., Lasa, G., Martinez-Arellano, G., & Unamuno, G. (2024) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-024-09414-0 · Cited by 30
Ge, Y., Li, M., Huang, X., Hu, Y., Wang, Q., Sun, X., & Guo, W. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714238 · Cited by 8
A Systematic Review of Self-Adaptive Mobile Applications with Cooperative Dimension
Gebreselassie, B. A., García, N. M., & Midekso, D. (2025) · IoT · doi:10.3390/iot7010006 · Cited by 1
Human–Machine Synergy in Learning-Driven Data Fabrics
Saravanan, T. R., Samuel, P., Kanimozhi, N., & Poongothai, E. (2026) · Springer eBooks · doi:10.1007/978-3-032-09090-4_15 · Cited by 1
Metadata
- Authors
- Ali, M., Khan, S. U. R., Mashkoor, A., & Taskeen, A.
- Affiliations
- COMSATS University Islamabad (PK)
- Shifa Tameer-e-Millat University (PK)
- Johannes Kepler University of Linz (AT)
- Corresponding author
- Mashkoor, Atif
- Venue
- Cognition, Technology & Work
- Published
- 2024-01-03
- Volume
- 26
- Issue
- 1
- Pages
- 83-106
- ISSN
- 1435-5558 (ISSN-L)
- 1435-5566
- OpenAlex
- W4390539103
- Cited by
- 20
- References
- 40
- Citations by year
- 2026: 13 · 2025: 5 · 2024: 2
- FWCI
- 4.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Cognition Technology & Work (publishedVersion, cc-by)
- University Library Linz repository (Johannes Kepler Universitat Linz) (submittedVersion, cc-by)
- Funders
- Johannes Kepler University Linz
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Keywords
- adaptive user interfaces, context-aware computing, Android, mobile user interface, conceptual framework, real-time adaptation, user satisfaction, expert validation, user activity patterns
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- Ali, M., Khan, S. U. R., Mashkoor, A., & Taskeen, A. (2024). A conceptual framework for context-driven self-adaptive intelligent user interface based on Android. Cognition, Technology & Work. https://doi.org/10.1007/s10111-023-00749-z
