Utilization of Tik Tok Social Media as Learning Media in the Teaching and Learning Process during Covid-19

Ratna Susanti (1), Hamka Hamka (2)
(1) Politeknik Indonusa Surakarta, Indonesia,
(2) Universitas Lambung Mangkurat, Indonesia

Abstract

Background. The Covid-19 outbreak that occurred at the end of 2019 spread rapidly in Indonesia. To reduce the transmission, the Government set a rule not to hold activities that trigger crowds and all activities are carried out at home. The impact of this policy is very much felt, one of which is in the field of education.  The learning system has changed significantly from face-to-face learning in classrooms to distance learning through online media. Efforts that can be made so that learning is still carried out during covid-19 are utilizing social media as a learning medium, one of which is through the Tik Tok application.


Purpose. The purpose of this study was to determine the utilization of Tik Tok social media as a learning medium in the teaching and learning process during covid-19.


Method. The research method used is quantitative method, data obtained from interviews and distributing questionnaires via google form.


Results The results showed that Tik Tok social media was able to motivate students in learning because of Tik Tok's interesting and fun features. In addition, educators can also be creative through videos in presenting learning materials so that learning indicators can be conveyed.


Conclusion. The conclusion of this study shows that the use of Tik Tok social media in the learning process during Covid-19 is very effective.

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References

Abiri, R., Borhani, S., Sellers, E. W., Jiang, Y., & Zhao, X. (2019). A comprehensive review of EEG-based brain–computer interface paradigms. Journal of Neural Engineering, 16(1), 011001. https://doi.org/10.1088/1741-2552/aaf12e

Al-Mahdy, Y. F. H., Emam, M. M., & Hallinger, P. (2018). Assessing the contribution of principal instructional leadership and collective teacher efficacy to teacher commitment in Oman. Teaching and Teacher Education, 69, 191–201. https://doi.org/10.1016/j.tate.2017.10.007

Anderson, K. E. (2020). Getting acquainted with social networks and apps: It is time to talk about TikTok. Library Hi Tech News, 37(4), 7–12. https://doi.org/10.1108/LHTN-01-2020-0001

Andrew, M., Taylorson, J., J Langille, D., Grange, A., & Williams, N. (2018). Student Attitudes towards Technology and Their Preferences for Learning Tools/Devices at Two Universities in the UAE. Journal of Information Technology Education: Research, 17, 309–344. https://doi.org/10.28945/4111

Aune, T. M., Tossberg, J. T., Heinrich, R. M., Porter, K. P., & Crooke, P. S. (2022). Alu RNA Structural Features Modulate Immune Cell Activation and A-to-I Editing of Alu RNAs Is Diminished in Human Inflammatory Bowel Disease. Frontiers in Immunology, 13, 818023. https://doi.org/10.3389/fimmu.2022.818023

Bhat, J. R., & Alqahtani, S. A. (2021). 6G Ecosystem: Current Status and Future Perspective. IEEE Access, 9, 43134–43167. https://doi.org/10.1109/ACCESS.2021.3054833

Biango-Daniels, M., & Sarvary, M. (2021). A challenge in teaching scientific communication: Academic experience does not improve undergraduates’ ability to assess their or their peers’ writing. Assessment & Evaluation in Higher Education, 46(5), 809–820. https://doi.org/10.1080/02602938.2020.1812512

Cui, Y., Tian, M., Huang, D., Wang, X., Huang, Y., Fan, L., Wang, L., Chen, Y., Liu, W., Zhang, K., Wu, Y., Yang, Z., Tao, J., Feng, J., Liu, K., Ye, X., Wang, R., Zhang, X., & Zha, Y. (2020). A 55-Day-Old Female Infant Infected With 2019 Novel Coronavirus Disease: Presenting With Pneumonia, Liver Injury, and Heart Damage. The Journal of Infectious Diseases, 221(11), 1775–1781. https://doi.org/10.1093/infdis/jiaa113

Fuentes, A., López, J., & Pozo, S. (2019). Análisis de la Competencia Digital Docente: Factor Clave en el Desempeño de Pedagogías Activas con Realidad Aumentada. REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 17(2), 27. https://doi.org/10.15366/reice2019.17.2.002

Goh, E., & Lee, C. (2018). A workforce to be reckoned with: The emerging pivotal Generation Z hospitality workforce. International Journal of Hospitality Management, 73, 20–28. https://doi.org/10.1016/j.ijhm.2018.01.016

Haumann, N. T., Lumaca, M., Kliuchko, M., Santacruz, J. L., Vuust, P., & Brattico, E. (2021). Extracting human cortical responses to sound onsets and acoustic feature changes in real music, and their relation to event rate. Brain Research, 1754, 147248. https://doi.org/10.1016/j.brainres.2020.147248

Hendrik, B., Ali, N. M., Nayan, N. M., Mat Isa, N. A., & Masril, M. (2022). A New Robotic Learning Activity Design to Increase the Figural Creativity: Originality, Elaboration, Flexibility, and Fluency. International Journal on Advanced Science, Engineering and Information Technology, 12(1), 114. https://doi.org/10.18517/ijaseit.12.1.14109

Hight, M. O., Nguyen, N. Q., & Su, T. A. (2021). Chemical Anthropomorphism: Acting Out General Chemistry Concepts in Social Media Videos Facilitates Student-Centered Learning and Public Engagement. Journal of Chemical Education, 98(4), 1283–1289. https://doi.org/10.1021/acs.jchemed.0c01139

Khosravi, K., Pham, B. T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., Prakash, I., & Tien Bui, D. (2018). A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Science of The Total Environment, 627, 744–755. https://doi.org/10.1016/j.scitotenv.2018.01.266

Li, J., Yang, X., & Craig, C. J. (2019). A narrative inquiry into the fostering of a teacher-principal’s best-loved self in an online teacher community in China. Journal of Education for Teaching, 45(3), 290–305. https://doi.org/10.1080/09589236.2019.1599508

Li, Y., Ma, G., Gao, Y., & Wang, S. (2018). The software development for calculating the closing energy of automotive side swing door based on Microsoft excel. International Journal of Vehicle Performance, 4(1), 15. https://doi.org/10.1504/IJVP.2018.088781

Lu, H., Fan, C., Song, X., & Fang, W. (2021). A novel few-shot learning based multi-modality fusion model for COVID-19 rumor detection from online social media. PeerJ Computer Science, 7, e688. https://doi.org/10.7717/peerj-cs.688

Lu, Y., & (Cindy) Shen, C. (2023). Unpacking Multimodal Fact-Checking: Features and Engagement of Fact-Checking Videos on Chinese TikTok (Douyin). Social Media + Society, 9(1), 205630512211504. https://doi.org/10.1177/20563051221150406

Mazza, C., Ricci, E., Biondi, S., Colasanti, M., Ferracuti, S., Napoli, C., & Roma, P. (2020). A Nationwide Survey of Psychological Distress among Italian People during the COVID-19 Pandemic: Immediate Psychological Responses and Associated Factors. International Journal of Environmental Research and Public Health, 17(9), 3165. https://doi.org/10.3390/ijerph17093165

Mendoza, S., Sánchez-Adame, L. M., Urquiza-Yllescas, J. F., González-Beltrán, B. A., & Decouchant, D. (2022). A Model to Develop Chatbots for Assisting the Teaching and Learning Process. Sensors, 22(15), 5532. https://doi.org/10.3390/s22155532

Mitra, A., Mohanty, S. P., Corcoran, P., & Kougianos, E. (2021). A Machine Learning Based Approach for Deepfake Detection in Social Media Through Key Video Frame Extraction. SN Computer Science, 2(2), 98. https://doi.org/10.1007/s42979-021-00495-x

Munguia, P., Brennan, A., Taylor, S., & Lee, D. (2020). A learning analytics journey: Bridging the gap between technology services and the academic need. The Internet and Higher Education, 46, 100744. https://doi.org/10.1016/j.iheduc.2020.100744

Mustaqeem, & Kwon, S. (2019). A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition. Sensors, 20(1), 183. https://doi.org/10.3390/s20010183

Nitz, A. H., Dent, T., Davies, G. S., Kumar, S., Capano, C. D., Harry, I., Mozzon, S., Nuttall, L., Lundgren, A., & Tápai, M. (2020). 2-OGC: Open Gravitational-wave Catalog of Binary Mergers from Analysis of Public Advanced LIGO and Virgo Data. The Astrophysical Journal, 891(2), 123. https://doi.org/10.3847/1538-4357/ab733f

Özerim, M. G., & Tolay, J. (2021). Discussing the Populist Features of Anti-refugee Discourses on Social Media: An Anti-Syrian Hashtag in Turkish Twitter. Journal of Refugee Studies, 34(1), 204–218. https://doi.org/10.1093/jrs/feaa022

Polsinelli, M., Cinque, L., & Placidi, G. (2020). A light CNN for detecting COVID-19 from CT scans of the chest. Pattern Recognition Letters, 140, 95–100. https://doi.org/10.1016/j.patrec.2020.10.001

Roziqin, A., Mas’udi, S. Y. F., & Sihidi, I. T. (2021). An analysis of Indonesian government policies against COVID-19. Public Administration and Policy, 24(1), 92–107. https://doi.org/10.1108/PAP-08-2020-0039

Sahour, H., Gholami, V., & Vazifedan, M. (2020). A comparative analysis of statistical and machine learning techniques for mapping the spatial distribution of groundwater salinity in a coastal aquifer. Journal of Hydrology, 591, 125321. https://doi.org/10.1016/j.jhydrol.2020.125321

Satici, B., Gocet-Tekin, E., Deniz, M. E., & Satici, S. A. (2021). Adaptation of the Fear of COVID-19 Scale: Its Association with Psychological Distress and Life Satisfaction in Turkey. International Journal of Mental Health and Addiction, 19(6), 1980–1988. https://doi.org/10.1007/s11469-020-00294-0

Schneider, S., Beege, M., Nebel, S., & Rey, G. D. (2018). A meta-analysis of how signaling affects learning with media. Educational Research Review, 23, 1–24. https://doi.org/10.1016/j.edurev.2017.11.001

Shaw, K. L., Baldwin, L., & Heath, G. (2021). ‘A confident parent breeds a confident child’: Understanding the experience and needs of parents whose children will transition from paediatric to adult care. Journal of Child Health Care, 25(2), 305–319. https://doi.org/10.1177/1367493520936422

Shiyanbola, O. O., Bolt, D., Tarfa, A., Brown, C., & Ward, E. (2019). A content validity and cognitive interview process to evaluate an Illness Perception Questionnaire for African Americans with type 2 diabetes. BMC Research Notes, 12(1), 308. https://doi.org/10.1186/s13104-019-4342-9

Song, S., Zhao, Y. C., Yao, X., Ba, Z., & Zhu, Q. (2021). Short video apps as a health information source: An investigation of affordances, user experience and users’ intention to continue the use of TikTok. Internet Research, 31(6), 2120–2142. https://doi.org/10.1108/INTR-10-2020-0593

Srivastava, S., Kumar, A., Bauddh, K., Gautam, A. S., & Kumar, S. (2020). 21-Day Lockdown in India Dramatically Reduced Air Pollution Indices in Lucknow and New Delhi, India. Bulletin of Environmental Contamination and Toxicology, 105(1), 9–17. https://doi.org/10.1007/s00128-020-02895-w

Sukmawan, D., Handayani, D. O. D., & Dewi, D. A. (2021). Deep Learning Approaches to Identify Sukabumi Potentials Through Images on Instagram. 2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED), 1–6. https://doi.org/10.1109/ICCED53389.2021.9664877

Touloupis, T., & Athanasiades, C. (2020). A comparison between primary school principals’ and teachers’ perceptions of students’ online risk behaviours: The role of perceived self-efficacy. Cambridge Journal of Education, 50(4), 1–18. https://doi.org/10.1080/0305764X.2020.1740170

Udut, V. V., Naumov, S. A., Evtushenko, D. N., Udut, E. V., Naumov, S. S., & Zyuz’kov, G. N. (2021). A case of xenon inhalation therapy for respiratory failure and neuropsychiatric disorders associated with COVID-19. EXCLI Journal; 20:Doc1517; ISSN 1611-2156. https://doi.org/10.17179/EXCLI2021-4316

Wang, S., Kang, B., Ma, J., Zeng, X., Xiao, M., Guo, J., Cai, M., Yang, J., Li, Y., Meng, X., & Xu, B. (2021). A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19). European Radiology, 31(8), 6096–6104. https://doi.org/10.1007/s00330-021-07715-1

Wang, S., Paulo Esperança, J., & Wu, Q. (2022). Effects of Live Streaming Proneness, Engagement and Intelligent Recommendation on Users’ Purchase Intention in Short Video Community: Take TikTok (DouYin) Online Courses as an Example. International Journal of Human–Computer Interaction, 1–13. https://doi.org/10.1080/10447318.2022.2091653

Wang, Y. (2020). Humor and camera view on mobile short-form video apps influence user experience and technology-adoption intent, an example of TikTok (DouYin). Computers in Human Behavior, 110, 106373. https://doi.org/10.1016/j.chb.2020.106373

Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., Tipton, E., Schneider, B., Hulleman, C. S., Hinojosa, C. P., Paunesku, D., Romero, C., Flint, K., Roberts, A., Trott, J., Iachan, R., Buontempo, J., Yang, S. M., Carvalho, C. M., … Dweck, C. S. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573(7774), 364–369. https://doi.org/10.1038/s41586-019-1466-y

Zhang, L., Sun, B., Jiang, Z., & Spencer, B. F. (2022). A Quantitative Method for Post-Earthquake Safety Assessment of Damaged Reinforced Concrete Frames Based on On-Site Survey Data. Journal of Earthquake Engineering, 1–29. https://doi.org/10.1080/13632469.2022.2121793

Zhu, T., Wang, Y., Zhou, S., Zhang, N., & Xia, L. (2020). A Comparative Study of Chest Computed Tomography Features in Young and Older Adults With Corona Virus Disease (COVID-19). Journal of Thoracic Imaging, 35(4), W97–W101. https://doi.org/10.1097/RTI.0000000000000513

Authors

Ratna Susanti
ratnasusanti19@poltekindonusa.ac.id (Primary Contact)
Hamka Hamka
Susanti, R., & Hamka, H. (2024). Utilization of Tik Tok Social Media as Learning Media in the Teaching and Learning Process during Covid-19. International Journal of Language and Ubiquitous Learning, 2(2), 346–359. https://doi.org/10.70177/ijlul.v2i2.971

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