Smart Interactive Quiz Model For An Education System Based On Fog Computing Technology
How to Cite?
Mohamed Saied M. El Sayed Amer, Nancy El Hefnawy, Hatem Mohamed Abdual-Kader, "Smart Interactive Quiz Model For An Education System Based On Fog Computing Technology," International Journal of Engineering Trends and Technology, vol. 69, no. 11, pp. 95-103, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I11P212
In current years, the usage of Internet of Things (IoT) devices takes place in several things in our lives. Several learning organizations profit from using web platforms to enhance and develop their educational environments and attract learners. E-learning is gaining popularity worldwide, and the number of learners enrolled in online courses is so large. The Smart Interactive Quiz (SIQ) presents a new type of quiz modeling to gain the benefits of (IoT) devices in the learning field. The SIQ shows a drawing board that allows users to answer quizzes in different ways like writing or drawing instead of the usual answer type that depends on multiple choices. The development of SIQ achieves based on web technology to receive answers in a graphic view. The answers graphics view is formatted in Scalable Vector Graphics (SVG) represented as text format. The answers are corrected based on finding similarities with the correct answers saved before. Moreover, there is the emergence of the new fog computing technology to bring the services closer to the end-users and to handle the big data resulting from this type of quizzes, and fog computing was emerged to provide a suitable environment to achieve the target.
Finally, the paper uses a new methodology to construct new quizzes for the learning process and gives preliminary results.
online quizzes, e-learning quizzes, assessments, quizzes, quizzes models.
 L. Nilson and B. J. Zimmerman., Creating Self-Regulated Learners: Strategies to Strengthen Students’ Self-Awareness and Learning Skills. Stylus Publishing, (2013).
 L. D. Fink., Creating Significant Learning Experiences: An Integrated Approach to Designing College Courses, 2nd ed. San Francisco: Jossey-Bass, (2013).
 E. S. Ebert and R. C. Culyer., School: An Introduction to Education,3rd ed. Belmont, CA: Cengage Learning, (2013).
 Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J... Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104 (2017) 18–33. https://doi.org/10.1016/j.compedu.2016.10.001.
 V. T. Mawhinney, D. E. Bostow, D. R. Laws, G. J. Blumenfeld, and B. L. Hopkins.,A comparison of students studying-behavior produced by daily, weekly, and three-week testing schedules,., Journal of Applied Behavior Analysis, 4(4) (1971) 257–264. [Online].Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1310703/
 Santos, R. et al., .,Teaching-Learning Environment Tool to Promote Individualized Student Assistance,., In proceedings of the 15th International Conference Computational Science and Its Applications, vol. Lecture Notes in Computer Science, 9155 (2015) 143-155.
 Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J., Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104 (2017) 18–33. https://doi.org/10.1016/j.compedu.2016.10.001.
 Kozulin, Alex, et al., Ed., Vygotsky ?s Educational Theory in Cultural Context (Learning in Doing: Social, Cognitive and Computational Perspectives).Cambridge, UK: Cambridge University Press, (2003).
 .,Scalable Vector Graphics (SVG)2.,. World Wide Web Consortium., Retrieved (2020).
 .,7.3. Base64 utility methods., HTML 5.2 Editor`s Draft. World Wide Web Consortium. Retrieved 2 January 2018. Introduced by changeset 5814 (2021) 02-01.
 Fredj, Z. B., & Duce, D. A., Schematic Diagrams, XML, and Accessibility. Theory and Practice of Computer Graphics 2003 (2003) 49 - 55.
 Mong, J. C., & Brailsford, D. F., Using SVG as the Rendering Model for Structured and Graphically Complex Web Material. Proceedings of the ACM Symposium on Document Engineering, (2003) 88-91.
 Sergio Antonio Andrade Freitas, Rita De Cassia Silva, Tiago Franklin R. Lucena, Eduardo do N. Ribeiro, Victor Cotrim De Lima, Rodrigo M. S. Da Silva.,. 49th Hawaii International Conference on System Sciences. 1 (2003) 66-73. doi: 10.1109/HICSS.2016.17.
 MDN contributors ,https://developer.mozilla.org/en-US/docs/Web/SVG, ( 2021).
 Ott J, Atchison A, Harnack P, Bergh A, Linstead E., a. A deep learning approach to identifying source code in images and video. In: Zaidman A, Kamei Y, Hill E, eds. (2018).
 Suzuki, S., and Be, K.., Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing 30 (1985) 32–46. doi:10.1016/0734-189X(85) 90016-7.
 Mohamed Saied M. ElSayed Amer, Nancy Elhefnawy, Hatem Mohamed Abdualkader , .,a proposed learning model based on fog computing technology.,. 1st International Conference on Computers and Information, Faculty of Computers and Information, Menoufia University, Egypt. (2021).