E-Learning Mobile Development of Student Structured Learning Applications during the pandemic

Andhika andhika; Manase Sahat H Simarangkir; Santo Wijaya

doi:10.35134/komtekinfo.v9i2.272

Authors

Andhika andhika Politeknik META Industri
Manase Sahat H Simarangkir Politeknik META Industri
Santo Wijaya Politeknik META Industri

DOI:

https://doi.org/10.35134/komtekinfo.v9i2.272

Keywords:

Education, Elearning, Mobile, Pandemic, School System

Abstract

During the Covid-19 pandemic, teaching and learning activities were threatened with a decline in the quality of world education, including the quality of education in Indonesia. Students and teachers cannot interact to carry out educational activities at school. Meanwhile, in the world of education, interaction and communication are very important for the growth and development of student knowledge. If this is lost, then one generation of students could be threatened by poor quality education services caused by the covid-19 virus. Although the internet has been developed in the world of education for a long time, there are still many schools that are still unable to develop it properly for students. This is evident when the national exams were held before the Covid-19 period, there were still many schools that did not understand and understood providing facilities directly to students. This is a challenge in itself for Indonesia when the covid-19 virus attacks and paralyzes all activities. Forcing all activities to be done inside the house and reducing all activities outside the home. Learning activities and examinations are important activities that are always the focus of the school every semester. This activity previously required students to be in school, but during the pandemic this should not be done due to the government's decision to limit the spread of the virus. All schools must think hard for a solution to this problem. Schools take an important role in school activities so that the quality of education services does not decrease drastically. Private schools are no exception, whose activities come from greater than that of students' parents. While many students' parents think that if there are no activities at school, the money for school payments will be postponed. Schools only have one choice so that the learning process and exams continue, namely by using an online application that can adjust national standards and school standards. Although there are many applications in circulation, many of these applications cannot be adapted to school conditions at a low cost. Mostly, if the school wants changes to the application, then the developer sets a lot of rates that the school cannot afford. Learning and examinations are activities where the administration must also exist for reporting by schools. The reporting format, of course, is different for each school with their respective systems. With the mobile application developed by researchers and implemented according to school administration, in general, learning activities and examinations continue to run with results that can be accounted for because they have reports that are adjusted by the school.

References

C. Chilivumbo, “Mobile E-learning: The choice between Responsive/Mobile Websites and Mobile Applications for Virtual Learning Environments for increasing access to Higher Education in Malawi,” 2015 IST-Africa Conf. IST-Africa 2015, pp. 1–15, 2015, doi: 10.1109/ISTAFRICA.2015.7190520.

Andhika, “Vege Application ! Using Mobile Application to Promote Vegetarian Food,” 2018 Int. Conf. Appl. Eng., pp. 1–6, 2018, [Online]. Available: https://ieeexplore.ieee.org/document/8579152.

Andhika, “Vege Application! Using Mobile Application to Buy Vegetarian Food,” Proc. 2019 Int. Conf. Appl. Eng. ICAE 2019, 2019, doi: 10.1109/ICAE47758.2019.9221650.

R. Njoroge and D. Nzuki, “Elearning induction model for the uptake of online courses: A case of Kenyatta University,” 2017 IST-Africa Week Conf. IST-Africa 2017, pp. 1–9, 2017, doi: 10.23919/ISTAFRICA.2017.8102306.

N. Ghatasheh, “Knowledge Level Assessment in e-Learning Systems Using Machine Learning and User Activity Analysis,” Int. J. Adv. Comput. Sci. Appl., vol. 6, no. 4, 2015, doi: 10.14569/ijacsa.2015.060415.

S. S. Al-Gahtani, “Empirical investigation of e-learning acceptance and assimilation: A structural equation model,” Appl. Comput. Informatics, vol. 12, no. 1, pp. 27–50, 2016, doi: 10.1016/j.aci.2014.09.001.

A. Zamfiroiu and C. Sbora, “Statistical Analysis of the Behavior for Mobile E-learning,” Procedia Econ. Financ., vol. 10, no. 14, pp. 237–243, 2014, doi: 10.1016/s2212-5671(14)00298-6.

A. Oztekin, Z. J. Kong, and O. Uysal, “UseLearn: A novel checklist and usability evaluation method for eLearning systems by criticality metric analysis,” Int. J. Ind. Ergon., vol. 40, no. 4, pp. 455–469, 2010, doi: 10.1016/j.ergon.2010.04.001.

C. M. Chen, L. J. Duh, and C. Y. Liu, “A personalized courseware recommendation system based on fuzzy item response theory,” Proc. - 2004 IEEE Int. Conf. e-Technology, e-Commerce e-Service, EEE 2004, pp. 305–308, 2004, doi: 10.1109/eee.2004.1287327.

G. Yun-Feng, “Research on Personalized Recommendation System in E-Learning Based onSemantic Web,” pp. 1046–1053, 2013, doi: 10.2991/icmt-13.2013.128.

M. Holenko Dlab and N. Hoic-Bozic, “Recommender system for Web 2.0 supported eLearning,” IEEE Glob. Eng. Educ. Conf. EDUCON, no. April, pp. 953–956, 2014, doi: 10.1109/EDUCON.2014.6826214.

N. Putu, “Embed Attitude from Student on Elearning Using Instructional Design with ADDIE Model,” Int. J. Adv. Comput. Sci. Appl., vol. 6, no. 11, pp. 35–43, 2015, doi: 10.14569/ijacsa.2015.061105.

C. Ivan, “A web based Publish-Subscribe framework for mobile computing,” Int. J. Adv. Comput. Sci. Appl., vol. 5, no. 4, pp. 103–112, 2014, doi: 10.14569/ijacsa.2014.050416.

M. Saud and M. Abdullah, “Diabetes Monitoring System Using Mobile Computing Technologies,” Int. J. Adv. Comput. Sci. Appl., vol. 4, no. 2, pp. 23–31, 2013, doi: 10.14569/ijacsa.2013.040204.

Andhika, “Reducing the Spread of Covid-19 by Buying Healthy Vegetarian Food at Home,” vol. 7, no. 3, pp. 197–204, 2020.

S. Shekapure and D. D. Patil, “Enhanced e-Learning experience using case based reasoning methodology,” Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 4, pp. 236–241, 2019, doi: 10.14569/ijacsa.2019.0100428.

M. Uddin, N. Ahmed, and A. Mahmood, “A Learner Model for Adaptable e-Learning,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 6, pp. 139–147, 2017, doi: 10.14569/ijacsa.2017.080618.

O. N, M. Salleh, and N. A., “E-Learning Methodologies and Tools,” Int. J. Adv. Comput. Sci. Appl., vol. 3, no. 2, pp. 48–52, 2012, doi: 10.14569/ijacsa.2012.030208.

K. Arai, “Comprehensive e-learning system with simulation capabilities for understanding of complex equations,” Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 11, pp. 330–335, 2019, doi: 10.14569/IJACSA.2019.0101146.

R. Razzaq and A. Badie, “E-Learning by Using Content Management System (CMS),” Int. J. Adv. Comput. Sci. Appl., vol. 5, no. 10, pp. 106–111, 2014, doi: 10.14569/ijacsa.2014.051015.

R. Bawarith, D. Abdullah, D. Anas, and P. Dr., “E-exam Cheating Detection System,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 4, pp. 176–181, 2017, doi: 10.14569/ijacsa.2017.080425.

O. A. H. Hassan, O. Qtaish, M. Abuhamdeh, and M. A. H. Hassan, “A hybrid exam scheduling technique based on graph coloring and genetic algorithms targeted towards student comfort,” Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 3, pp. 503–512, 2019, doi: 10.14569/IJACSA.2019.0100365.

M. J. Hoque, M. R. Ahmed, M. J. Uddin, and M. M. A. Faisal, “Automation of traditional exam invigilation using CCTV and bio-metric,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 6, pp. 392–399, 2020, doi: 10.14569/IJACSA.2020.0110651.

E. E., “A Proposed Framework for Generating Random Objective Exams using Paragraphs of Electronic Courses,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 9, pp. 426–432, 2017, doi: 10.14569/ijacsa.2017.080956.

A. A. Kamal, N. M. Shaipullah, L. Truna, M. Sabri, and S. N. Junaini, “Transitioning to online learning during COVID-19 Pandemic: Case study of a Pre-University Centre in Malaysia,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 6, pp. 217–223, 2020, doi: 10.14569/IJACSA.2020.0110628.

A. Alashqur, “Towards A Broader Adoption of Agile Software Development Methods,” Int. J. Adv. Comput. Sci. Appl., vol. 7, no. 12, pp. 94–98, 2016, doi: 10.14569/ijacsa.2016.071212.

S. M. Golodetz, C. Nicholls, I. D. Voiculescu, and S. A. Cameron, “Two tree-based methods for the waterfall,” Pattern Recognit., vol. 47, no. 10, pp. 3276–3292, 2014, doi: 10.1016/j.patcog.2014.04.017.

H. Huiting, P. W. C. Prasad, A. Alsadoon, and K. S. Bajaj, “Influences of learning styles on learner satisfaction in E-learning environment,” 2015 Int. Conf. Work. Comput. Commun. IEMCON 2015, vol. 6, no. 9, pp. 24–31, 2015, doi: 10.1109/IEMCON.2015.7344511.

A. Rahman and A. Fukuda, “User Interface Design of E-Learning System for Functionally Illiterate People,” Int. J. Adv. Comput. Sci. Appl., vol. 6, no. 11, pp. 126–134, 2015, doi: 10.14569/ijacsa.2015.061118.

N. Kipkurui, P. G., and A. Ikoha, “Evaluating Usability of E-Learning Systems in Universities,” Int. J. Adv. Comput. Sci. Appl., vol. 5, no. 8, pp. 97–102, 2014, doi: 10.14569/ijacsa.2014.050815.

M. Z. Asghar, “Quizzes : Quiz Application Development Using Android-Based MIT APP Inventor Platform,” vol. 7, no. 5, pp. 43–54, 2016.