A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions

Galiya A. Abayeva; Gulzhan S. Orazayeva; Saltanat J. Omirbek; Gaukhar B. Ibatova; Venera G. Zakirova; Vera K. Vlasova

doi:10.30935/cedtech/13648

Galiya A. Abayeva ¹, Gulzhan S. Orazayeva ², Saltanat J. Omirbek ², Gaukhar B. Ibatova ¹, Venera G. Zakirova ³ ^* , Vera K. Vlasova ³

More Detail

CONT ED TECHNOLOGY, Volume 15, Issue 4, Article No: ep471

https://doi.org/10.30935/cedtech/13648

Submitted: 28 July 2023, Published Online: 07 September 2023

OPEN ACCESS 1485 Views 1067 Downloads

Download Full Text (PDF)

Abstract

The concept of ubiquitous learning has emerged as a pedagogical approach in response to the advancements made in mobile, wireless communication, and sensing technologies. The domain of ubiquitous learning is distinguished by swift progression, thereby presenting a difficulty in maintaining current knowledge of its developments. The implementation of bibliometric analysis would enable the tracking of its development and current status. The objective of the present investigation is to perform a thorough bibliometric examination of the domain of ubiquitous learning. This research aims to discern significant attributes, patterns, and influencers within the discipline by analyzing scholarly works. The primary objective of this study is to provide a comprehensive depiction of the salient characteristics and patterns exhibited by the datasets employed in ubiquitous learning research, namely Scopus, Web of Science (WoS), and merged datasets. Additionally, the study seeks to trace the historical development of publications in this domain and to ascertain the most noteworthy publications and authors that have exerted a significant impact on this field. This study provides an extensive bibliometric analysis of ubiquitous learning, examining output from Scopus, WoS, and a merged dataset. It highlights the field’s growth and the rising use of diverse data sources, with Scopus and the merged dataset revealing broader insights. The analysis reveals an interest peak in 2016 and a subsequent decline likely due to incomplete recent data. Documents, predominantly articles, differ across databases, underscoring the unique contributions of each. The study identifies “Lecture Notes in Computer Science” and “Ubiquitous Learning” as major research sources. It recognizes Hwang, G.-J. as a highly influential author, with Asian institutions leading in research output. However, Western institutions also show strong representation in WoS and merged databases. Despite variations in total citation counts, countries like China, Switzerland, and Ireland contribute significantly to the field. Terms like “mobile learning” and “life log” have vital roles in bridging research clusters, while thematic maps reveal evolving trends like mobile learning and learning analytics. The collaborative structure and key figures in ubiquitous learning are illuminated through network analysis, emphasizing the importance of cross-database analysis for a comprehensive view of the field.

Keywords: bibliometric analysis, Scopus, ubiquitous learning, WoS

References

Alioon, Y., & Delialioglu, O. (2019). The effect of authentic m-learning activities on student engagement and motivation. British Journal of Educational Technology, 50(2), 655-668. https://doi.org/10.1111/bjet.12559
Allcoat, D., Hatchard, T., Azmat, F., Stansfield, K., Watson, D., & von Mühlenen, A. (2021). Education in the digital age: Learning experience in virtual and mixed realities. Journal of Educational Computing Research, 59(5), 795-816. https://doi.org/10.1177/0735633120985120
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Bdiwi, R., Runz, C. De, Faiz, S., & Cherif, A. A. (2018). A blockchain based decentralized platform for ubiquitous learning environment. In Proceedings of the 18^th International Conference on Advanced Learning Technologies (pp. 90-92). https://doi.org/10.1109/ICALT.2018.00028
Caputo, A., & Kargina, M. (2022). A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis. Journal of Marketing Analytics, 10(1), 82-88. https://doi.org/10.1057/s41270-021-00142-7
Cárdenas-Robledo, L. A., & Peña-Ayala, A. (2018). Ubiquitous learning: A systematic review. Telematics and Informatics, 35(5), 1097-1132. https://doi.org/10.1016/j.tele.2018.01.009
Chen, C. C., & Huang, T. C. (2012). Learning in a u-museum: Developing a context-aware ubiquitous learning environment. Computers and Education, 59(3), 873-883. https://doi.org/10.1016/j.compedu.2012.04.003
Chen, N. S., Wei, C. W., Huang, Y. C., & Kinshuk. (2013). The integration of print and digital content for providing learners with constructive feedback using smartphones. British Journal of Educational Technology, 44(5), 837-845. https://doi.org/10.1111/j.1467-8535.2012.01371.x
Chu, H.-C., Hwang, G.-J., & Tsai, C.-C. (2010a). A knowledge engineering approach to developing mindtools for context-aware ubiquitous learning. Computers & Education, 54(1), 289-297. https://doi.org/10.1016/j.compedu.2009.08.023
Chu, H.-C., Hwang, G.-J., Tsai, C.-C., & Tseng, J. C. R. (2010b). A two-tier test approach to developing location-aware mobile learning systems for natural science courses. Computers & Education, 55(4), 1618-1627. https://doi.org/10.1016/j.compedu.2010.07.004
Cope, B., & Kalantzis, M. (2010). Ubiquitous learning: An agenda for educational transformation. University of Illinois Press.
Davies, D., Beauchamp, G., Davies, J., & Price, R. (2020). The potential of the ‘Internet of things’ to enhance inquiry in Singapore schools. Research in Science and Technological Education, 38(4), 484-506. https://doi.org/10.1080/02635143.2019.1629896
De Lourdes Martínez-Villaseñor, M., González-Mendoza, M., & Valle, I. D. Del. (2014). Enrichment of learner profile with ubiquitous user model interoperability. Computacion y Sistemas [Computing and Systems], 18(2), 359-374. https://doi.org/10.13053/CyS-18-2-2014-037
Díaz, J. E. M. (2020). Virtual world as a complement to hybrid and mobile learning. International Journal of Emerging Technologies in Learning, 15(22), 267-274. https://doi.org/10.3991/ijet.v15i22.14393
Echchakoui, S. (2020). Why and how to merge Scopus and Web of Science during bibliometric analysis: The case of sales force literature from 1912 to 2019. Journal of Marketing Analytics, 8(3), 165-184. https://doi.org/10.1057/s41270-020-00081-9
Fakomogbon, M. A., & Bolaji, H. O. (2017). Effects of collaborative learning styles on performance of students in a ubiquitous collaborative mobile learning environment. Contemporary Educational Technology, 8(3), 268-279. https://doi.org/10.30935/cedtech/6200
Farooq, R. (2022). 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
Fernández-Batanero, J. M., Cabero-Almenara, J., Román-Graván, P., & Palacios-Rodríguez, A. (2022). Knowledge of university teachers on the use of digital resources to assist people with disabilities. The case of Spain. Education and Information Technologies, 27, 9015-9029. https://doi.org/10.1007/s10639-022-10965-1
Fidai, A., Kwon, H., Buettner, G., Capraro, R. M., Capraro, M. M., Jarvis, C., Benzor, M., & Verma, S. (2019). Internet of things (IoT) instructional devices in STEM classrooms: Past, present and future directions. In Proceedings of the Frontiers in Education Conference. https://doi.org/10.1109/FIE43999.2019.9028679
Frohberg, D., Göth, C., & Schwabe, G. (2009). Mobile learning projects–A critical analysis of the state of the art. Journal of Computer Assisted Learning, 25(4), 307-331. https://doi.org/10.1111/j.1365-2729.2009.00315.x
Garzón, J. (2021). An overview of twenty-five years of augmented reality in education. Multimodal Technologies and Interaction, 5(7), 37. https://doi.org/10.3390/mti5070037
Graf, S., & Kinshuk. (2008). Adaptivity and personalization in ubiquitous learning systems. In A. Holzinger (Ed.), Proceedings of the HCI and Usability for Education and Work. Springer. https://doi.org/10.1007/978-3-540-89350-9_23
Guillén-Gámez, F. D., Lugones, A., Mayorga-Fernández, M. J., & Wang, S. (2019). ICT use by pre-service foreign languages teachers according to gender, age and motivation. Cogent Education, 6(1), 1-17. https://doi.org/10.1080/2331186X.2019.1574693
Hua, Z. A. (2010). Study of ubiquitous learning environment based on ubiquitous computing. In Proceedings of the 3^rd IEEE International Conference on Ubi-Media Computing (pp. 136-138). https://doi.org/10.1109/UMEDIA.2010.5544482
Hwang, G.-J. (2014). Definition, framework and research issues of smart learning environments–A context-aware ubiquitous learning perspective. Smart Learning Environments, 1(1), 1-14. https://doi.org/10.1186/s40561-014-0004-5
Hwang, G.-J., & Tsai, C.-C. (2011). Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 42(4), E65-E70. https://doi.org/10.1111/j.1467-8535.2011.01183.x
Hwang, G.-J., & Wu, P. H. (2014). Applications, impacts and trends of mobile technology-enhanced learning: A review of 2008-2012 publications in selected SSCI journals. International Journal of Mobile Learning and Organization, 8(2), 83. https://doi.org/10.1504/IJMLO.2014.062346
Hwang, G.-J., Shi, Y. R., & Chu, H. C. (2011). A concept map approach to developing collaborative mindtools for context-aware ubiquitous learning. British Journal of Educational Technology, 42(5), 778-789. https://doi.org/10.1111/j.1467-8535.2010.01102.x
Hwang, G.-J., Tsai, C.-C., & Yang, S. J. H. (2008). Criteria, strategies and research issues of context-aware ubiquitous learning. Educational Technology and Society, 11(2), 81-91.
Hwang, G.-J., Yang, T.-C., Tsai, C.-C., & Yang, S. J. H. (2009). A context-aware ubiquitous learning environment for conducting complex science experiments. Computers & Education, 53(2), 402-413. https://doi.org/10.1016/j.compedu.2009.02.016
Kaur, J., & Kaur, K. (2017). Internet of things: A review on technologies, architecture, challenges, applications, future trends. International Journal of Computer Network and Information Security, 9(4), 57-70. https://doi.org/10.5815/ijcnis.2017.04.07
Lin, M.-H., Chen, H.-C., & Liu, K.-S. (2017). A study of the effects of digital learning on learning motivation and learning outcome. EURASIA Journal of Mathematics Science and Technology Education, 13(7), 3553-3564. https://doi.org/10.12973/eurasia.2017.00744a
Liu, T.-Y., & Chu, Y.-L. (2010). Using ubiquitous games in an English listening and speaking course: Impact on learning outcomes and motivation. Computers & Education, 55(2), 630-643. https://doi.org/10.1016/j.compedu.2010.02.023
López-Belmonte, J., Parra-González, M. E., Segura-Robles, A., & Pozo-Sánchez, S. (2020). Scientific mapping of gamification in web of science. European Journal of Investigation in Health, Psychology and Education, 10(3), 832-847. https://doi.org/10.3390/ejihpe10030060
Makodamayanti, S., Nirmala, D., & Kepirianto, C. (2020). The use of digital media as a strategy for lowering anxiety in learning English as a foreign language. Culturalistics: Journal of Cultural, Literary, and Linguistic Studies, 4(1), 22-26. https://doi.org/10.14710/culturalistics.v4i1.8187
Marinagi, C., Skourlas, C., & Belsis, P. (2013). Employing ubiquitous computing devices and technologies in the higher education classroom of the future. Procedia-Social and Behavioral Sciences, 73, 487-494. https://doi.org/10.1016/j.sbspro.2013.02.081
Matthew, U., Kazaure, J., & Okafor, N. (2018). Contemporary development in e-learning education, cloud computing technology & internet of things. EAI Endorsed Transactions on Cloud Systems, 7(20), 169173. https://doi.org/10.4108/eai.31-3-2021.169173
Nikou, S. A., & Economides, A. A. (2021). A framework for mobile-assisted formative assessment to promote students’ self-determination. Future Internet, 13(5), 116. https://doi.org/10.3390/fi13050116
Ogata, H., & Yano, Y. (2004). Context-aware support for computer-supported ubiquitous learning. In Proceedings of the 2^nd IEEE International Workshop on Wireless and Mobile Technologies in Education (pp. 27-34). https://doi.org/10.1109/WMTE.2004.1281330
Panjaburee, P., & Srisawasdi, N. (2018). The opportunities and challenges of mobile and ubiquitous learning for future schools: A context of Thailand. Knowledge Management and E-Learning, 10(4), 485-506. https://doi.org/10.34105/j.kmel.2018.10.030
Park, Y. (2011). A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distributed Learning, 12(2), 78. https://doi.org/10.19173/irrodl.v12i2.791
Pimmer, C., Mateescu, M., & Gröhbiel, U. (2016). Mobile and ubiquitous learning in higher education settings: A systematic review of empirical studies. Computers in Human Behavior, 63, 490-501. https://doi.org/10.1016/j.chb.2016.05.057
Roach, K., Tilley, E., & Mitchell, J. (2018). How authentic does authentic learning have to be? Higher Education Pedagogies, 3(1), 495-509. https://doi.org/10.1080/23752696.2018.1462099
Sotiriadou, P., Logan, D., Daly, A., & Guest, R. (2019). The role of authentic assessment to preserve academic integrity and promote skill development and employability. Studies in Higher Education, 45(11), 2132-2148. https://doi.org/10.1080/03075079.2019.1582015
Suartama, I. K., Setyosari, P., Sulthoni, Ulfa, S., Yunus, M., & Sugiani, K. A. (2021). Ubiquitous learning vs. electronic learning: A comparative study on learning activeness and learning achievement of students with different self-regulated learning. International Journal of Emerging Technologies in Learning, 16(3), 36-56. https://doi.org/10.3991/ijet.v16i03.14953
Sudakova, N. E., Savina, T. N., Masalimova, A. R., Mikhaylovsky, M. N., Karandeeva, L. G., & Zhdanov, S. P. (2022). Online formative assessment in higher education: Bibliometric analysis. Education Sciences, 12(3), 209. https://doi.org/10.3390/educsci12030209
Thongkoo, K., Panjaburee, P., & Daungcharone, K. (2019). A development of ubiquitous learning support system based on an enhanced inquiry-based learning approach. International Journal of Mobile Learning and Organization, 13(2), 129-151. https://doi.org/10.1504/IJMLO.2019.098179
Virtanen, M. A., Haavisto, E., Liikanen, E., & Kääriäinen, M. (2018). Ubiquitous learning environments in higher education: A scoping literature review. Education and Information Technologies, 23(2), 985-998. https://doi.org/10.1007/s10639-017-9646-6
Wang, J., Wang, J., Qin, J., Wang, W., & Yang, W. (2020). Power marketing ubiquitous learning mode based on QR code of the Internet of things. In Proceedings of the 2020 International Conference on Artificial Intelligence and Communication Technology (pp. 34-39).
Wannapiroon, P., Kaewrattanapat, N., & Premsmith, J. (2019). Development of cloud learning management systems for higher education institutions. In Proceedings of the Research, Invention, and Innovation Congress. https://doi.org/10.1109/RI2C48728.2019.8999877
Weeber, M., Gebbe, C., Lutter-Günther, M., Böhner, J., Glasschroeder, J., Steinhilper, R., & Reinhart, G. (2016). Extending the scope of future learning factories by using synergies through an interconnection of sites and process chains. Procedia CIRP, 54, 124-129. https://doi.org/10.1016/j.procir.2016.04.102
Yang, S. J. H. (2006). Context aware ubiquitous learning environments for peer-to-peer collaborative learning. Educational Technology & Society, 9(1), 188-201.
Zammarchi, G., & Conversano, C. (2021). Application of eye tracking technology in medicine: A bibliometric analysis. Vision, 5(4), 56. https://doi.org/10.3390/vision5040056

Citation

Abayeva, G. A., Orazayeva, G. S., Omirbek, S. J., Ibatova, G. B., Zakirova, V. G., & Vlasova, V. K. (2023). A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions. Contemporary Educational Technology, 15(4), ep471. https://doi.org/10.30935/cedtech/13648

Abayeva, G. A., Orazayeva, G. S., Omirbek, S. J., Ibatova, G. B., Zakirova, V. G., and Vlasova, V. K. (2023). A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions. Contemporary Educational Technology, 15(4), ep471. https://doi.org/10.30935/cedtech/13648

Abayeva GA, Orazayeva GS, Omirbek SJ, Ibatova GB, Zakirova VG, Vlasova VK. A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions. CONT ED TECHNOLOGY. 2023;15(4), ep471. https://doi.org/10.30935/cedtech/13648

Abayeva, Galiya A., Gulzhan S. Orazayeva, Saltanat J. Omirbek, Gaukhar B. Ibatova, Venera G. Zakirova, and Vera K. Vlasova. "A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions". Contemporary Educational Technology 2023 15 no. 4 (2023): ep471. https://doi.org/10.30935/cedtech/13648

Abayeva, Galiya A. et al. "A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions". Contemporary Educational Technology, vol. 15, no. 4, 2023, ep471. https://doi.org/10.30935/cedtech/13648

Abayeva GA, Orazayeva GS, Omirbek SJ, Ibatova GB, Zakirova VG, Vlasova VK. A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions. CONT ED TECHNOLOGY. 2023;15(4):ep471. https://doi.org/10.30935/cedtech/13648