AI-Based Culture Independent Pervasive M-Learning Prototype Using UI Plasticity Design
Source abstract
Abstract
This paper explains the development of a culturally inclusive ubiquitous M-Learning platform (“Mobile Academy”) with an AI-based adaptive user interface. The rationale and need for this research and development are justif... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Mobile Learning in Education · ICT in Developing Communities · IoT and Edge/Fog Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (57)
Show source-provided references
1. Mobile academy: A ubiquitous mobile learning (mLearning) platform
2. Adaptive user interfaces and universal usability through plasticity of user interface design10.1016/j.cosrev.2021.100363 ↗
3. Cramming more components onto integrated circuits
4. Lithography and the future of Moore’s law10.1109/N-SSC.2006.4785861 ↗
5. Progress in digital integrated electronics10.1109/N-SSC.2006.4804410 ↗
6. A review on internet of things (IoT), internet of everything (IoE) and internet of nano things (IoNT)
7. Review of trends from mobile learning studies: A meta-analysis10.1016/j.compedu.2012.03.016 ↗
8. Sharples · The SAGE Handbook of e-Learning Research · 2007 · 12 · 22110.4135/9781848607859.n10 ↗
9. Mobile assisted language learning: A literature review
10. How should the higher education workforce adapt to advancements in technology for teaching and learning?10.1016/j.iheduc.2011.12.002 ↗
11. Using mobile communication technology in high school education: Motivation, pressure, and learning performance10.1016/j.compedu.2006.03.008 ↗
12. Using Hofstede’s cultural dimensions to interpret cross-cultural blended teaching and learning10.1016/j.compedu.2010.09.021 ↗
13. Pachler · Mobile Learning: Structures, Agency, Practices · 201010.1007/978-1-4419-0585-7 ↗
14. An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction10.1017/S0958344008000335 ↗
15. An investigation of mobile learning readiness in higher education based on the theory of planned behavior10.1016/j.compedu.2012.04.015 ↗
16. Norman · User Centered System Design: New Perspectives on Human-Computer Interaction · 198610.1201/b15703 ↗
17. Toward empirically derived methodologies and tools for human-computer interface development10.1016/0020-7373(89)90005-9 ↗
18. Helal · The Engineering Handbook of Smart Technology for Aging, Disability and Independence · 200810.1002/9780470379424 ↗
19. Multilingual website usability analysis based on an international user survey
20. User interface (UI) design issues for multilingual users: A case study10.1007/s10209-014-0397-5 ↗
21. Early user involvement in the development of information technology-related products for older people10.1007/s10209-004-0092-z ↗
22. Cross-cultural usability issues in e/m-learning10.33166/AETiC.2018.02.005 ↗
23. Color makes a better message
24. Cross-cultural analysis of gender difference in product color choice in global markets
25. What we know about consumers’ color choices10.1108/EUM0000000004565 ↗
26. Google: Android wallpaper apps were not security threats
27. Localization via ultra-wideband radios: A look at positioning aspects for future sensor networks10.1109/MSP.2005.1458289 ↗
28. Localization Technologies for Indoor Human Tracking
29. iText, “API documentation: iText 7 Java, iText PDF,” 2020. [Online]. Available: https://itextpdf.com/en/resources/api-documentation/itext-7-java.
30. Smartphone Adoption Tips Past 50% in Major Markets Worldwide
31. Corallo · Knowledge-Based Intelligent Information and Engineering Systems · 2006 · 4253 · 1092
32. Predicting user traits from a snapshot of apps installed on a smartphone10.1145/2636242.2636244 ↗
33. Unsafe exposure analysis of mobile in-app advertisements
34. Who’s who with big-five: Analyzing and classifying personality traits with smartphones
35. MoodScope: Building a mood sensor from smartphone usage patterns
36. Composite social network for predicting mobile apps installation
37. Fast app launching for mobile devices using predictive user context
38. Practical prediction and prefetch for faster access to applications on mobile phones
39. Preference, context and communities: A multi-faceted approach to predicting smartphone app usage patterns
40. An introduction to the five-factor model and its applications10.1111/j.1467-6494.1992.tb00970.x ↗
41. LiveLab: Measuring wireless networks and smartphone users in the field10.1145/1925019.1925023 ↗
42. Falling asleep with Angry Birds, Facebook and Kindle—A large scale study on mobile application usage
43. Demographic prediction based on user’s browsing behavior
44. Who does what on the web: A large-scale study of browsing behavior
45. Don’t kill my ads! balancing privacy in an ad-supported mobile application market
46. AdSplit: Separating smartphone advertising from applications
47. Private traits and attributes are predictable from digital records of human behavior10.1073/pnas.1218772110 ↗
48. Android, “Android Developers,” 2020. [Online]. Available: http://developer.android.com/reference/java/util/Locale.html#getDisplayLanguage().
49. Detect Language, “Language Detection API,” 2020. [Online]. Available: https://detectlanguage.com/.
50. Support-vector networks10.1007/BF00994018 ↗
51. The WEKA data mining software: An update10.1145/1656274.1656278 ↗
52. Platt · Advances in Kernel Methods · 1999 · 185
53. One-class SVMs for document classification
54. A comparative study on feature selection in text categorization
55. Russell · Artificial Intelligence: A Modern Approach · 2003
56. Cross-cultural inclusivity and usability evaluation of mobile academy prototype
57. Culturally inclusive adaptive user interface (CIAUI) framework: Exploration of plasticity of user interface design10.1142/S0219622020500455 ↗