A Web-based Data Visualization Tool Regarding School Dropouts and User Asssesment
“Dropout in Primary Schools - Datasets - Basic Statistics Tanzania.” http://opendata.go.tz/dataset/wanafunzi-wa-shule-za-msingi-walioachishwa-au-kuacha-shule (accessed Oct. 22, 2019).
“Dropout in Secondary Schools. - Datasets - Basic Statistics Tanzania,” 2018. http://opendata.go.tz/dataset/idadi-ya-wanafunzi-walioacha-au-kuachishwa-shule-sekondari-kwa-mkoa (accessed Oct. 22, 2019).
T. S. Kalinga, “Causes of the Dropout in Secondary School in Tanzania: The Case Study of Mbeya, Dar es Salaam and Kilimanjaro Regions,” M.S. thesis, The Open University of Tanzania, Dar es Salaam, Tanzania, 2013.
D. H. Ouma, Z. Ting, and J. C. Pesha, “Analysis of the Socio-Economic Factors That Contribute to Children School Dropout in Artisanal Small-Scale Gold Mining Communities of Tanzania,” Journal of Education and Practice, vol. 8, no. 14, pp. 71–78, 2017.
N. Mduma, K. Kalegele, and D. Machuve, “An Ensemble Predictive Model Based Prototype for Student Drop-out in Secondary Schools,” Journal of Information Systems Engineering and Management, vol. 4, no. 3, Aug. 2019, Art no. em0094, doi: 10.29333/jisem/5893.
B. Williamson, “Digital methodologies of education governance: Pearson plc and the remediation of methods:,” European Educational Research Journal, vol. 15, no. 1, pp. 34–53, Jan. 2016, doi: 10.1177/1474904115612485.
C. I. Baker, “Visual Processing in the Primate Brain,” in Handbook of Psychology, Second Edition, American Cancer Society, 2012.
D. S. Alexandre and J. M. R. S. Tavares, “Introduction of Human Perception in Visualization,” International Journal of Imaging and Robotics, vol. 4, no. A10, pp. 60–70, May 2010.
D. Li et al., “ECharts: A declarative framework for rapid construction of web-based visualization,” Visual Informatics, vol. 2, no. 2, pp. 136–146, Jun. 2018, doi: 10.1016/j.visinf.2018.04.011.
M. M. Brehmer, “Why visualization? : task abstraction for analysis and design,” Ph.D. dissertation, University of British Columbia, Vancouver, Canada, 2016.
L. Wang, G. Wang, and C. A. Alexander, “Big Data and Visualization: Methods, Challenges and Technology Progress,” Digital Technologies, vol. 1, no. 1, pp. 33–38, doi: 10.12691/dt-1-1-7.
“TSED_FINAL,” National Bureau of Statistics. http://www.tsed.go.tz/dashboard/Dashboard#/ (accessed Oct. 22, 2019).
Y. Chen, Q. Chen, M. Zhao, S. Boyer, K. Veeramachaneni, and H. Qu, “DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction,” in 2016 IEEE Conference on Visual Analytics Science and Technology (VAST), Oct. 2016, pp. 111–120, doi: 10.1109/VAST.2016.7883517.
M. Liu, J. Kang, P. Zilong, W. Zou, and H. Lee, “Exploring Data Visualization as an Emerging Analytic Technique,” in E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Vancouver, British Columbia, Canada, Oct. 2017, pp. 1681–1690.
K. Kuosa et al., “Interactive Visualization Tools to Improve Learning and Teaching in Online Learning Environments,” International Journal of Distance Education Technologies, vol. 14, no. 1, pp. 1–21, Jan. 2016, doi: 10.4018/IJDET.2016010101.
F. Okubo, A. Shimada, C. Yin, and H. Ogata, “Visualization and prediction of learning activities by using discrete graphs,” in Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015, Hangzhou, China, Jan. 2015, pp. 739–744.
M. A. Rajib, V. Merwade, I. L. Kim, L. Zhao, C. Song, and S. Zhe, “SWATShare – A web platform for collaborative research and education through online sharing, simulation and visualization of SWAT models,” Environmental Modelling & Software, vol. 75, pp. 498–512, Jan. 2016, doi: 10.1016/j.envsoft.2015.10.032.
B. Alper, N. H. Riche, F. Chevalier, J. Boy, and M. Sezgin, “Visualization Literacy at Elementary School,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, Colorado, USA, May 2017, pp. 5485–5497, doi: 10.1145/3025453.3025877.
V. L. West, D. Borland, and W. E. Hammond, “Innovative information visualization of electronic health record data: a systematic review,” Journal of the American Medical Informatics Association: JAMIA, vol. 22, no. 2, pp. 330–339, Mar. 2015, doi: 10.1136/amiajnl-2014-002955.
S. Herzinger et al., “SmartR: an open-source platform for interactive visual analytics for translational research data,” Bioinformatics (Oxford, England), vol. 33, no. 14, pp. 2229–2231, Jul. 2017, doi: 10.1093/bioinformatics/btx137.
D. Haehn et al., “Scalable Interactive Visualization for Connectomics,” Informatics, vol. 4, no. 3, p. 29, Sep. 2017, doi: 10.3390/informatics4030029.
A. S. Rose and P. W. Hildebrand, “NGL Viewer: a web application for molecular visualization,” Nucleic Acids Research, vol. 43, no. Web Server issue, pp. W576–W579, Jul. 2015, doi: 10.1093/nar/gkv402.
D. Smilkov, S. Carter, D. Sculley, F. B. Viégas, and M. Wattenberg, “Direct-Manipulation Visualization of Deep Networks,” arXiv:1708.03788 [cs, stat], Aug. 2017, Accessed: Jun. 12, 2020. [Online]. Available: http://arxiv.org/abs/1708.03788.
M. Eid et al., “Cinematic Rendering in CT: A Novel, Lifelike 3D Visualization Technique,” American Journal of Roentgenology, vol. 209, no. 2, pp. 370–379, Aug. 2017, doi: 10.2214/AJR.17.17850.
R. A. Al-Msie’deen, “Tag Clouds for Object-Oriented Source Code Visualization,” Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4243–4248, Jun. 2019.
O. M. Kunene and D. Allopi, “Comparison Between Conditions of Major Roads Within and Outside the Port of Durban,” Engineering, Technology & Applied Science Research, vol. 3, no. 1, pp. 363–367, Feb. 2013.
M. Yildirim, H. Kurum, D. Miljavec, and S. Corovic, “Influence of Material and Geometrical Properties of Permanent Magnets on Cogging Torque of BLDC,” Engineering, Technology & Applied Science Research, vol. 8, no. 2, pp. 2656–2662, Apr. 2018.
A. A. Mahessar, A. N. Laghari, S. Qureshi, I. A. Siming, A. L. Qureshi, and F. A. Shaikh, “Environmental Impact Assessment of the Tidal Link Failure and Sea Intrusion on Ramsar Site No. 1069,” Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4148–4153, Jun. 2019.
“Tanzania National Health Portal.” https://hmisportal.moh.go.tz/hmisportal/#/ (accessed Oct. 26, 2019).
A. Sharma, A. Samantaray, and S. R. Dash, “Demographic Analytical Study of Girl Child Dropout from Schools in India,” International Journal of Engineering Technology Science and Research, vol. 4, no. 10, pp. 921–926, Oct. 2017.
A. Dennis, B. H. WIXOM, and R. M. Roth, System Analysis and Design. New York, NY: John Wiley & Sons, Inc., 2012.
J. Heer, S. K. Card, and J. A. Landay, “prefuse: a toolkit for interactive information visualization,” in Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’05, Portland, Oregon, USA, 2005, Art no. 421, doi: 10.1145/1054972.1055031.
J. L. R. Tamayo, M. B. Hernández, and H. G. Gómez, “Digital Data Visualization with Interactive and Virtual Reality Tools. Review of Current State of the Art and Proposal of a Model,” Revista ICONO14 Revista Científica de Comunicación y Tecnologías Emergentes, vol. 16, no. 2, pp. 40–65, 2018, doi: 10.7195/ri14.v16i2.1174.
MetricsAbstract Views: 73
PDF Downloads: 47
Copyright (c) 2020 Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
Most read articles by the same author(s)
- S. L. Sanga, D. Machuve, K. Jomanga, Mobile-based Deep Learning Models for Banana Disease Detection , Engineering, Technology & Applied Science Research: Vol. 10 No. 3 (2020): June, 2020
- K. P. Asiimwe, D. Machuve, M. A. Dida, Usability Testing of a Web Portal for Ornamental Plants and Flowers in Arusha, Tanzania , Engineering, Technology & Applied Science Research: Vol. 10 No. 3 (2020): June, 2020