Factors Influencing the Success of Students’ Learning through Online Learning/Distance Education : A Bibliometric Analysis of Scopus Database

Agus Santoso, Heri Retnawati, Munaya Nikma Rosyada, Ezi Apino, Ibnu Rafi, Kartianom Kartianom, Aigul Dauletkulova

Abstract


This study aims to examine the co-occurrence of several topics linked to factors that influence student learning success and explore the motor themes related to factors that influence student learning success. This study used the literature review method with data analysis using R Studio and VOSViewer software. Data analyzed were exported from the Scopus website from 2013 to 2023 of 383 documents. The research data analysis techniques used network mapping analysis of VOSviewer results (network visualization) and content analysis within the keywords and studies. The findings of this study presented the keywords (most frequent words, trending topics), co-occurrence network (thematic map and thematic evolution), and discussion of topics related to factors that influence student learning success. The basic themes identified were higher education and Covid-19. Meanwhile, gender and self-efficacy are motor themes that could be researched further as those can influence student learning performance in online learning. The findings of the bibliometric analysis were intended to reveal unique insights into the factors that determine student learning performance in distant learning and contribute to previously unexplored issues.


Keywords


Online Learning; Distance Education; Bibliometric Analysis; Student Success.

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References


Abdolrezapour, P., Ganjeh, S. J., & Ghanbari, N. (2023). Self-efficacy and resilience as predictors of students’ academic motivation in online education. PLOS ONE, 18(5), e0285984. https://doi.org/10.1371/journal.pone.0285984

Adzovie, D. E., & Jibril, A. B. (2022). Assessment of the effects of Covid-19 pandemic on the prospects of e-learning in higher learning institutions: The mediating role of academic innovativeness and technological growth. Cogent Education, 9(1), 2041222. https://doi.org/10.1080/2331186X.2022.2041222

Afkar, R., & Yarrow, N. (2021). Rewrite the future: How Indonesia’s education system can overcome the losses from the COVID-19 pandemic and raise learning outcomes for all (163674). World Bank. https://doi.org/10.1596/36327

Afshan, G., & Ahmed, A. (2020). Distance learning is here to stay: Shall we reorganize ourselves for the post-covid-19 world? Anaesthesia, Pain & Intensive Care, 24(5). https://doi.org/10.35975/apic.v24i5.1353

Al-Adwan, A. S. (2020). Investigating the drivers and barriers to MOOCs adoption: The perspective of TAM. Education and Information Technologies, 25(6), 5771–5795. https://doi.org/10.1007/s10639-020-10250-z

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Almaiah, M. A., Ayouni, S., Hajjej, F., Lutfi, A., Almomani, O., & Awad, A. B. (2022). Smart mobile learning success model for higher educational institutions in the context of the COVID-19 pandemic. Electronics, 11(8), 1278. https://doi.org/10.3390/electronics11081278

Almarashdeh, I., & Alsmadi, M. (2016). Investigating the acceptance of technology in distance learning program. 2016 International Conference on Information Science and Communications Technologies (ICISCT), 1–5. https://doi.org/10.1109/ICISCT.2016.7777404

AlRyalat, S. A. S., Malkawi, L. W., & Momani, S. M. (2019). Comparing bibliometric analysis using PubMed, scopus, and web of science databases. Journal of Visualized Experiments, 152, 58494. https://doi.org/10.3791/58494

Alzahrani, A. (2023). Analysis of the technology acceptance model (TAM) in understanding faculty’s behavioral intention to use internet of things (IoT). IJERI: International Journal of Educational Research and Innovation, 19, 153–169. https://doi.org/10.46661/ijeri.7461

Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., Sulijaya, B., & Puspitawati, R. (2020). Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. BMC Medical Education, 20(1), 392. https://doi.org/10.1186/s12909-020-02312-0

Andrade, M. S., Miller, R. M., Kunz, M. B., & Ratliff, J. M. (2020). Online learning in schools of business: The impact of quality assurance measures. Journal of Education for Business, 95(1), 37–44. https://doi.org/10.1080/08832323.2019.1596871

Baldwin, S., & Trespalacios, J. H. (2017). Evaluation instruments and good practices in online education. Online Learning, 21(2). https://doi.org/10.24059/olj.v21i2.913

Buabeng-Andoh, C., & Baah, C. (2020). Pre-service teachers’ intention to use learning management system: An integration of UTAUT and TAM. Interactive Technology and Smart Education, 17(4), 455–474. https://doi.org/10.1108/ITSE-02-2020-0028

Bubou, G. M., & Job, G. C. (2022). Individual innovativeness, self-efficacy and e-learning readiness of students of Yenagoa study centre, National Open University of Nigeria. Journal of Research in Innovative Teaching & Learning, 15(1), 2–22. https://doi.org/10.1108/JRIT-12-2019-0079

Cho, M.-H., Lim, S., Lim, J., & Kim, O. (2022). Does gender matter in online courses? A view through the lens of the community of inquiry. Australasian Journal of Educational Technology, 38(6), 169–184. https://doi.org/10.14742/ajet.7194

Churiyah, M., Sholikhan, S., Filianti, F., & Sakdiyyah, D. A. (2020). Indonesia education readiness conducting distance learning in COVID-19 pandemic situation. International Journal of Multicultural and Multireligious Understanding, 7(6), 491. https://doi.org/10.18415/ijmmu.v7i6.1833

Culajara, C. J., Culajara, J. P. M., Portos, O., & Villapando, M. K. (2022). Bridging instructional gaps through recognizing the factors and students’ experiences in distance learning. International Journal of Theory and Application in Elementary and Secondary School Education, 4(2), 152–167. https://doi.org/10.31098/ijtaese.v4i2.1025

Dumford, A. D., & Miller, A. L. (2018). Online learning in higher education: Exploring advantages and disadvantages for engagement. Journal of Computing in Higher Education, 30(3), 452–465. https://doi.org/10.1007/s12528-018-9179-z

Gharaibeh, M. K., & Gharaibeh, N. K. (2020). An empirical study on factors influencing the intention to use mobile learning. Advances in Science, Technology and Engineering Systems Journal, 5(5), 1261–1265. https://doi.org/10.25046/aj0505151

Giannakos, M., Papamitsiou, Z., Markopoulos, P., Read, J., & Hourcade, J. P. (2020). Mapping child–computer interaction research through co-word analysis. International Journal of Child-Computer Interaction, 23–24, 100165. https://doi.org/10.1016/j.ijcci.2020.100165

Haddar, G. A. (2023). Pengembangan keterampilan digital melalui pembelajaran daring: Sebuah eksplorasi dampak. Jurnal Pendidikan West Science, 1(08), 554–569. https://doi.org/10.58812/jpdws.v1i08.603

Hamann, K., Glazier, R. A., Wilson, B. M., & Pollock, P. H. (2021). Online teaching, student success, and retention in political science courses. European Political Science, 20(3), 427–439. https://doi.org/10.1057/s41304-020-00282-x

Hongsuchon, T., Emary, I. M. M. E., Hariguna, T., & Qhal, E. M. A. (2022). Assessing the impact of online-learning effectiveness and benefits in knowledge management, the antecedent of online-learning strategies and motivations: An empirical study. Sustainability, 14(5), 2570. https://doi.org/10.3390/su14052570

Huang, T. (2023). Factors affecting students’ online courses learning behaviors. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11882-7

Khan, M. A., Vivek, V., Nabi, M. K., Khojah, M., & Tahir, M. (2020). Students’ Perception towards E-Learning during COVID-19 Pandemic in India: An Empirical Study. Sustainability, 13(1), 57. https://doi.org/10.3390/su13010057

Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020). Projecting the potential impact of COVID-19 school closures on academic achievement. Educational Researcher, 49(8), 549–565. https://doi.org/10.3102/0013189X20965918

Kuswoyo, H., Rido, A., & Mandasari, B. (2022). A systematic review of research on EFL online learning: Effectiveness, challenges, learning tools, and suggestions. Proceeedings of the 19th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2022), 20–26. https://doi.org/10.33965/CELDA2022_202207L003

Li, D. (2020). A review of self-efficacy of learners through online learning. Journal of Humanities and Education Development, 2(6), 526–533. https://doi.org/10.22161/jhed.2.6.17

Lockman, A. S., & Schirmer, B. R. (2020). Online instruction in higher education: Promising, research-based, and evidence-based practices. Journal of Education and E-Learning Research, 7(2), 130–152. https://doi.org/10.20448/journal.509.2020.72.130.152

Marzilli, C. E., Delello, J. A., Marmion, S., & McWhorter, R. (2015). Exploring the Perceptions of College Students on the Use of Technology: What Do They Really Think? International Journal of Sciences, 24(2), 434–456.

Masrun, M., & Rusdinal, R. (2022). Self-efficacy, learning motivation, learning environment and its effect on online learning outcomes. Jurnal Kependidikan Penelitian Inovasi Pembelajaran, 6(2), 143–151. https://doi.org/10.21831/jk.v6i2.49445

Mesquita, A., Peres, P., & Moreira, F. (2018). The Use of Technology in Portuguese Higher Education: Building Bridges Between Teachers and Students. In Á. Rocha, H. Adeli, L. P. Reis, & S. Costanzo (Eds.), Trends and Advances in Information Systems and Technologies (Vol. 746, pp. 1327–1336). Springer International Publishing. https://doi.org/10.1007/978-3-319-77712-2_127

Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de La Información, 29(1). https://doi.org/10.3145/epi.2020.ene.03

Oluwadele, D., Singh, Y., & Adeliyi, T. T. (2023). E-learning performance evaluation in medical education—A bibliometric and visualization analysis. Healthcare, 11(2), 232. https://doi.org/10.3390/healthcare11020232

Ouajdouni, A., Chafik, K., & Boubker, O. (2021). Measuring e-learning systems success: Data from students of higher education institutions in Morocco. Data in Brief, 35, 106807. https://doi.org/10.1016/j.dib.2021.106807

Pacheco, A. Q. (2009). Issues for effective distance learning: A challenge in online education. Revista de Lenguas Modernas, 11, 345–362.

Park, K., Moon, S., & Oh, J. (2022). Predictors of academic achievement in distance learning for nursing students. Nurse Education Today, 108, 105162. https://doi.org/10.1016/j.nedt.2021.105162

Paudel, P. (2020). Online Education: Benefits, Challenges and Strategies During and After COVID-19 in Higher Education. International Journal on Studies in Education, 3(2), 70–85. https://doi.org/10.46328/ijonse.32

Richards, K., & Thompson, B. M. W. (2023). Challenges and instructor strategies for transitioning to online learning during and after the COVID-19 pandemic: A review of literature. Frontiers in Communication, 8, 1260421. https://doi.org/10.3389/fcomm.2023.1260421

Rizun, M., & Strzelecki, A. (2020). Students’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. International Journal of Environmental Research and Public Health, 17(18), 6468. https://doi.org/10.3390/ijerph17186468

Salas‐Pilco, S. Z., Yang, Y., & Zhang, Z. (2022). Student engagement in online learning in Latin American higher education during the COVID‐19 pandemic: A systematic review. British Journal of Educational Technology, 53(3), 593–619. https://doi.org/10.1111/bjet.13190

Shaikh, U. U., & Asif, Z. (2022). Persistence and dropout in higher online education: Review and categorization of factors. Frontiers in Psychology, 13, 902070. https://doi.org/10.3389/fpsyg.2022.902070

Sholikah, M., & Sutirman, S. (2020). How technology acceptance model (TAM) factors of electronic learning influence education service quality through students’ satisfaction. TEM Journal, 9(3), 1221–1226. https://doi.org/10.18421/TEM93-50

Sugandini, D., Garaika, & Istanto, Y. (2022). E-Learning system success adoption in Indonesia higher education. Academic Journal of Interdisciplinary Studies, 11(1), 149. https://doi.org/10.36941/ajis-2022-0013

Tsilika, K. (2023). Exploring the Contributions to Mathematical Economics: A Bibliometric Analysis Using Bibliometrix and VOSviewer. Mathematics, 11(22), 4703. https://doi.org/10.3390/math11224703

Turnbull, D., Chugh, R., & Luck, J. (2021). Transitioning to E-Learning during the COVID-19 pandemic: How have Higher Education Institutions responded to the challenge? Education and Information Technologies, 26(5), 6401–6419. https://doi.org/10.1007/s10639-021-10633-w

van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3

Voicu, M.-C., & Muntean, M. (2023). Factors that influence mobile learning among university students in Romania. Electronics, 12(4), 938. https://doi.org/10.3390/electronics12040938

Weiler, T., & Murad, Md. W. (2022). Motivational factors influencing learners’ academic success in an Australian enabling education setting. Journal of Social Studies Education Research, 13(4), 97–119.

Wu, X. (2017). Main Factor Analysis of Influencing Factors of College Students’ Success Rate. 2017 International Conference on Robots & Intelligent System (ICRIS), 198–201. https://doi.org/10.1109/ICRIS.2017.56

Yavuzalp, N., & Bahcivan, E. (2021). A structural equation modeling analysis of relationships among university students’ readiness for e-learning, self-regulation skills, satisfaction, and academic achievement. Research and Practice in Technology Enhanced Learning, 16(1), 15. https://doi.org/10.1186/s41039-021-00162-y

Yawson, D. E., & Yamoah, F. A. (2020). Understanding satisfaction essentials of E-learning in higher education: A multi-generational cohort perspective. Heliyon, 6(11), e05519. https://doi.org/10.1016/j.heliyon.2020.e05519

Younas, M., Noor, U., Zhou, X., Menhas, R., & Qingyu, X. (2022). COVID-19, students’ satisfaction about e-learning and academic achievement: Mediating analysis of online influencing factors. Frontiers in Psychology, 13, 948061. https://doi.org/10.3389/fpsyg.2022.948061

Yu, Z. (2021). The effects of gender, educational level, and personality on online learning outcomes during the COVID-19 pandemic. International Journal of Educational Technology in Higher Education, 18(1), 14. https://doi.org/10.1186/s41239-021-00252-3




DOI: https://doi.org/10.33394/jk.v10i1.10856

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