Research Article
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The Current Trend in Educational Neuroscience Research: A Descriptive and Bibliometric Study

Year 2022, Volume: 10 Issue: 19, 184 - 201, 23.04.2022
https://doi.org/10.18009/jcer.1002588

Abstract

In the present study, 36 articles indexed in the Web of Science database were examined in order to reveal the current trend in scientific studies in the field of educational neuroscience. Therefore, the distribution of the articles was examined considering publication years, host journals, the most productive author(s), co-authorship, abstract keywords, collocated keywords, educational attainment of the samples, dependent variables, and the EEG devices used. The data were evaluated with descriptive and bibliometric analysis methods. The findings revealed that the publishing in the field gained an elevation in 2020; the papers were mostly published in Computers & Education; Mayer was the most productive author; Cheng, Lin, Yang, and Huang were those who produced the most collaborative studies in the field. In addition, it was found out that the keyword “cognitive load” was discussed more than the others; it was used with “attention” the most; studies were mostly carried out at university level; cognitive load and attention were the most examined dependent variables; the NeuroSky Mindwave was used in these articles the most. To sum, the present results have the potential to generate an overall perspective to educational neuroscience.

References

  • Ansari, D., Coch, D., & De Smedt, B. (2011). Connecting education and cognitive neuroscience: Where will the journey take us?. Educational philosophy and theory, 43(1), 37-42. https://doi.org/10.1111/j.1469-5812.2010.00705.x
  • Çakmak, E. K. (2007). The bottle neck in multimedia: Cognitive overload. Gazi University Gazi The Journal of Educational Faculty, 27(2), 1-24. http://www.gefad.gazi.edu.tr/en/pub/issue/6750/90766
  • Deryakulu, D., Atal, D., ve Sancar, R. (2019). Eğitimsel sinirbilim ve eğitim teknolojisi açısından doğurguları. (Editörler: A. İşman, H. F. Odabaşı ve B. Akkoyunlu). Eğitim Teknolojileri Okumaları 2019 içinde (ss. 331-348). Pegem Akademi.
  • Duman, B. (2015). Neden beyin temelli öğrenme? Pegem Akademi.
  • Dündar, S., (2013). The investigation of students' brain waves in the problem solving process (Unpublished Doctoral Dissertation). Gazi University.
  • Feiler, J. B., & Stabio, M. E. (2018). Three pillars of educational neuroscience from three decades of literature. Trends in neuroscience and education, 13, 17-25. https://doi.org/10.1016/j.tine.2018.11.001
  • Ferrari, M. (2011). What can neuroscience bring to education?. Educational Philosophy and Theory, 43(1), 31-36. https://doi.org/10.1111/j.1469-5812.2010.00704.x
  • Gürlen, E., Özdiyar, Ö., & Şen, Z. (2018). Social network analysis of academic studies on gifted people. Education and Science, 44(197), 185-208. http://dx.doi.org/10.15390/EB.2018.7735
  • İkiz, Y. D. (2021). An investigation of cognitive load effect using augmented reality glasses in an automotive assembly line (Unpublished Master Dissertation). Bursa Uludağ University.
  • Koçak, G. (2020). Reflections of brain researches to education: Toward education of future. Yeditepe University the Journal of Educational Faculty, 9(11), 1-16. https://dergipark.org.tr/tr/pub/edu7/issue/59006/731860
  • Morshad, S., Mazumder, M. R., & Ahmed, F. (2020, January). Analysis of brain wave data using Neurosky Mindwave Mobile II. In Proceedings of the International Conference on Computing Advancements (pp. 1-4). https://doi.org/10.1145/3377049.3377053
  • Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32, 9-31. https://www.jstor.org/stable/41953635
  • Sweller, J., van Merrienboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review. 31, 261-292. https://doi.org/10.1007/s10648-019-09465-5
  • Tabakcıoğlu, M., Çizmeci, H., & Ayberkin, D. (2016). Neurosky EEG biosensor using in education. International Journal of Applied Mathematics Electronics and Computers, 76-78. https://doi.org/10.18100/ijamec.265371
  • Varma, S., McCandliss, B. D., & Schwartz, D. L. (2008). Scientific and pragmatic challenges for bridging education and neuroscience. Educational researcher, 37(3), 140-152. https://doi.org/10.3102/0013189X08317687
  • Yazgan, E., & Korurek, K. M., (1996). Tıp elektroniği. İ.T.Ü. Matbaası.

The Current Trend in Educational Neuroscience Research: A Descriptive and Bibliometric Study

Year 2022, Volume: 10 Issue: 19, 184 - 201, 23.04.2022
https://doi.org/10.18009/jcer.1002588

Abstract

In the present study, 36 articles indexed in the Web of Science database were examined in order to reveal the current trend in scientific studies in the field of educational neuroscience. Therefore, the distribution of the articles was examined considering publication years, host journals, the most productive author(s), co-authorship, abstract keywords, collocated keywords, educational attainment of the samples, dependent variables, and the EEG devices used. The data were evaluated with descriptive and bibliometric analysis methods. The findings revealed that the publishing in the field gained an elevation in 2020; the papers were mostly published in Computers & Education; Mayer was the most productive author; Cheng, Lin, Yang, and Huang were those who produced the most collaborative studies in the field. In addition, it was found out that the keyword “cognitive load” was discussed more than the others; it was used with “attention” the most; studies were mostly carried out at university level; cognitive load and attention were the most examined dependent variables; the NeuroSky Mindwave was used in these articles the most. To sum, the present results have the potential to generate an overall perspective to educational neuroscience.

References

  • Ansari, D., Coch, D., & De Smedt, B. (2011). Connecting education and cognitive neuroscience: Where will the journey take us?. Educational philosophy and theory, 43(1), 37-42. https://doi.org/10.1111/j.1469-5812.2010.00705.x
  • Çakmak, E. K. (2007). The bottle neck in multimedia: Cognitive overload. Gazi University Gazi The Journal of Educational Faculty, 27(2), 1-24. http://www.gefad.gazi.edu.tr/en/pub/issue/6750/90766
  • Deryakulu, D., Atal, D., ve Sancar, R. (2019). Eğitimsel sinirbilim ve eğitim teknolojisi açısından doğurguları. (Editörler: A. İşman, H. F. Odabaşı ve B. Akkoyunlu). Eğitim Teknolojileri Okumaları 2019 içinde (ss. 331-348). Pegem Akademi.
  • Duman, B. (2015). Neden beyin temelli öğrenme? Pegem Akademi.
  • Dündar, S., (2013). The investigation of students' brain waves in the problem solving process (Unpublished Doctoral Dissertation). Gazi University.
  • Feiler, J. B., & Stabio, M. E. (2018). Three pillars of educational neuroscience from three decades of literature. Trends in neuroscience and education, 13, 17-25. https://doi.org/10.1016/j.tine.2018.11.001
  • Ferrari, M. (2011). What can neuroscience bring to education?. Educational Philosophy and Theory, 43(1), 31-36. https://doi.org/10.1111/j.1469-5812.2010.00704.x
  • Gürlen, E., Özdiyar, Ö., & Şen, Z. (2018). Social network analysis of academic studies on gifted people. Education and Science, 44(197), 185-208. http://dx.doi.org/10.15390/EB.2018.7735
  • İkiz, Y. D. (2021). An investigation of cognitive load effect using augmented reality glasses in an automotive assembly line (Unpublished Master Dissertation). Bursa Uludağ University.
  • Koçak, G. (2020). Reflections of brain researches to education: Toward education of future. Yeditepe University the Journal of Educational Faculty, 9(11), 1-16. https://dergipark.org.tr/tr/pub/edu7/issue/59006/731860
  • Morshad, S., Mazumder, M. R., & Ahmed, F. (2020, January). Analysis of brain wave data using Neurosky Mindwave Mobile II. In Proceedings of the International Conference on Computing Advancements (pp. 1-4). https://doi.org/10.1145/3377049.3377053
  • Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32, 9-31. https://www.jstor.org/stable/41953635
  • Sweller, J., van Merrienboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review. 31, 261-292. https://doi.org/10.1007/s10648-019-09465-5
  • Tabakcıoğlu, M., Çizmeci, H., & Ayberkin, D. (2016). Neurosky EEG biosensor using in education. International Journal of Applied Mathematics Electronics and Computers, 76-78. https://doi.org/10.18100/ijamec.265371
  • Varma, S., McCandliss, B. D., & Schwartz, D. L. (2008). Scientific and pragmatic challenges for bridging education and neuroscience. Educational researcher, 37(3), 140-152. https://doi.org/10.3102/0013189X08317687
  • Yazgan, E., & Korurek, K. M., (1996). Tıp elektroniği. İ.T.Ü. Matbaası.
There are 16 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Article
Authors

Şenol Saygıner This is me 0000-0002-5280-3847

Fatih Balaman 0000-0003-2175-0778

Sevil Hanbay Tiryaki 0000-0003-4780-9715

Early Pub Date April 19, 2022
Publication Date April 23, 2022
Submission Date September 30, 2021
Acceptance Date April 1, 2022
Published in Issue Year 2022 Volume: 10 Issue: 19

Cite

APA Saygıner, Ş., Balaman, F., & Hanbay Tiryaki, S. (2022). The Current Trend in Educational Neuroscience Research: A Descriptive and Bibliometric Study. Journal of Computer and Education Research, 10(19), 184-201. https://doi.org/10.18009/jcer.1002588

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