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Investigating the brain wave activities of middle school students during the implementation of STEM-based digital creativity practices

Year 2025, Volume: 12 Issue: 2, 203 - 219
https://doi.org/10.5281/zenodo.17271022

Abstract

This study explores when students engage in creative thinking during STEM activities designed to foster such skills. The significance of this research lies in its focus on scientific creativity from a neurophysiological perspective, aiming to provide insights into the brain mechanisms underlying creative thinking in educational contexts. The purpose of the study is to examine the effectiveness of specially designed STEM activities in fostering students’ scientific creativity by analyzing their brain wave patterns during different stages of participation. A case study design was adopted to enable an in-depth exploration of the phenomenon. To monitor brain activity throughout different stages of the activities, a wireless EEG headset was used. Specifically, a NeuroSky MindWave Mobile 2 wireless EEG headset and the EEGID Data-Record application were employed for brainwave measurement, while a semi-structured interview form was used to collect students’ views. Analysis focused on alpha frequency amplitudes as indicators of cognitive engagement during creative tasks. Quantitative data were analyzed using statistical tests in SPSS, and qualitative data were examined through content analysis to identify patterns in students’ experiences. Results showed increased alpha activity during the active phases of creativity-focused tasks, suggesting heightened cognitive involvement. Although statistical analyses were conducted on these patterns, no significant differences were observed—likely due to the small sample size. To better understand contextual factors influencing EEG data, students’ experiences were also gathered through semi-structured interviews. Students generally viewed the EEG device as suitable for individual use but found it less practical in classroom settings. Overall, the findings indicate that the developed STEM activities hold promise for supporting creative thinking in science education. The study underscores the value of integrating neurophysiological measurements with educational interventions to better understand learning processes. However, broader data collection—particularly in classroom environments—is needed to strengthen generalizability.

Ethical Statement

This study was conducted in accordance with ethical standards. Ethical approval was obtained from the Ethics Committee of Aydın Adnan Menderes University

Supporting Institution

This study was supported by funding from TUBİTAK (The Scientific and Technological Research Council of Türkiye).

Project Number

121K847

Thanks

This study was conducted as part of a TÜBİTAK 1002 project (The Scientific and Technological Research Council of Türkiye).

References

  • Abraham, A., & Bubic, A. (2015). Semantic memory as the root of imagination. Frontiers in Psychology, 6, 325.
  • Abraham, A. (2013). The promises and perils of the neuroscience of creativity. Frontiers in Human Neuroscience, 7. https://doi.org/10.3389/fnhum.2013.00246
  • Amabile, T. M. (1983). The social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45(2), 357–376. https://doi.org/10.1037/0022-3514.45.2.357
  • Arden, R., Chavez, R. S., Grazioplene, R., & Jung, R. E. (2010). Neuroimaging creativity: A psychometric view. Behavioral Brain Research, 214(2), 143-156.
  • Beghetto, R. A., & Kaufman, J. C. (2014). Classroom contexts for creativity. High Ability Studies, 25(1), 53–69. https://doi.org/10.1080/13598139.2014.905247
  • Bennett, N., Borg, W. R., & Gall, M. D. (1984). Educational research: An introduction. British Journal of Educational Studies, 32(3), 274. https://doi.org/10.2307/3121583
  • Bigdeli, S. (2012). New educational research era: Educational neuroscience technology. International Journal of Learning and Teaching, 4(1), 14-25.
  • Bitner, R., Le, N.-T., & Pinkwart, N. (2020). A concurrent validity approach for eeg-based feature classification algorithms in learning analytics. In Computational collective intelligence (pp. 568–580). Springer International Publishing. https://doi.org/10.1007/978-3-030-63007-2_44
  • Borling, J. E. (1981). The effects of sedative music on alpha rhythms and focused attention in high-creative and low-creative subjects. Journal of Music Therapy, 18(2), 101–108. https://doi.org/10.1093/jmt/18.2.101
  • Boynton, T. (2001). Applied research using alpha/theta training for enhancing creativity and well-being. Journal of Neurotherapy, 5(1-2), 5–18. https://doi.org/10.1300/j184v05n01_02
  • Bulut Ates, C. (2023). Investigating scientific creativity in science education in terms of neurophysiological approach. Doctoral dissertation, Aydin Adnan Menderes University, Aydin, Turkey.
  • Cheng, V. M. Y. (2010). Tensions and dilemmas of teachers in creativity reform in a Chinese context. Thinking Skills and Creativity, 5(3), 120–137. https://doi.org/10.1016/j.tsc.2010.09.005
  • Chi, R. P., & Snyder, A. W. (2011). Facilitate insight by non-invasive brain stimulation. PLoS ONE, 6(2), e16655.
  • Cropley, A. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3), 391–404. https://doi.org/10.1207/s15326934crj1803_13
  • Davis, G. A. (2011). Barriers to creativity and creative attitudes. In Encyclopedia of creativity (pp. 115–121). Elsevier. https://doi.org/10.1016/b978-0-12-375038-9.00021-2
  • De Bono, E. (1985). The practical teaching of thinking using the cort method. Special Services in the Schools, 3(1– 2), 33–47. https://doi.org/10.1300/j008v03n01_04
  • Dietrich, A., & Kanso, R. (2010). A review of EEG, ERP, and neuroimaging studies of creativity and insight. Psychological Bulletin, 136(5), 822–848. https://doi.org/10.1037/a0019749
  • Dundar, S., & Ayvaz, U. (2016). From cognitive to educational neuroscience. International Education Studies, 9(9), 50. https://doi.org/10.5539/ies.v9n9p50
  • Erat, K., & Onay Durdu, P. (2021). User experience evaluation of low cost EEG headsets. Pamukkale University Journal of Engineering Sciences, 27(5), 646–659. https://doi.org/10.5505/pajes.2021.78910
  • Fink, A., Schwab, D., & Papousek, I. (2011). Sensitivity of EEG upper alpha activity to cognitive and affective creativity interventions. International Journal of Psychophysiology, 82(3), 233–239. https://doi.org/10.1016/j.ijpsycho.2011.09.003
  • Fink, A., Benedek, M., Grabner, R., Staudt, B., & Neubauer, A. (2007). Creativity meets neuroscience: Experimental tasks for the neuroscientific study of creative thinking. Methods, 42(1), 68–76. https://doi.org/10.1016/j.ymeth.2006.12.001
  • Fink, T. E. (2012). The enhancement of Neurofeedback with a low cost and easy-to-use NeuroSky EEG biofeedback training device: The MindReflectorProtocols. MindReflector Technologies LLC, 3.
  • Fong, S. S. M. (2015). Single-channel electroencephalographic recording in children with developmental coordination disorder: Validity and influence of eye blink artifacts. Journal of Novel Physiotherapies, 05(04). https://doi.org/10.4172/2165-7025.1000270
  • Geake, J. G. (2009). The brain at school: Educational neuroscience in the classroom. McGraw Hill/Open University Press.
  • Grierson, M., & Kiefer, C. (2011). Better Brain Interfacing for the masses. CHI ’11 Extended Abstracts on Human Factors in Computing Systems. https://doi.org/10.1145/1979742.1979828
  • Guilford, J. P. (1967). Creativity: Yesterday, today and tomorrow. The Journal of Creative Behavior, 1(1), 3–14. https://doi.org/10.1002/j.2162-6057.1967.tb00002.x
  • Haier, R. J., & Jung, R. E. (2008). Brain imaging studies of intelligence and creativity: What is the picture for education? Roeper Review, 30(3), 171–180. https://doi.org/10.1080/02783190802199347
  • Hennessey, B. A., & Amabile, T. M. (2010). Creativity. Annual Review of Psychology, 61, 569-598.
  • Howard-Jones, P. A., Varma, S., Ansari, D., Butterworth, B., De Smedt, B., Goswami, U., Laurillard, D., & Thomas, M. S. C. (2016). The principles and practices of educational neuroscience: Comment on bowers (2016). Psychological Review, 123(5), 620–627. https://doi.org/10.1037/rev0000036
  • Jaušovec, N. (2000). Differences in cognitive processes between gifted, intelligent, creative, and average individuals while solving complex problems: An EEG study. Intelligence, 28(3), 213–237. https://doi.org/10.1016/s0160-2896(00)00037-4
  • Jung, R. E., Segall, J. M., Jeremy, B., Flores, R. A., Smith, S. M., Chavez, R. S., ... & Haier, R. J. (2010). Neuroanatomy of creativity. Human Brain Mapping, 31(3), 398-409.
  • Kaygısız, Ç. “Educational neuroscience: Issues and challenges.” Erciyes Journal of Education, vol. 6, no. 1, 31 May 2022, pp. 80–98, https://doi.org/10.32433/eje.990407.
  • Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2-3), 169–195. https://doi.org/10.1016/s0165-0173(98)00056-3
  • Koudelková, Z., & Strmiska, M. (2018). Introduction to the identification of brain waves based on their frequency. In MATEC Web of Conferences. EDP Sciences.
  • Liu, C.-J., & Huang, C.-F. (2015). Innovative science educational neuroscience: Strategies for engaging brain waves in science education research. In Science education research and practices in taiwan (pp. 233–247). Springer Singapore. https://doi.org/10.1007/978-981-287-472-6_12
  • Lustenberger, C., Boyle, M. R., Foulser, A. A., Mellin, J. M., & Fröhlich, F. (2015). Functional role of frontal alpha oscillations in creativity. Cortex, 67, 74–82. https://doi.org/10.1016/j.cortex.2015.03.012
  • Mareschal, D., Butterworth, B., & Tolmie, A. (Eds.). (2013). Educational neuroscience. John Wiley & Sons.
  • Michel, C. M., & Murray, M. M. (2012). Towards the utilization of EEG as a brain imaging tool. NeuroImage, 61(2), 371–385. https://doi.org/10.1016/j.neuroimage.2011.12.039
  • National Research Council. (2009). Learning Science Through Computer Games and Simulations. National Academies Press.
  • NeuroSky, I. (n.d.). Brain Wave Signal (EEG) of NeuroSky. NeuroSky Brain-Computer Interface Technologies, 22.
  • Nedvědová, M., & Marek, J. (2018). Comparing EEG signals and emotions provoked by images with different aesthetic variables using emotive insight and neurosky mindwave. In 17th Conference on Applied Mathematics APLIMAT 2018: proceedings. Slovenská technická univezita v Bratislave.
  • Niedermeyer, E., & da Silva, F. H., 1935- (Eds.). (2005). Electroencephalography: Basic principles, clinical applications, and related fields (5th ed.). Lippincott Williams & Wilkins.
  • Onton, J. (2009). High-frequency broadband modulation of electroencephalographic spectra. Frontiers in Human Neuroscience, 3. https://doi.org/10.3389/neuro.09.061.2009
  • Qu, X., Sun, Y., Sekuler, R., & Hickey, T. (2018). EEG markers of STEM learning. In 2018 IEEE frontiers in education conference (FIE). IEEE. https://doi.org/10.1109/fie.2018.8659031
  • Ringtved, U. L., Larsen, T., Toftegaard, L. L., Schack, L. M. W., Stougaard, M. K., & Mortensen, A. (2017, October). Tracing students' attention through the Neurosky MindWave headset. In LASI-Nordic 2017: Learning Analytics (late) Summer Institute.
  • Osburn, H. K., & Mumford, M. D. (2006). Creativity and planning: Training interventions to develop creative problem-solving skills. Creativity Research Journal, 18(2), 173–190. https://doi.org/10.1207/s15326934crj1802_4
  • Poldrack, R. A., & Farah, M. J. (2015). Progress and challenges in probing the human brain. Nature, 526(7573), 371–379. https://doi.org/10.1038/nature15692
  • Ray, W. J., & Cole, H. W. (1985). EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes. Science, 228(4700), 750-752.
  • Robinson, K. (2006). Do schools kill creativity? In Presentation at TED2006 conference, Monterey, CA.
  • Rominger, C., Gubler, D. A., Makowski, L. M., & Troche, S. J. (2022). More creative ideas are associated with increased right posterior power and frontal-parietal/occipital coupling in the upper alpha band: A within- subjects study. International Journal of Psychophysiology. https://doi.org/10.1016/j.ijpsycho.2022.08.012
  • Runco, M. A. (2014). “Big C, little c” creativity as a false dichotomy: Reality is not categorical. Creativity Research Journal, 26(1), 131–132. https://doi.org/10.1080/10400419.2014.873676
  • Runco, M. A., & Jaeger, G. J. (2012). The standard definition of creativity. Creativity Research Journal, 24(1), 92– 96. https://doi.org/10.1080/10400419.2012.650092
  • Sahu, M., Shukla, P., Chandel, A., Jain, S., & Verma, S. (2020). Eye blinking classification through neurosky mindwave headset using eegid tool. In Advances in intelligent systems and computing (pp. 789–799). Springer Singapore. https://doi.org/10.1007/978-981-15-5113-0_65
  • Sawyer, K. (2011). The cognitive neuroscience of creativity: A critical review. Creativity Research Journal, 23(2), 137–154. https://doi.org/10.1080/10400419.2011.571191
  • Schicktanz, N., Schwabe, L., & Grosbras, M. H. (2020). Exploring the neural basis of creativity in language using TMS. NeuroImage, 204, 116255.
  • Sezer, A., İnel, Y., Seçkin, A. Ç., & Uluçınar, U. (2015, May). An investigation of university students’ attention levels in real classroom settings with NeuroSky’s MindWave mobile (EEG) device. In International educational technology conference (pp. 88-101).
  • Shiu, S. C., Chien, H. O., Lee, M. H., & Chang, C. L. (2011). The study of brain wave change in creative thinking process. International Journal of Arts & Sciences, 4(19), 9.
  • Singh, D. (2017). To investigate power of brain activity using EEG comparison between creative and non- creative design task (Doctoral dissertation, Concordia University).
  • Singala, K. V., & Trivedi, K. R. (2016). Analysis of EEG spectrum bands aiding to read human mental states. In 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT). IEEE. https://doi.org/10.1109/iceeot.2016.7754983
  • Sternberg, R. J., & Lubart, T. I. (1993). Investing in creativity. Psychological Inquiry, 4(3), 229–232. https://doi.org/10.1207/s15327965pli0403_16
  • Stevens, C. E., & Zabelina, D. L. (2019). Creativity comes in waves: An EEG-focused exploration of the creative brain. Current Opinion in Behavioral Sciences, 27, 154–162. https://doi.org/10.1016/j.cobeha.2019.02.003
  • Stroe, M. A. (2018). Harold Bloom and the brain-wave theory of creativity. Creativity, 1(2), 3-112.
  • Sulaiman, N., Ying, B. S., Mustafa, M., & Jadin, M. S. (2018). Offline labview-based EEG signals analysis for human stress monitoring. In 2018 9th IEEE control and system graduate research colloquium (ICSGRC). IEEE. https://doi.org/10.1109/icsgrc.2018.8657606
  • Stevens, C. E., & Zabelina, D. L. (2019). Creativity comes in waves: An EEG-focused exploration of the creative brain. Current Opinion in Behavioral Sciences, 27, 154–162. https://doi.org/10.1016/j.cobeha.2019.02.003
  • Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., ... & Kawashima, R. (2012). The association between resting functional connectivity and creativity. Cerebral Cortex, 22(12), 2921-2929.
  • Thibault, R. T., Lifshitz, M., & Raz, A. (2016). The self-regulating brain and neurofeedback: Experimental science and clinical promise. Cortex, 74, 247–261. https://doi.org/10.1016/j.cortex.2015.10.024
  • Ward, L. M. (2003). Synchronous neural oscillations and cognitive processes. Trends in Cognitive Sciences, 7(12), 553–559. https://doi.org/10.1016/j.tics.2003.10.012
  • Wise, A. (1997). The high-performance mind: Mastering brainwaves for insight, healing, and creativity. Putnam.
  • Yin, R. K. (2009). Case study research: Design and methods (2nd ed.). Sage Publications.
There are 69 citations in total.

Details

Primary Language English
Subjects Applied and Developmental Psychology (Other)
Journal Section Creativity
Authors

Cagla Bulut Ates

Hilal Aktamış

Furkan Aydin 0000-0002-1531-0138

Project Number 121K847
Early Pub Date October 5, 2025
Publication Date October 24, 2025
Submission Date August 18, 2025
Acceptance Date October 5, 2025
Published in Issue Year 2025 Volume: 12 Issue: 2

Cite

APA Bulut Ates, C., Aktamış, H., & Aydin, F. (2025). Investigating the brain wave activities of middle school students during the implementation of STEM-based digital creativity practices. Journal of Gifted Education and Creativity, 12(2), 203-219. https://doi.org/10.5281/zenodo.17271022

JGEDC is one of approximately ten academic journals in the world that publish in the field of gifted education, and its editorial board includes some of the most prominent scholars in this field.