Abstract
Researchers have begun applying developments in neuroscience to reveal the underlying physiological mechanisms involved in learning processes, beginning with early childhood education and extending to the quest for lifelong learning. This chapter examines the research findings of neuroscience, from three distinct perspectives: psychological, educational, and technological. Our examination of memory processes (short term and long term) led to a discussion of perception, attention, and the role of the senses in the processes of recognition, the actions of composition and decomposition, and the activation of various parts of the brain. We looked at the establishment of new neural pathways, the development of brain-based curricula, and the interaction of these elements in learning outcomes. We also examined the differences inherent in learning new versus familiar concepts and disconnected data versus relevant information. Finally, we examined the processes and implications involved in the visualization of science-related concepts. With a focus experiments on the tracking of eye movements and the latest development in MRI detection with regard to the sequence learning system and differences in the activation of various parts of the brain, we found these research methods could apply to investigate a lot of kinds of studies including a comparison of the perception of actual events with those rendered in 2D low virtual reality and 3D high virtual reality.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ach, E., Gerhardt, C. A., Barrera, M., Kupst, M. J., Meyer, E. A., Patenaude, A. F., & Vannatta, K. (2013). Family factors associated with academic achievement deficits in pediatric brain tumor survivors. Psychooncology, 22(8), 1731–1737. doi:10.1002/pon.3202.
Bandettini, P. A. (2012). Twenty years of fMRI: The science and the stories. NeuroImage, 62, 575–588.
Baron-Cohen, S., Knickmeyer, R. C., & Belmonte, M. K. (2005). Sex differences in the brain: Implications for explaining autism. Science, 310(5749), 819–823.
Basmajian, J. V. (1982). Clinical use of biofeedback in rehabilitation. Psychosomatics, 23(1), 67–73.
Blair, M. R., Watson, M. R., Walshe, R. C., & Maj, F. (2009). Extremely selective attention: Eye-tracking studies on dynamic attentional allocation to stimulus features. Journal of Experimental Psychology. Learning, Memory, and Cognition, 35, 1196–1206.
Busatto, G. F., Pilowsky, L. S., Costa, D. C., Ell, P. J., David, A. S., Lucey, J. V., & Kerwin, R. W. (1997). Correlation between reduced in vivo benzodiazepine receptor binding and severity of psychotic symptoms in schizophrenia. The American Journal of Psychiatry, 154, 56–63.
Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences, 4(6), 215–222.
Chiang, W. W., & Liu, C. J. (2014). Scale of academic emotion in science education: Development and validation. International Journal of Science Education, 36(6), 908–928.
Croft, R. J., Chandler, J. S., Barry, R. J., Cooper, N. R., & Clarke, A. R. (2005). EOG correction: A comparison of four methods. Psychophysiology, 42(1), 16–24. doi:10.1111/j.1468-8986.2005.00264.x.
D’Esposito, M., Postle, B. R., Ballard, D., & Lease, J. (1999). Maintenance versus manipulation of information held in working memory: An event-related fMRI study. Brain and Cognition, 41, 66–86.
D’Esposito, M., Postle, B. R., Jonides, J., & Smith, E. E. (1999). The neural substrate and temporal dynamics of interference effects in working memory as revealed by event-related functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 96, 7514–7519.
Damasio, A. (2003). Looking for Spinoza: joy, sorrow and the feeling brain. New York, NY: Harcourt.
Davidson, R. J., & Begley, S. (2012). The emotional life of your brain: How its unique patterns affect the way you think, feel, and live – And how you can change them. New York, NY: Hudson Street Press.
Dawson, T. L. (2006). Stage-like patterns in the development of conceptions of energy. In X. Liu & W. Boone (Eds.), Applications of Rasch measurement in science education (pp. 111–136). Maple Grove, MN: JAM Press.
Dawson, T. L., Fischer, K. W., & Stein, Z. (2006). Reconsidering qualitative and quantitative research approaches: A cognitive developmental perspective. New Ideas in Psychology, 24(3), 229–239. doi:10.1016/j.newideapsych.2006.10.001.
Duncan, J., & Owen, A. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends in Neurosciences, 23, 475–483.
Eagleton, S., & Muller, A. (2011). Development of a model for whole brain learning of physiology. Advances in Physiology Education, 35(4), 421–426. doi:10.1152/advan.00007.2011.
Ellsworth, P. C., & Scherer, K. R. (2003). Appraisal processes in emotion. In R. J. Davidson, K. R. Scherer, & H. Goldsmith (Eds.), Handbook of affective sciences (pp. 572–595). New York, NY: Oxford University Press.
Estevez, M. E., Lindgren, K. A., & Bergethon, P. R. (2010). A novel three-dimensional tool for teaching human neuroanatomy. Anatomical Sciences Education, 3(6), 309–317. doi:10.1002/ase.186.
Eysenck, W. M., & Keane, T. M. (2000). Cognitive psychology: A student’s handbook (4th ed.). New York, NY: Psychology Press.
Fan, J., Flombaum, J. I., McCandliss, B. D., Thomas, K. M., & Posner, M. I. (2003). Cognitive and brain consequences of conflict. NeuroImage, 18(1), 42–57.
Fischer, K. W., Immordino-Yang, M. H., & Waber, D. P. (2007). Toward a grounded synthesis of mind, brain, and education for reading disorders: An introduction to the field and this book. In K. W. Fischer, J. H. Bernstein, & M. H. Immordino-Yang (Eds.), Mind, brain, and education in reading disorders (pp. 3–15). Cambridge, UK: Cambridge University Press.
Geake, J. (2011). Position statement on motivations, methodologies, and practical implications of educational neuroscience research: fMRI studies of the neural correlates of creative intelligence. Educational Philosophy and Theory, 43(1), 43–47. doi:10.1111/j.1469-5812.2010.00706.x.
Gilbert, M. (2013). Cognitive function: Mechanisms underlying learning and memory. Kaohsiung, Taiwan (R.O.C.): Graduate Institute of Science Education and Environmental Education. National Kaohsiung Normal University.
Ho, M. C., Chou, C. Y., Huang, C. F., Lin, Y. T., Shih, C. S., Han, S. Y., … Liu, C. J. (2012). Age-related changes of task-specific brain activity in normal aging. Neuroscience Letters, 507, 78–83.
Ho, M. C., Huang, C. F., Chou, C. Y., Lin, Y. T., Shih, C. S., Wu, M. T., … Liu, C. J. (2012). Task-related brain oscillations in normal aging. Health, 4, 762–768.
Huang, C. F., & Liu, C. J. (2012). An event-related potentials study of mental rotation in identifying chemical structural formulas. European Journal of Educational Research, 1(1), 37–54.
Immordino-Yang, M. H. (2011). Implications of affective and social neuroscience for educational theory. Educational Philosophy and Theory, 43(1), 98–103. doi:10.1111/j.1469-5812.2010.00713.x.
Kierkels, J. J., van Boxtel, G. J., & Vogten, L. L. (2006). A model-based objective evaluation of eye movement correction in EEG recordings. IEEE Transactions on Biomedical Engineering, 53(2), 246–253. doi:10.1109/TBME.2005.862533.
Kraut, M. A., Hart, J., Soher, B., & Gordon, B. (1997). Object shape processing in the visual system evaluated using functional MRI. Neurology, 48, 1416–1420.
Lee, J. H., Gurney, P. T., Dharmakumar, R., Wright, G. A., Hargreaves, B. A., Shankaranarayanan, A., … Pauly, J. M. (2006). Blood oxygenation (BOX) level dependent functional brain imaging using steady-state free precession. Paper presented at the 14th ISMRM, Seattle, Washington, DC.
Lehky, S. R., & Sereno, A. B. (2007). Comparison of shape encoding in primate dorsal and ventral visual pathways. Journal of Neurophysiology, 97(1), 307–319. doi:10.1152/jn.00168.2006.
Lin, Y. C., Liu, B. Y., & Liu, C. J. (2012). A study of applying cognitive load theory to science education websites. International Journal of Science and Engineering, 2(3), 53–58.
Liu, B. Y., & Liu, C. J. (2012). Using ERPs to investigate two-dimensional and three-dimensional image recognition. Journal of Research in Education Sciences, 57(2), 1–23.
Liu, C. J. (2005–2008). Evaluation and development of creativity sub-program 10: the study composed of elements of the scientific creativity researched by the brain signals. Kaohsiung, Taiwan (R.O.C.): National Science Council.
Liu, C. J., & Hou, I. L. (2009). Explore the influence of prior knowledge on understanding in scientific diagrams through eye tracking. Bulletin of Educational Psychology, 43(Special Issue on Reading), 227–250.
Liu, C. J., & Chiang, W. W. (2014). Theory, method and practice of neuroscientific findings in science education. International Journal of Science and Mathematics Education, 12(3), 629–646.
Liu, C. J., Huang, C. F., Chou, C. Y., Kuo, W. J., Lin, Y. T., Hung, C. M., … Ho, M. C. (2012). Age- and disease-related features of task-related brain oscillations by using mutual information. Brain and Behaviour, 2(6), 754–762.
Liu, C. J., Huang, C. F., Chou, C. Y., Yu, C. H., Lin, Y. T., Wu, M. T., & Ho, M. C. (2013). The influence of 40 Hz electromagnetic wave induce phase-synchronization on brain. Applied Mechanics and Materials, 311, 491–496.
Liu, C. J., Hou, I. L., Chiu, H. L., & Treagust, D. F. (2014). An exploration of secondary students’ mental states when learning about acids and bases. Research in Science Education, 44(1), 133–154.
Liu, C. J., Huang, C. F., Liu, M. C., Chien, Y. C., Lai, C. H., & Huang, Y. M. (2015). Does gender influence emotions resulting from positive applause feedback in self-assessment testing? Evidence from neuroscience. Educational Technology & Society, 18(1), 337–350.
Mathai, S., & Ramadas, J. (2009). Visuals and visualisation of human body systems. International Journal of Science Education, 31(3), 439–458. doi:10.1080/09500690802595821.
Milivojevic, B., Johnson, B. W., Hamm, J. P., & Corballis, M. C. (2003). Non-identical neural mechanisms for two types of mental transformation: Event-related potentials during mental rotation and mental paper folding. Neuropsychologia, 41, 1345–1356.
Nehdi, H. (2007). Creative and strategic thinking: The coming competencies. FOCUS, 8–10.
Noonan, K. J., Farnum, C. E., Leiferman, E. M., Lampl, M., Markel, M. D., & Wilsman, N. J. (2004). Growing pains: Are they due to increased growth during recumbency as documented in a lamb model? Journal of Pediatric Orthopaedics, 24(6), 726–731.
Nunez-Pena, M. I., & Aznar-Casanova, J. A. (2009). Mental rotation of mirrored letters: Evidence from event-related brain potentials. Brain and Cognition, 69(1), 180–187. doi:10.1016/j.bandc.2008.07.003.
Perani, D., Fazio, F., Borghese, N. A., Tettamanti, M., Ferrari, S., Decety, J., & Gilardi, M. C. (2001). Different brain correlates for watching real and virtual hand actions. Neuroimage, 14(3), 749–758.
Poole, A., & Ball, L. J. (2005). Eye tracking in human-computer interaction and usability research: Current status and future prospects. In C. Ghaoui (Ed.), Encyclopedia of human computer interaction (pp. 211–219). Hershey, PA: Idea Group, Inc.
Ritchie, S. M., Tobin, K., Hudson, P., Roth, W. M., & Mergard, V. (2011). Reproducing successful rituals in bad times: Exploring interactions of a new science teacher. Science Education, 95(4), 745–765. doi:10.1002/Sce.20440.
Ruhland, R., & van Geert, P. (1998). Jumping into syntax: Transitions in the development of closed class words. British Journal of Developmental Psychology, 16, 65–95.
Selden, S., Sherrier, T., & Wooters, R. (2012). Experimental study comparing a traditional approach to performance appraisal training to a whole-brain training method at C.B. fleet laboratories. Human Resource Development Quarterly, 23(1), 9–34.
Shipulina, O., & Campbell, S. (2009). Electrooculography: connecting mind, brain, and behavior in mathematics education research. Paper presented at the brain, neuroscience, and education SIG, San Diego, CA.
Stevens, R. H., Galloway, T., Berka, C., Johnson, R., & Sprang, M. (2008). Assessing students’ mental representations of complex problem spaces with EEG technologies. Paper presented at the 52nd annual meeting of the Human Factors and Ergonomic Society, New York, NY.
Tobin, K., & Ritchie, S. M. (2012). Multi-method, multi-theoretical, multi-level research in the learning sciences. Asia-Pacific Education Researcher, 21(1), 117–129.
Trueswell, J., Medina, T. N., Hafri, A., & Gleitman, L. R. (2013). Propose but verify: Fast-mapping meets cross situational word learning. Cognitive Psychology, 66, 126–156.
Ungerleider, L. G., & Mishkin, M. (1982). Two cortical visual systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of visual behavior (pp. 549–586). Cambridge, MA: MIT Press.
Vidyasagar, T. R., & Pammer, K. (1999). Impaired visual search in dyslexia relates to the role of the magnocellular pathway in attention. Neuroreport, 10(6), 1283–1287.
Vidyasagar, T. R., & Pammer, K. (2010). Dyslexia: A deficit in visuo-spatial attention, not in phonological processing. Trends in Cognitive Sciences, 14(2), 57–63.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Liu, CJ., Chiang, WW., Huang, CF., Shen, MH. (2015). The Implications of Science Teaching and Practices on Educational Neuroscience. In: Khine, M. (eds) Science Education in East Asia. Springer, Cham. https://doi.org/10.1007/978-3-319-16390-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-16390-1_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16389-5
Online ISBN: 978-3-319-16390-1
eBook Packages: Humanities, Social Sciences and LawEducation (R0)