Intelligence and Usability Empowerment of Smartphone Adaptive Features
Source abstract
Abstract
In adaptivity, the interface of the device automatically adjusts and assists the user. The adaptive user interfaces can adapt their activities by monitoring user status, the state of the system, and the current situation according to the adaptation strategy. Usually, the intensity of adaptation is measured in effectiveness, efficiency, and satisfaction to analyze the smartphone’s adaptive features. The adaptive features of light-emitting diode (LED) notifications, voice commands, face recognition, screen rotation, kid mode, drive mode, night mode, Swift Keyboard, s-health, gesture recognition, and fingerprint are selected for both iOS and Android platforms. Task completion within a specific time frame is used to measure effectiveness and efficiency, while satisfaction is calculated using the after-scenario questionnaire (ASQ). A total of 550 users are involved in the experimentation. The usability evaluation is measured for smartphone features. The effectiveness of adaptive features contains higher adaptivity in face recognition (87%) and voice command (85%). Furthermore, the satisfaction level is greater for adaptive features than non-adaptive features. This study indicates that adaptive features can only be used after a thorough examination of the user’s context. Furthermore, the usability evaluation shows that there is a dire need for adaptive smartphone features to provide ease and satisfaction to the user.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Personal Information Management and User Behavior · Green IT and Sustainability · Innovative Human-Technology Interaction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi Arabia
Department of Software Engineering, Superior University, Lahore 54000, Pakistan
Department of Computer Science, GC Women University, Sialkot 53310, Pakistan
Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi Arabia
Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi Arabia
Funding
The University of Jeddah
References (42)
Show source-provided references
1. Smartphone use in everyday life and travel10.1177/0047287514535847 ↗
2. The effects of mobile push notifications on news consumption and learning
3. Ahmed, S., Balasubramanian, H., Stumpf, S., Morrison, C., and Sellen, A. (2020, January 17–20). Investigating the intelligibility of a computer vision system for blind users. Proceedings of the 25th International Conference on Intelligent User Interfaces, Cagliari, Italy.10.1145/3377325.3377508 ↗
4. Andone, I., Błaszkiewicz, K., Eibes, M., Trendafilov, B., Montag, C., and Markowetz, A. (2016, January 12–16). How age and gender affect smartphone usage. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), Heidelberg, Germany.10.1145/2968219.2971451 ↗
5. Iqbal, M.W., Ahmad, N., and Shahzad, S.K. (2017, January 6–8). Usability evaluation of adaptive features in smartphones. Proceedings of the International Conference on Knowledge Based and Intelligent Information and Engineering Systems, (KES), Marseille, France.
6. A Comparative Study between Applications Developed for Android and iOS
7. Smartphones in mental health: A critical review of background issues, current status, and future concerns10.1186/s40345-019-0164-x ↗
8. Smartphone use and academic performance: A literature review10.1016/j.ijer.2020.101618 ↗
9. Usability Study of Smart Phone Messaging for Elderly and Low-literate Users
10. The Relationship Between Smartphone Addiction and Life Satisfaction: Faculty of Sport Sciences Students10.17220/ijpes.2020.01.008 ↗
11. Memon, I., Ali, Q., Fazal, H., Zubedi, A., and Khuwaja, S.S. (2020, January 29–30). Concepts, analysis, issues of smartphone and smart devices: A survey. Proceedings of the IEEE 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, Pakistan.10.1109/iCoMET48670.2020.9074106 ↗
12. Identifying smartphone users based on how they interact with their phones10.1186/s13673-020-0212-7 ↗
13. Predicting mental health using smart-phone usage and sensor data10.1007/s12652-020-02616-5 ↗
14. Providing adaptive smartphone interfaces targeted at elderly people: An approach that takes into account diversity among the elderly
15. Novac, O.C., Novac, M., Gordan, C., Berczes, T., and Bujdosó, G. (2017, January 1–2). Comparative study of google android, apple iOS and microsoft windows phone mobile operating systems. Proceedings of the 2017 14th International Conference on Engineering of Modern Electric Systems (EMES), Oradea, Romania.10.1109/EMES.2017.7980403 ↗
16. Use of smartphones, computers and social media among people with smi: Opportunity for intervention10.1007/s10597-019-00431-7 ↗
17. Lahiani, H., Elleuch, M., and Kherallah, M. (2015, January 14–16). Real time hand gesture recognition system for android devices. Proceedings of the 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), Marrakech, Morocco.10.1109/ISDA.2015.7489184 ↗
18. Usability of Mobile Applications: A Systematic Literature Study10.1109/ACCESS.2020.2981892 ↗
19. Liu, W., Lee, K.-P., Gray, C.M., Toombs, A.L., Chen, K.-H., and Leifer, L. (2021). Transdisciplinary Teaching and Learning in UX Design: A Program Review and AR Case Studies. Appl. Sci., 11.10.3390/app112210648 ↗
20. Detecting usability problems in mobile applications on the basis of dissimilarity in user behavior10.1016/j.ijhcs.2019.10.001 ↗
21. Integrated model-driven development of self-adaptive user interfaces10.1007/s10270-020-00777-7 ↗
22. Baqeel, H., and Saeed, S. (2019, January 3–4). Face detection authentication on smartphones: End user’s usability assessment experiences. Proceedings of the International Conference on Computer and Information Sciences (ICCIS), Sakaka, Saudi Arabia.10.1109/ICCISci.2019.8716452 ↗
23. User centered system design: New perspectives on human-computer interaction
24. Evaluation of usability dimensions of smartphone applications
25. Context-based mobile user interface10.4236/jcc.2016.49001 ↗
26. Environmental context detection for adaptive navigation using GNSS measurements from a smartphone10.1002/navi.221 ↗
27. Towards adaptive user interfaces for mobile-phone in smart world
28. Identifying child users via touchscreen interactions10.1145/3403574 ↗
29. The smart use of smartphones in pediatrics10.1016/j.pedn.2020.06.001 ↗
30. They would call me, and I would need to know because it is like life and death’: A qualitative examination of the acceptability of smartphone applications designed to reduce mobile phone use while driving10.1016/j.trf.2020.06.007 ↗
31. Can our phones keep us safe? A content analysis of smartphone applications to prevent mobile phone distracted driving
32. Analysis of circadian properties and healthy levels of blue light from smartphones at night10.1038/srep11325 ↗
33. Intelligent face recognition and navigation system using neural learning for smart security in internet of things10.1007/s10586-017-1323-4 ↗
34. Hand gesture recognition based on active ultrasonic sensing of smartphone: A survey10.1109/ACCESS.2019.2933987 ↗
35. Context-aware rule learning from smartphone data: Survey, challenges and future directions10.1186/s40537-019-0258-4 ↗
36. Understanding smartphone notifications’ user interactions and content importance10.1016/j.ijhcs.2019.03.001 ↗
37. Voice controlled home automation by using bluetooth module10.22214/ijraset.2018.1447 ↗
38. BehavDT: A behavioral decision tree learning to build user-centric context-aware predictive model10.1007/s11036-019-01443-z ↗
39. Okoshi, T., Tsubouchi, K., and Tokuda, H. (2019, January 4–8). Real-world product deployment of adaptive push notification scheduling on smartphones. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Anchorage, AK, USA.10.1145/3292500.3330732 ↗
40. Usability evaluation of mobile banking applications in digital business as emerging economy
41. Anova Based Usability Evaluation of Kid’s Mobile Apps Empowered Learning Process
42. Usability empowered by user’s adaptive features in smart phones: The rsm approach