AN EVALUATION ON ONLINE LEARNING BY DATA VISUALIZATION: A CASE STUDY FROM INFORMATION TECHNOLOGY EDUCATION PROGRAM

Sulidar Fitri(1*), Maesaroh Lubis(2)

(1) Universitas Muhammadiyah Tasikmalaya
(2) Universitas Muhammadiyah Tasikmalaya
(*) Corresponding Author

Abstract

The result of learning process can be seen using scores from the exam as a result for evaluating the learning quality. This study focused on comparing the learning outcomes in Universitas Muhammadiyah Tasikmalaya (UMTAS) students especially one class in Information Technology Education Program between face-to-face learning and online learning. The learning process is observed in order to gain some insight about the difference number of academic performance and student’s perception between face-to-face online learning. The comparative results of this research will be described through data visualization using R programming language. Data visualization using R programming language will result in form of numbers summary data and graphics. The results of this study showed that the exam score and student’s perception after face-to-face learning is higher than online learning. This study shows around 93% students from Information Technology Education Department demanded more face-to-face in class than online learning.

Keywords

Evaluation; Online Learning; Student Performance; Data Visualization; R Language

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References

Abou El-Seoud, S., Seddiek, N., Taj-Eddin, I., Ghenghesh, P., Nosseir, A., & El-Khouly, M. (2014). E-Learning and Students’ Motivation: A Research Study on the Effect of E-Learning on Higher Education. International Journal of Emerging Technologies in Learning (iJET), 9(4), 20. https://doi.org/10.3991/ijet.v9i4.3465

Adler, D., Nenadic, O., & Zucchini, W. (2003). RGL: A R-library for 3D visualization with OpenGL. http://rgl.neoscientists.org/arc/doc/RGL_INTERFACE03.pdf

Bali, S., & Liu, M. C. (2018). Students’ perceptions toward online learning and face-to-face learning courses. Journal of Physics: Conference Series, 1108, 012094. https://doi.org/10.1088/1742-6596/1108/1/012094

Bir, D. D. (2019). Comparison of Academic Performance of Students in Online Vs Traditional Engineering Course. European Journal of Open, Distance and E-Learning, 22(1), 1–13. https://doi.org/10.2478/eurodl-2019-0001

Bozkurt, A. (2022). A Retro Perspective on Blended/Hybrid Learning: Systematic Review, Mapping and Visualization of the Scholarly Landscape. Journal of Interactive Media in Education, 2022(1), 2. https://doi.org/10.5334/jime.751

Broatch, J. E., Dietrich, S., & Goelman, D. (2019). Introducing Data Science Techniques by Connecting Database Concepts and dplyr. Journal of Statistics Education, 27(3), 147–153. https://doi.org/10.1080/10691898.2019.1647768

Campbell, M. (2019). Data Visualization. In M. Campbell, Learn RStudio IDE (pp. 73–85). Apress. https://doi.org/10.1007/978-1-4842-4511-8_7

Chisadza, C., Clance, M., Mthembu, T., Nicholls, N., & Yitbarek, E. (2021). Online and face‐to‐face learning: Evidence from students’ performance during the Covid‐19 pandemic. African Development Review, 33(S1). https://doi.org/10.1111/1467-8268.12520

Culpepper, S. A., & Aguinis, H. (2011). R is for Revolution: A Cutting-Edge, Free, Open Source Statistical Package. Organizational Research Methods, 14(4), 735–740. https://doi.org/10.1177/1094428109355485

Eberhard, K. (2023). The effects of visualization on judgment and decision-making: A systematic literature review. Management Review Quarterly, 73(1), 167–214. https://doi.org/10.1007/s11301-021-00235-8

Edlink | Platform Pembelajaran Inovatif Kreasi Anak Bangsa. (n.d.). Retrieved October 27, 2020, from https://edlink.id/

Fatihahsari, F., & Darujati, C. (2021). Analisis Usability Mobile Apps Edlink dengan Menggunakan Heuristic Evaluation. Sistemasi: Jurnal Sistem Informasi, 10(2), Article 2. https://doi.org/10.32520/stmsi.v10i2.1263

Fitri, S., Muhammad, T., Riki, C., & Sampath, S. (2023). Data Visualization for Students’ Perception Toward Online and Offline Learning in Information Technology Education Program. International Journal of Quantitative Research and Modeling, 4(3), Article 3. https://doi.org/10.46336/ijqrm.v4i3.500

Fitri, S., & Rubiani, H. (2023). Edukasi Penggunaan Aplikasi Zoom Untuk Menunjang Pemberdayaan Diri Perempuan Paruh Baya. Jurnal Pengabdian Nasional (JPN) Indonesia, 4(1), Article 1. https://doi.org/10.35870/jpni.v4i1.102

Foundation, R. (n.d.). R: What is R? Retrieved October 26, 2020, from https://www.r-project.org/about.html

Fox, J., & Leanage, A. (2016). R and the Journal of Statistical Software. Journal of Statistical Software, 73(2). https://doi.org/10.18637/jss.v073.i02

Gatto, L., Breckels, L. M., Naake, T., & Gibb, S. (2015). Visualization of proteomics data using R and Bioconductor. PROTEOMICS, 15(8), 1375–1389. https://doi.org/10.1002/pmic.201400392

Gherheș, V., Stoian, C. E., Fărcașiu, M. A., & Stanici, M. (2021). E-Learning vs. Face-To-Face Learning: Analyzing Students’ Preferences and Behaviors. Sustainability, 13(8), 4381. https://doi.org/10.3390/su13084381

Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923–6947. https://doi.org/10.1007/s10639-021-10523-1

Heer, J., & Bostock, M. (2010). Crowdsourcing graphical perception: Using mechanical turk to assess visualization design.

Hudiburgh, L. M., & Garbinsky, D. (2020). Data Visualization: Bringing Data to Life in an Introductory Statistics Course. Journal of Statistics Education, 28(3), 262–279. https://doi.org/10.1080/10691898.2020.1796399

Idris, F., Hassan, Z., Ya’acob, A., Gill, S. K., & Awal, N. A. M. (2012). The Role of Education in Shaping Youth’s National Identity. Procedia - Social and Behavioral Sciences, 59, 443–450. https://doi.org/10.1016/j.sbspro.2012.09.299

Iglesias-Pradas, S., Hernández-García, Á., Chaparro-Peláez, J., & Prieto, J. L. (2021). Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study. Computers in Human Behavior, 119, 106713. https://doi.org/10.1016/j.chb.2021.106713

Jones, J. E., Jones, L. L., Calvert, M. J., Damery, S. L., & Mathers, J. M. (2022). A Literature Review of Studies that Have Compared the Use of Face-To-Face and Online Focus Groups. International Journal of Qualitative Methods, 21, 160940692211424. https://doi.org/10.1177/16094069221142406

Karnalim, O., Kumiawati, G., & Suiadi, S. F. (2021). Online Teaching on Student Programming Performance During the Pandemic. 2021 IEEE International Conference on Engineering, Technology & Education (TALE), 01–05. https://doi.org/10.1109/TALE52509.2021.9678601

Keržič, D., Alex, J. K., Pamela Balbontín Alvarado, R., Bezerra, D. D. S., Cheraghi, M., Dobrowolska, B., Fagbamigbe, A. F., Faris, M. E., França, T., González-Fernández, B., Gonzalez-Robledo, L. M., Inasius, F., Kar, S. K., Lazányi, K., Lazăr, F., Machin-Mastromatteo, J. D., Marôco, J., Marques, B. P., Mejía-Rodríguez, O., … Aristovnik, A. (2021). Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries. PLOS ONE, 16(10), e0258807. https://doi.org/10.1371/journal.pone.0258807

Maia, R., Eliason, C. M., Bitton, P.-P., Doucet, S. M., & Shawkey, M. D. (2013). pavo: An R package for the analysis, visualization and organization of spectral data. Methods in Ecology and Evolution, 4(10), 906–913. https://doi.org/10.1111/2041-210X.12069

Mather, M., & Sarkans, A. (2018). Student Perceptions of Online and Face-to-Face Learning. International Journal of Curriculum and Instruction, 10(2), Article 2.

Mendikbud Terbitkan SE tentang Pelaksanaan Pendidikan dalam Masa Darurat Covid-19. (2020, March 24). Kementerian Pendidikan Dan Kebudayaan. https://www.kemdikbud.go.id/main/blog/2020/03/mendikbud-terbitkan-se-tentang-pelaksanaan-pendidikan-dalam-masa-darurat-covid19

Michael Onyema, E., Chika Eucheria, N., Ayobamidele Obafemi, F., Sen, S., Grace Atonye, F., Sharma, A., & Omar Alsayed, A. (2020). Impact of Coronavirus Pandemic on Education. Journal of Education and Practice. https://doi.org/10.7176/JEP/11-13-12

Panse, C., Trachsel, C., & Türker, C. (2022). Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences. Journal of Integrative Bioinformatics, 19(4), 20220031. https://doi.org/10.1515/jib-2022-0031

Rashid, T., & Asghar, H. M. (2016). Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior, 63, 604–612. https://doi.org/10.1016/j.chb.2016.05.084

Rubiani, H., Samsoleh, E., Fitri, S., & Soprani, S. R. (2021). SOSIALISASI SISTEM INFORMASI BERBASIS TEKNOLOGI INFORMASI SEBAGAI PENDUKUNG PENERAPAN PHYSICAL DISTANCING DI MASA PANDEMI COVID-19. BERNAS: Jurnal Pengabdian Kepada Masyarakat, 2(1), Article 1. https://doi.org/10.31949/jb.v2i1.738

Setiawan, A. M., Munzil, & Fitriyah, I. J. (2021). Trend of learning management system (LMS) platforms for science education before-after Covid-19 pandemic. 060005. https://doi.org/10.1063/5.0043196

Smith, P. (2019). Engaging online students through peer-comparison progress dashboards. Journal of Applied Research in Higher Education, 12(1), 38–56. https://doi.org/10.1108/JARHE-11-2018-0249

Tümen Akyıldız, S. (2020). College Students’ Views on the Pandemic Distance Education: A Focus Group Discussion. International Journal of Technology in Education and Science, 4(4), 322–334. https://doi.org/10.46328/ijtes.v4i4.150

Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T., Miller, E., Bache, S., Müller, K., Ooms, J., Robinson, D., Seidel, D., Spinu, V., … Yutani, H. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686

Xiao, W., Liu, C., Wang, H., Zhou, M., Hossain, M. S., Alrashoud, M., & Muhammad, G. (2021). Blockchain for Secure-GaS: Blockchain-Powered Secure Natural Gas IoT System With AI-Enabled Gas Prediction and Transaction in Smart City. IEEE Internet Things J., 8(8), 6305–6312. https://doi.org/10.1109/JIOT.2020.3028773

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