Analysis of Learning Quality With Internet-Based Distance Learning During the COVID-19 Pandemic

  • Yuli Sutoto Nugroho Universitas Negeri Surabaya
  • Lilik Anifah Universitas Negeri Surabaya
  • Edy Sulistiyo Universitas Negeri Surabaya
  • Sari Cahyaningtias Arizona St ate University, Tempe, United States
  • Rifqi Firmansyah King Abdulaziz University, Jeddah, Saudi Arabia
Keywords: Quality of Learning, Internet-Based, Distance Learning, Covid-19


Analysis of the quality of learning is crucial in the teaching and learning process, to ensure the quality of learning is well maintained. Learning quality assurance instruments are one of the tools to improve quality in education through evaluations produced by studies of students. This research was conducted to test the quality of online learning during the COVID-19 pandemic. This research aims to evaluate Internet-Based Distance Learning which was carried out during the Work From Home (WFH) period. The learning analysis step is carried out through 1) Formulation of the need for quality analysis of learning, 2) Compiling quality analysis instruments, 3) Distribution of questionnaires, 4) Data processing, 5) Data analysis and 6) Compilation of results. The data analysis technique used descriptive qualitative analysis. The data that has been processed will then be analyzed using descriptive qualitative methods to find conclusions about the quality of learning in the Department of Electrical Engineering (JTE) during the 2020 pandemic. From the analysis, results obtained information that the Quality of Learning with Internet-Based Distance Learning during the COVID-19 Pandemic at JTE it can be said that it is good from a student's point of view, while from a lecturer's point of view, It can be concluded that online learning is very good. The implementation of this research is a consideration for JTE to improve the quality of Internet-Based Distance Learning

Abstract View : 45, PDF Download : 17
Download data is not yet available.


Aggor, C. S., Tchao, E. T., Keelson, E., & Diawuo, K. (2019). Mobile phone usage among senior high and technical school students in ghana and its impact on academic outcomes – a case study. Advances in Intelligent Systems and Computing, 903–913. doi:10.1007/978-3-030-11932-4_83

Bao, W. (2020). COVID-19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies. doi:10.1002/hbe2.191

Boud, D., & Molloy, E. (2013). Rethinking models of feedback for learning: the challenge of design. Assessment & Evaluation in Higher Education, 38(6), 698–712. doi:10.1080/02602938.2012.691462

Capdeferro, N., & Romero, M. (2012). Are online learners frustrated with collaborative learning experiences? The International Review of Research in Open and Distributed Learning, 13(2), 26. doi:10.19173/irrodl.v13i2.1127

da Costa, K. A. P., Papa, J. P., Lisboa, C. O., Munoz, R., & de Albuquerque, V. H. C. (2019). Internet of Things: A survey on machine learning-based intrusion detection approaches. Computer Networks, 147-157.

Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior, 60, 198–211. doi:10.1016/j.chb.2016.02.066

Dubey, A. D. (2016). ICT in education. International Journal of Information and Communication Technology Education, 12(4), 37–50. doi:10.4018/ijicte.2016100104

Erol, S., Jäger, A., Hold, P., Ott, K., & Sihn, W. (2016). Tangible industry 4.0: A scenario-based approach to learning for the future of production. Procedia CIRP, 54, 13–18. doi:10.1016/j.procir.2016.03.162

Gómez, J., Huete, J. F., Hoyos, O., Perez, L., & Grigori, D. (2013). Interaction system based on internet of things as support for education. Procedia Computer Science, 21, 132–139. doi:10.1016/j.procs.2013.09.019

Graham, C. R., Woodfield, W., & Harrison, J. B. (2013). A framework for institutional adoption and implementation of blended learning in higher education. The Internet and Higher Education, 18, 4–14. doi:10.1016/j.iheduc.2012.09.003

Hollins, E. R. (2011). Teacher preparation for quality teaching. Journal of Teacher Education, 62(4), 395–407. doi:10.1177/0022487111409415

Hubackova, S., & Semradova, I. (2016). Evaluation of Blended Learning. Procedia - Social and Behavioral Sciences, 217, 551–557. doi:10.1016/j.sbspro.2016.02.044

Inayat, I., Amin, R. ul, Inayat, Z., & Salim, S. S. (2013). Effects of collaborative web based vocational education and training (VET) on learning outcomes. Computers & Education, 68, 153–166. doi:10.1016/j.compedu.2013.04.027

Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260. doi:10.1126/science.aaa8415

Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23. doi:10.3402/rlt.v23.26507

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. doi:10.1038/nature14539

Li, J., Monroe, W., Shi, T., Jean, S., Ritter, A., & Jurafsky, D. (2017). Adversarial learning for neural dialogue generation. EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings.

Livingstone, S. (2012). Critical reflections on the benefits of ICT in education. Oxford Review of Education, 38(1), 9–24. doi:10.1080/03054985.2011.577938

Ma, J., Han, X., Yang, J., & Cheng, J. (2015). Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: The role of the instructor. The Internet and Higher Education, 24, 26–34. doi:10.1016/j.iheduc.2014.09.005

Markova, T., Glazkova, I., & Zaborova, E. (2017). Quality Issues of Online Distance Learning. Procedia - Social and Behavioral Sciences, 237, 685–691. doi:10.1016/j.sbspro.2017.02.043

Mohammadi, N., Ghorbani, V., & Hamidi, F. (2011). Effects of e-learning on language learning. Procedia Computer Science, 3, 464–468. doi:10.1016/j.procs.2010.12.078

Moore, J. L., Dickson-Deane, C., & Galyen, K. (2011). E-Learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135. doi:10.1016/j.iheduc.2010.10.001

Ni, A. Y. (2013). Comparing the effectiveness of classroom and online learning: teaching research methods. Journal of Public Affairs Education, 19(2), 199–215. doi:10.1080/15236803.2013.12001730

Nugroho, Y. S. (2018). The making of mobile learning as learning media using MIT App Inventor 2 in alternative energy course. International Journal of Learning and Teaching, 4(3), 190–194.

Nugroho, Y. S., & Paleologoudias, A. K. (2020). Differences between students from senior high school and vocational school in the learning outcomes of electrical engineering students. Proceeding - 2020 3rd International Conference on Vocational Education and Electrical Engineering: Strengthening the Framework of Society 5.0 through Innovations in Education, Electrical, Engineering and Informatics Engineering, ICVEE 2020.

Nugroho, Y. S., Suyitno, Daryanto, Achmad, F., C.N, L. E., & Rohman, M. (2019). Pengembangan modul pembelajaran matakuliah energi alternatif program studi pendidikan vokasional teknik elektro. JINoP (Jurnal Inovasi Pembelajaran), 5(1), 93-106.

Panigrahi, R., Srivastava, P. R., & Sharma, D. (2018). Online learning: Adoption, continuance, and learning outcome—A review of literature. International Journal of Information Management, 43, 1–14. doi:10.1016/j.ijinfomgt.2018.05.005

Prestridge, S. (2012). The beliefs behind the teacher that influences their ICT practices. Computers & Education, 58(1), 449–458. doi:10.1016/j.compedu.2011.08.028

Schuwirth, L. W. T., & Van der Vleuten, C. P. M. (2011). Programmatic assessment: From assessment of learning to assessment for learning. Medical Teacher, 33(6), 478–485. doi:10.3109/0142159x.2011.565828

Shen, D., Cho, M.-H., Tsai, C.-L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10–17. doi:10.1016/j.iheduc.2013.04.001

Shokri, R., & Shmatikov, V. (2015). Privacy-preserving deep learning. 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton). doi:10.1109/allerton.2015.7447103

Sugiyono. (2015). Metode Penelitian Pendekatan Kuantitatif, Kualitatif dan R&D. Alfabeta.

Sugiyono. (2016). Metode Penelitian Kuantitatif, Kualitatif dan R&D. PT Alfabet.

Tarutė, A., & Gatautis, R. (2014). ICT Impact on SMEs Performance. Procedia - Social and Behavioral Sciences, 110, 1218–1225. doi:10.1016/j.sbspro.2013.12.968

Wang, T.-H. (2014). Developing an assessment-centered e-Learning system for improving student learning effectiveness. Computers & Education, 73, 189–203. doi:10.1016/j.compedu.2013.12.002

How to Cite
Nugroho, Y. S., Anifah, L., Sulistiyo, E., Cahyaningtias, S., & Rifqi Firmansyah. (2021). Analysis of Learning Quality With Internet-Based Distance Learning During the COVID-19 Pandemic. IJORER : International Journal of Recent Educational Research, 2(1), 96-110.