How the Evolution and Track of Several Digital Technologies in Science Education?

Authors

  • Khoirun Nisa' Universitas Negeri Surabaya
  • Afaurina Indriana Safitri Universitas Negeri Surabaya
  • Husni Mubarok National Taiwan University of Science and Technology

DOI:

https://doi.org/10.26740/jpps.v13n2.p113-128

Keywords:

Bibliometric, Digital Technologies, Literature Review , Science Education

Abstract

Objective:  Digital technologies have significantly impacted science education. This research uses a bibliometric analysis to analyze the evolution of various digital technologies in science education. Method: The research uses the PRISMA method to conduct a systematic review using the Scopus database. Results: LMS was the highest publication and citation in the last five years. DL and LMS publications increased, but DA decreased. DL, LMS, DA, and EA publications dominate article papers. SC and ILS dominated conference papers. 57% of DT researchers are European, with 19% from Asian and North American researchers. Twenty-four sources are participating in DT research. Many universities in America, such as Harvard University, Stanford University, MIT, and Berkeley University, the University of California have extensive facilities for participating in DL, LMS, DA, EA, SC, and ILS research. Novelty: This research is essential to educators, researchers, and policymakers to provide insights on improving digital teaching technologies, inform policy, and promote interdisciplinary collaboration. It also offers an overview and research trend of DT in science education research and its opportunities for researchers, librarians, digital developers, educators, and policymakers to develop further research, education, and technology. Further research can be conducted based on the scope of mathematics or physics education, especially to investigate specific skills or STEAM.

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References

Alam, A. (2022). Educational robotics and computer programming in early childhood

education: a conceptual framework for assessing elementary school students’ computational thinking for designing powerful educational scenarios. 2022 International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN), 1–7.

Aliyyah, R. R., Rasmitadila, Fauziah, S. P., Widyasari, Marini, A., & Ruhimat. (2024).

Digital library: Lecturers’ perceptions of facilitating learning resources in the industrial era 4.0. Journal of Education and E-Learning Research, 11(1), 203–210. https://doi.org/10.20448/jeelr.v11i1.5425

Ameli, F. (2020). Teaching and learning for the twenty-first century: educational goals, policies,

and curricula from six nations: edited by FM Reimers and CK Chung, Cambridge, MA, Harvard Education Press, 2016, 304 pp., US $34 (paperback), ISBN 978-1-61250-922-8. Taylor & Francis.

Aristovnik, A., Ravšelj, D., & Umek, L. (2020). A bibliometric analysis of COVID-19 across

science and social science research landscape. Sustainability, 12(21), 9132. https://doi.org/10.3390/su12219132

Awaji, B. M. A. (2021). Investigating the effectiveness of using GeoGebra software on students’

mathematical proficiency. University of Glasgow.

Balyer, A., & Öz, Ö. (2018). Academicians’ Views on Digital Transformation in Education.

International Online Journal of Education and Teaching, 5(4), 809–830. http://iojet.org/index.php/IOJET/article/view/441/295

Berchin, I. I., Sima, M., de Lima, M. A., Biesel, S., dos Santos, L. P., Ferreira, R. V., de

Andrade, J. B. S. O., & Ceci, F. (2018). The importance of international conferences on sustainable development as higher education institutions’ strategies to promote sustainability: A case study in Brazil. Journal of Cleaner Production, 171, 756–772. https://doi.org/10.1016/j.jclepro.2017.10.042.

Bielecka, E. (2020). GIS spatial analysis modeling for land use change. A bibliometric

analysis of the intellectual base and trends. Geosciences, 10(11), 421. https://doi.org/10.3390/geosciences10110421.

Brundiers, K., Barth, M., Cebrián, G., Cohen, M., Diaz, L., Doucette-Remington, S.,

Dripps, W., Habron, G., Harré, N., & Jarchow, M. (2021). Key competencies in sustainability in higher education—toward an agreed-upon reference framework. Sustainability Science, 16, 13–29. https://doi.org/10.1007/s11625-020-00838-2.

Cebrián, G., Palau, R., & Mogas, J. (2020). The smart classroom as a means to the

development of ESD methodologies. Sustainability, 12(7), 3010. https://doi.org/10.3390/su12073010.

Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial

Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233.

Cress, T., & Kalthoff, H. (2023). Hybrid Imbalance: Collaborative Fabrication of Digital

Teaching and Learning Material. Qualitative Sociology, 46(3), 403–428. https://doi.org/10.1007/s11133-023-09539-5.

Dede, C., & Lidwell, W. (2023). Developing a next-generation model for massive digital

learning. Education Sciences, 13(8), 845. https://doi.org/10.3390/educsci13080845.

Farooq, R. (2023). Knowledge management and performance: a bibliometric analysis

based on Scopus and WOS data (1988–2021). Journal of Knowledge Management, 27(7), 1948–1991. https://doi.org/10.1108/JKM-06-2022-0443.

García-Lillo, F., Claver, E., Marco-Lajara, B., Seva-Larrosa, P., & Ruiz-Fernández, L.

(2021). MNEs from emerging markets: a review of the current literature through “bibliographic coupling” and social network analysis. International Journal of Emerging Markets, 16(8), 1912–1942. https://doi.org/10.1108/IJOEM-03-2019-0170.

González, C., López, D., Calle-Arango, L., Montenegro, H., & Clasing, P. (2022). Chilean

University Students’ Digital Learning Technology Usage Patterns and Approaches to Learning. ECNU Review of Education, 5(1), 37–64. https://doi.org/10.1177/20965311211073538.

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of

digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004.

Heradio, R., Perez-Morago, H., Fernandez-Amoros, D., Cabrerizo, F. J., & Herrera-

Viedma, E. (2016). A bibliometric analysis of 20 years of research on software product lines. Information and Software Technology, 72, 1–15. https://doi.org/10.1016/j.infsof.2015.11.004.

Hernandez-de-Menendez, M., & Morales-Menendez, R. (2019). Technological

innovations and practices in engineering education: a review. International Journal on Interactive Design and Manufacturing (IJIDeM), 13, 713–728.

Horbach, S. ( S., & Halffman, W. ( W. (2018). The changing forms and expectations of peer

review. Research Integrity and Peer Review, 3, 1–15. https://doi.org/10.1186/s41073-018-0051-5.

Islam, M. M., Chowdhury, M. A. M., Begum, R. A., & Amir, A. A. (2022). A

bibliometric analysis on the research trends of climate change effects on economic vulnerability. Environmental Science and Pollution Research, 29(39), 59300–59315. https://doi.org/10.1007/s11356-022-20028-0.

Lembani, R., Gunter, A., Breines, M., & Dalu, M. T. B. (2020). The same course, different

access: the digital divide between urban and rural distance education students in South Africa. Journal of Geography in Higher Education, 44(1), 70–84. https://doi.org/10.1080/03098265.2019.1694876.

Li, K. C., & Wong, B. T.-M. (2022). Research landscape of smart education: a bibliometric

analysis. Interactive Technology and Smart Education, 19(1), 3–19. https://doi.org/10.1108/ITSE-05-2021-0083.

Marks, B., & Thomas, J. (2022). Adoption of virtual reality technology in higher education:

An evaluation of five teaching semesters in a purpose-designed laboratory. Education and Information Technologies, 27(1), 1287–1305. https://doi.org/10.1007/s10639-021-10653-6.

McDaniel, K. G., Brown, T., Radford, C. C., McDermott, C. H., van Houten, T., Katz, M.

E., Stearns, D. A., & Hildebrandt, S. (2021). Anatomy as a model environment for acquiring professional competencies in medicine: Experiences at Harvard Medical School. Anatomical Sciences Education, 14(2), 241–251. https://doi.org/10.1002/ase.2000.

Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences.

Artificial Intelligence, 267, 1–38. https://doi.org/10.1016/j.artint.2018.07.007.

Nami, F. (2020). Educational smartphone apps for language learning in higher education:

Students’ choices and perceptions. Australasian Journal of Educational Technology, 36(4), 82–95. https://doi.org/10.14742/ajet.5350.

Norton, J. C., Politis, M. D., Bimali, M., Vyas, K. S., Bircan, E., Nembhard, W. N., Amick,

B. C., & Koturbash, I. (2023). Analysis of COVID-19 pandemic on supplement usage and its combination with self-medication within the state of Arkansas. Journal of Dietary Supplements, 20(2), 171–198. https://doi.org/10.1080/19390211.2022.2128500.

Oliveira, G., Grenha Teixeira, J., Torres, A., & Morais, C. (2021). An exploratory study on

the emergency remote education experience of higher education students and teachers during the COVID‐19 pandemic. British Journal of Educational Technology, 52(4), 1357–1376. https://doi.org/10.1111/bjet.13112.

Oyewola, D. O., & Dada, E. G. (2022). Exploring machine learning: a scientometrics

approach using bibliometrix and VOSviewer. SN Applied Sciences, 4(5), 143. https://doi.org/10.1007/s42452-022-05027-7.

Peng, X., & Dai, J. (2020). A bibliometric analysis of neutrosophic set: two decades review

from 1998 to 2017. Artificial Intelligence Review, 53(1), 199–255. https://doi.org/10.1007/s10462-018-9652-0.

Pham, P.-T., Lien, D. T. H., Kien, H. C., Chi, N. H., Tinh, P. T., Do, T., Nguyen, L. C., &

Nguyen, T.-T. (2022). Learning Management System in Developing Countries: A Bibliometric Analysis between 2005 and 2020. European Journal of Educational Research, 11(3), 1363–1377. https://doi.org/10.12973/eu-jer.11.3.1363.

Radanović, I., & Likić, R. (2018). Opportunities for use of blockchain technology in

medicine. Applied Health Economics and Health Policy, 16, 583–590.

https://doi.org/10.1007/s40258-018-0412-8.

Rajan, K. K., & Pandit, A. S. (2022). Comparing computer-assisted learning activities for

learning clinical neuroscience: A randomized control trial. BMC Medical Education, 22(1), 522. https://doi.org/10.1186/s12909-022-03578-2.

Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., &

Koffel, J. B. (2021). PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Systematic Reviews, 10, 1–19. https://doi.org/10.1186/s13643-020-01542-z.

Robinson-Garcia, N., Mongeon, P., Jeng, W., & Costas, R. (2017). DataCite as a

novel bibliometric source: Coverage, strengths and limitations. Journal of Informetrics, 11(3), 841–854. https://doi.org/10.1016/j.joi.2017.07.003.

Rouleau, G., Gagnon, M.-P., Côté, J., Payne-Gagnon, J., Hudson, E., Dubois, C.-A., &

Bouix-Picasso, J. (2019). Effects of e-learning in a continuing education context on nursing care: systematic review of systematic qualitative, quantitative, and mixed-studies reviews. Journal of Medical Internet Research, 21(10), e15118. https://doi.org/10.2196/15118.

Schoeneberger, C. A., McMillan, C. A., Kurup, P., Akar, S., Margolis, R., & Masanet, E.

(2020). Solar for industrial process heat: A review of technologies, analysis approaches, and potential applications in the United States. Energy, 206, 118083. https://doi.org/10.1016/j.energy.2020.118083.

Shvets, O., Murtazin, K., & Piho, G. (2020). Providing feedback for students in e-learning

systems: a literature review, based on ieee explore digital library. 2020 IEEE Global Engineering Education Conference (EDUCON), 284–289. https://doi.org/10.1109/EDUCON45650.2020.9125344.

Singh, H., & Miah, S. J. (2020). Smart education literature: A theoretical analysis. Education

and Information Technologies, 25(4), 3299–3328. https://doi.org/10.1007/s10639-020-10116-4.

Smith, N. (2018). Integrating Gamification into Mathematics Instruction: A Qualitative

Exploratory Case Study on the Perceptions of Teachers at the Fourth and Fifth Grade Level. Online Submission.

Tazouti, Y., Thomas, A., Hoareau, L., Jarlégan, A., Hubert, B., & Luxembourger, C. (2024).

Correction to: Assessment of an educational classroom app’s impact on preschoolers’ early numeracy skills. European Journal of Psychology of Education, 39(1), 29–30. https://doi.org/10.1007/s10212-023-00709-1.

Wang, S., Chen, Y., Lv, X., & Xu, J. (2023). Hot topics and frontier evolution of science

education research: A bibliometric mapping from 2001 to 2020. Science & Education, 32(3), 845–869. https://doi.org/10.1007/s11191-022-00337-z.

Wu, S. P. W., & Rau, M. A. (2019). How students learn content in science, technology,

engineering, and mathematics (STEM) through drawing activities. Educational Psychology Review, 31, 87–120. https://doi.org/10.1007/s10648-019-09467-3.

Zhan, X., Sun, D., Wen, Y., Yang, Y., & Zhan, Y. (2022). Investigating students’

engagement in mobile technology-supported science learning through video-based classroom observation. Journal of Science Education and Technology, 31(4), 514–527. https://doi.org/10.1007/s10956-022-09970-3.

Zhong, J., & Zheng, Y. (2022). Empowering future education: Learning in the Edu-

Metaverse. 2022 International Symposium on Educational Technology (ISET), 292–295. https://doi.org/10.1109/ISET55194.2022.00068.

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Published

2024-06-08

How to Cite

Nisa’, K. ., Indriana Safitri, A. ., & Mubarok, H. . (2024). How the Evolution and Track of Several Digital Technologies in Science Education?. JPPS (Jurnal Penelitian Pendidikan Sains), 13(2), 113–128. https://doi.org/10.26740/jpps.v13n2.p113-128

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