Browse > Article
http://dx.doi.org/10.21796/jse.2022.46.3.255

Analysis of Brain Activation on the Self-Regulation Process in College Life Science Learning between Biology Major and Non-Major Students  

Su-Min Lee (Korea National University of Education)
Sang-Hee Park (Daejeon Gwanpyeong Elementary School)
Seung-Hyuk Kwon (Gongju National University of Education)
Yong-Ju Kwon (Korea National University of Education)
Publication Information
Journal of Science Education / v.46, no.3, 2022 , pp. 255-265 More about this Journal
Abstract
The purpose of this study is to analyze and compare brain activation that appears in the self-regulation process of biology major and non-major college students in life science learning. The self-regulation task implemented a life science learning situation with the concept of biological classification. The brain activation of college students was measured and analyzed by fNIRS. In the assimilation process, bilateral FP and left DLPFC show significant activation, and the two groups show a difference in the left OFC activation related to motivation and reward. In the conflict process, the left DLPFC shows significantly lower activation in common, and the two groups show a difference in activation between BA 46, which is related to recent memory, and BA 47, which is related to long-term memory. In the accommodation process, a significantly high activation was found in right DLPFC in common, and the two groups show a difference in activation between right DLPFC and right FP. These areas are in the right frontal lobe area and are related to the understanding of life science knowledge. As a result of this study, it can be seen that the brain activation patterns of biology major and non-major college students are different in the self-regulation process. In addition, we will propose additional neurological studies on self-regulation and present systems and learning strategies that can be constructed in school settings.
Keywords
life science learning; self-regulation; assimilation; conflict; accommodation; brain activation; biology major;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Byeon, J., & Kwon, Y. J. (2020). Development of the Learning Model for Biological Classification based on the Brain Connectivity using fMRI Analysis. Biology Education, 48(2), 188-202.
2 Cohen, M. (2012). The importance of self-regulation for college student learning. College Student Journal, 46(4), 892-902.
3 Dekker, S., Krabbendam, L., Lee, N., Boschloo, A., De Groot, R., & Jolles, J. (2016). Dominant goal orientations predict differences in academic achievement during adolescence through metacognitive self-regulation. Journal of Educational and Developmental Psychology, 6(1), 47-58.
4 Dom, G., Sabbe, B., Hulstijn, W., & Van Den Brink, W. (2005). Substance use disorders and the orbitofrontal cortex: systematic review of behavioural decision-making and neuroimaging studies. The British Journal of Psychiatry, 187(3), 209-220.   DOI
5 Durantin, G., Gagnon, J.-F., Tremblay, S., & Dehais, F. (2014). Using near infrared spectroscopy and heart rate variability to detect mental overload. Behavioural Brain Research, 259, 16-23.
6 Eilam, B., & Aharon, I. (2003). Students' planning in the process of self-regulated learning. Contemporary Educational Psychology, 28(3), 304-334.
7 Eilam, B., & Reiter, S. (2014). Long-term self- regulation of biology learning using standard junior high school science curriculum. Science Education, 98(4), 705-737.   DOI
8 Elhusseini, S. A., Tischner, C. M., Aspiranti, K. B., & Fedewa, A. L. (2022). A quantitative review of the effects of self-regulation interventions on primary and secondary student academic achievement. Metacognition and Learning, 17, 1117-1139.   DOI
9 Fairclough, S., Ewing, K., Burns, C., & Kreplin, U. (2019). Neural efficiency and mental workload: locating the red line. In Neuroergonomics (pp. 73-77): Elsevier.
10 Goldberg, T. E., Berman, K. F., Fleming, K., Ostrem, J., Van Horn, J. D., Esposito, G., ... Weinberger, D. R. (1998). Uncoupling cognitive workload and prefrontal cortical physiology: a PET rCBF study. Neuroimage, 7(4), 296-303.   DOI
11 Gupta, R., & Tranel, D. (2012). Memory, neural substrates. In Encyclopedia of Human Behavior (pp. 593-600), London, UK: Academic Press.
12 Karaca, M., & Bektas, O. (2021). The relationship between perceived role models and self-regulation in science. International Journal of Educational Research, 110, 101884.
13 Keating, D. P. (2004). Cognitive and brain development. In Handbook of Adolescent Psychology, 2nd ed. (pp. 45-84). Hoboken, NJ.: John Wiley & Sons Inc.
14 Knight, J. K., & Smith, M. K. (2010). Different but equal? How nonmajors and majors approach and learn genetics. CBE-Life Sciences Education, 9(1), 34-44.   DOI
15 Koechlin, E. (2011). Frontal pole function: what is specifically human? Trends in Cognitive Sciences, 15(6), 241.
16 Koechlin, E., & Hyafil, A. (2007). Anterior prefrontal function and the limits of human decision-making. Science, 318(5850), 594-598.   DOI
17 Kwon, S. H., Park, S. H., Park, J. S., Hwang, N. R., & Kwon, Y. J. (2020). Identification of fNIRS Brain Activity and Exploration of Deep Learning-Based Predictive Model in Self-Regulation Process Taking Mirror Task. Brain, Digital, & Learning, 10(4), 365-376.   DOI
18 Kwon, Y. J., Lee, J. K., Shin, D. H., & Jeong, J. S. (2009). Changes in brain activation induced by the training of hypothesis generation skills: An fMRI study. Brain and Cognition, 69(2), 391-397.   DOI
19 Lawson, A. E. (1995). Science Teaching and the Development of Thinking. Belmont, CA.: Wadsworth Publishing.
20 Lawson, A. E., & Wollman, W. T. (1977). Using chemistry problems to provoke self-regulation. Journal of Chemical Education, 54(1), 41.
21 Lee, S. R., & Kwon, Y. J. (2022). Age-Specific Brain Activation in Secondary School Students' Self-Regulating Activities on Biological Tasks -fNIRS Study. Journal of Science Education, 46(1), 30-39.
22 Mansouri, F. A., Koechlin, E., Rosa, M. G., & Buckley, M. J. (2017). Managing competing goals-a key role for the frontopolar cortex. Nature Reviews Neuroscience, 18(11), 645-657.   DOI
23 McClelland, M. M., Ponitz, C. C., Messersmith, E. E., & Tominey, S. (2010). Self-regulation: Integration of Cognition and Emotion.
24 Murphy, D., Daly, E., Van Amelsvoort, T., Robertson, D., Simmons, A., & Critchley, H. (1998). Functional neuroanatomical dissociation of verbal, visual and spatial working memory. Schizophrenia Research, 1(29), 105-106.
25 Organisation for Economic Co-operation and Development (OECD). (2018). The future of education and skills: Education 2030. OECD Education Working Papers.
26 Oldfield, R. C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 9(1), 97-113.   DOI
27 Paniukov, D., & Davis, T. (2018). The evaluative role of rostrolateral prefrontal cortex in rule-based category learning. Neuroimage, 166, 19-31.   DOI
28 Park, J. S., & Kwon, Y. J. (2021). Comparison of science gifted and general students' brain activity and thinking process in the process of self-regulation-An fNIRS study. Brain, Digital, & Learning, 11(2), 405-416.
29 Park, S. H., Lee, S. M., Kwon, S. H., & Kwon, Y. J. (2022). A Study on the Brain Network Development Model in Self-Regulation Process of Adolescents' Life Science Learning. Brain, Digital, & Learning, 12(1), 119-129.
30 Pas, P., Hulshoff Pol, H. E., Raemaekers, M., & Vink, M. (2021). Self-regulation in the pre-adolescent brain. Developmental Cognitive Neuroscience, 51, 101012. 
31 Piaget, J. (1968). Six Psychological Studies. New York: Vintage Books.
32 Sahranavard, S., Miri, M. R., & Salehiniya, H. (2018). The relationship between selfregulation and educational performance in students. Journal of Education and Health Promotion, 7, 154-159.
33 Sebesta, A. J., & Bray Speth, E. (2017). How should I study for the exam? Self-regulated learning strategies and achievement in introductory biology. CBE-Life Sciences Education, 16(2), ar30.
34 Stalnaker, T. A., Cooch, N. K., & Schoenbaum, G. (2015). What the orbitofrontal cortex does not do. Nature Neuroscience, 18(5), 620-627.   DOI
35 Stanton, J. D., Neider, X. N., Gallegos, I. J., & Clark, N. C. (2015). Differences in metacognitive regulation in introductory biology students: when prompts are not enough. CBE-Life Sciences Education, 14(2), ar15.
36 Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28(1), 78-106.   DOI
37 Steinberg, L., Icenogle, G., Shulman, E. P., Breiner, K., Chein, J., Bacchini, D., ... Dodge, K. A. (2018). Around the world, adolescence is a time of heightened sensation seeking and immature self-regulation. Developmental Science, 21(2), e12532.
38 Thibodeaux, J., Deutsch, A., Kitsantas, A., & Winsler, A. (2017). First-year college students' time use: Relations with self-regulation and GPA. Journal of Advanced Academics, 28(1), 5-27.   DOI
39 Toepper, M., Gebhardt, H., Beblo, T., Thomas, C., Driessen, M., Bischoff, M., ... Sammer, G. (2010). Functional correlates of distractor suppression during spatial working memory encoding. Neuroscience, 165(4), 1244-1253.   DOI
40 Vink, M., Gladwin, T. E., Geeraerts, S., Pas, P., Bos, D., Hofstee, M., & Vollebergh, W. (2020). Towards an integrated account of the development of self-regulation from a neurocognitive perspective: A framework for current and future longitudinal multi-modal investigations. Developmental Cognitive Neuroscience, 45, 100829.
41 Wallis, J. D. (2007). Orbitofrontal cortex and its contribution to decision-making. Annual Review of Neuroscience, 30(1), 31-56.
42 Woltering, S., & Shi, Q. (2016). On the neuroscience of self-regulation in children with disruptive behavior problems: Implications for education. Review of Educational Research, 86(4), 1085-1110.
43 Xia, M., Wang, J., & He, Y. (2013). BrainNet Viewer: a network visualization tool for human brain connectomics. PloS One, 8(7), e68910.
44 Ye, J. C., Tak, S., Jang, K. E., Jung, J., & Jang, J. (2009). NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy. Neuroimage, 44(2), 428-447.   DOI
45 Baumert, A., Buchholz, N., Zinkernagel, A., Clarke, P., MacLeod, C., Osinsky, R., & Schmitt, M. (2020). Causal underpinnings of working memory and stroop interference control: testing the effects of anodal and cathodal tDCS over the left DLPFC. Cognitive, Affective, & Behavioral Neuroscience, 20(1), 34-48.   DOI
46 Badre, D., & Wagner, A. D. (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia, 45(13), 2883-2901.   DOI
47 Ballesta, S., Shi, W., Conen, K. E., & Padoa-Schioppa, C. (2020). Values encoded in orbitofrontal cortex are causally related to economic choices. Nature, 588(7838), 450-453.   DOI
48 Barbey, A. K., Koenigs, M., & Grafman, J. (2013). Dorsolateral prefrontal contributions to human working memory. Cortex, 49(5), 1195-1205.   DOI
49 Berger, A., Kofman, O., Livneh, U., & Henik, A. (2007). Multidisciplinary perspectives on attention and the development of self-regulation. Progress in Neurobiology, 82(5), 256-286.   DOI
50 Blume, F., Irmer, A., Dirk, J., & Schmiedek, F. (2022). Day to-day variation in students' academic success: The role of self-regulation, working memory, and achievement goals. Developmental Science, https://doi.org/10.1111/desc.13301.   DOI
51 Borghini, G., Astolfi, L., Vecchiato, G., Mattia, D., & Babiloni, F. (2014). Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neuroscience & Biobehavioral Reviews, 44, 58-75.   DOI