A Rapid Cortical Learning Process Supporting Students’ Knowledge Construction During Real Classroom Teaching
Source abstract
Abstract
Abstract Classroom teaching is essential for cognitive development and cultural evolution, yet its neurocognitive mechanisms remain unclear. Here, this is explored in a university graduate course by combining wearable functional near‐infrared spectroscopy (fNIRS) and machine learning models. The results show that blended teaching involving both students’ recalling and teachers’ lecturing leads to better learning outcomes than lecturing alone. Moreover, during the same lecturing phase, blended teaching induces knowledge construction in the middle frontal cortex (MFC), while lecturing alone induces knowledge representation in the right temporoparietal junction (TPJ), with the former significantly correlating with the final learning outcomes. Additionally, the MFC's construction begins during earlier recalling but is significantly facilitated by later lecturing. Finally, when teacher's TPJ activity precedes that of students’ MFC, significant teacher–student neural synchronization is observed during lecturing of blended teaching and is correlated with learning outcomes. These findings suggest that, in the real classroom teaching, the MFC serves as a hub of a rapid cortical learning process, supporting knowledge construction through a projection from the teacher's TPJ.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Neural dynamics and brain function · Functional Brain Connectivity Studies · EEG and Brain-Computer Interfaces
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research Beijing Normal University Beijing 100875 China
Center for Teacher Education Research Beijing Normal University Beijing 100875 China
Research Institute of Science Education Beijing Normal University Beijing 100875 China
Funding
National Natural Science Foundation of China
References (100+)
Show source-provided references
1. Comenius J. M. · 1907
2. 10.3102/003465431774320010.3102/0034654317743200 ↗
3. 10.1007/s13164-017-0346-310.1007/s13164-017-0346-3 ↗
4. 10.1016/j.tate.2019.04.00210.1016/j.tate.2019.04.002 ↗
5. 10.1016/j.neuron.2010.08.02810.1016/j.neuron.2010.08.028 ↗
6. 10.1073/pnas.221501512010.1073/pnas.2215015120 ↗
7. 10.1126/sciadv.abo355510.1126/sciadv.abo3555 ↗
8. 10.1080/0046152740952912910.1080/00461527409529129 ↗
9. 10.1207/s15326985ep2704_810.1207/s15326985ep2704_8 ↗
10. 10.3102/0002831203100233810.3102/00028312031002338 ↗
11. Selvi K. · 2013 · 167
12. 10.1038/s41539-020-0064-y10.1038/s41539-020-0064-y ↗
13. 10.1207/s15326985ep4102_110.1207/s15326985ep4102_1 ↗
14. 10.1080/10494820.2013.79284510.1080/10494820.2013.792845 ↗
15. 10.1080/10508406.2011.59171710.1080/10508406.2011.591717 ↗
16. J.Bishop M.Verleger in2013 ASEE Annual Conference & Exposition ASEE Conferences ASEE Atlanta Georgia2013 pp.23.1200.1–23.1200.18.
17. 10.1093/cercor/bhad26010.1093/cercor/bhad260 ↗
18. 10.1038/s41467-022-31965-210.1038/s41467-022-31965-2 ↗
19. 10.1038/nn.445010.1038/nn.4450 ↗
20. 10.1016/j.neuron.2009.08.01110.1016/j.neuron.2009.08.011 ↗
21. 10.1073/pnas.101693910810.1073/pnas.1016939108 ↗
22. 10.1038/s41593-018-0220-310.1038/s41593-018-0220-3 ↗
23. 10.1038/nrn356310.1038/nrn3563 ↗
24. 10.1016/j.neuron.2023.02.01410.1016/j.neuron.2023.02.014 ↗
25. 10.1177/095935431350016610.1177/0959354313500166 ↗
26. 10.1016/0010-0285(77)90012-310.1016/0010-0285(77)90012-3 ↗
27. 10.1037/0033-2909.112.1.2410.1037/0033-2909.112.1.24 ↗
28. 10.1002/hipo.2020010.1002/hipo.20200 ↗
29. 10.1038/nrn160710.1038/nrn1607 ↗
30. 10.1016/j.tics.2019.09.00910.1016/j.tics.2019.09.009 ↗
31. 10.1126/science.aau252810.1126/science.aau2528 ↗
32. 10.1126/science.aam680810.1126/science.aam6808 ↗
33. 10.1155/2015/80438510.1155/2015/804385 ↗
34. 10.1016/j.neuropsychologia.2016.05.00310.1016/j.neuropsychologia.2016.05.003 ↗
35. 10.1523/JNEUROSCI.3603-16.201710.1523/JNEUROSCI.3603-16.2017 ↗
36. 10.1073/pnas.240364812110.1073/pnas.2403648121 ↗
37. 10.1016/S0010-9452(08)70651-810.1016/S0010-9452(08)70651-8 ↗
38. 10.1523/JNEUROSCI.2926-12.201210.1523/JNEUROSCI.2926-12.2012 ↗
39. 10.1016/j.ijer.2013.02.00210.1016/j.ijer.2013.02.002 ↗
40. 10.1016/j.neuroimage.2020.11665710.1016/j.neuroimage.2020.116657 ↗
41. 10.1016/j.neuroimage.2018.08.00510.1016/j.neuroimage.2018.08.005 ↗
42. 10.1002/hbm.2405910.1002/hbm.24059 ↗
43. 10.1177/0956797623116387210.1177/09567976231163872 ↗
44. 10.1016/j.cub.2017.04.00210.1016/j.cub.2017.04.002 ↗
45. 10.1093/cercor/bhac48410.1093/cercor/bhac484 ↗
46. 10.1111/nyas.1394810.1111/nyas.13948 ↗
47. 10.1073/pnas.240272312110.1073/pnas.2402723121 ↗
48. 10.1016/0001-6918(69)90055-910.1016/0001-6918(69)90055-9 ↗
49. 10.20849/jed.v5i2.89810.20849/jed.v5i2.898 ↗
50. 10.3389/neuro.01.016.200810.3389/neuro.01.016.2008 ↗
51. 10.1162/jmlr.2003.3.4-5.99310.1162/jmlr.2003.3.4-5.993 ↗
52. 10.1073/pnas.190340211610.1073/pnas.1903402116 ↗
53. 10.7554/eLife.7743010.7554/eLife.77430 ↗
54. 10.1016/j.neuroimage.2021.11808510.1016/j.neuroimage.2021.118085 ↗
55. 10.1016/j.neuron.2017.06.04110.1016/j.neuron.2017.06.041 ↗
56. 10.1523/JNEUROSCI.0251-18.201810.1523/JNEUROSCI.0251-18.2018 ↗
57. 10.1016/j.tics.2018.03.01310.1016/j.tics.2018.03.013 ↗
58. 10.7554/eLife.7369310.7554/eLife.73693 ↗
59. 10.1038/s41593-022-01020-w10.1038/s41593-022-01020-w ↗
60. 10.1038/s41593-023-01331-610.1038/s41593-023-01331-6 ↗
61. 10.7238/rusc.v12i1.247510.7238/rusc.v12i1.2475 ↗
62. 10.1016/j.compedu.2018.07.02110.1016/j.compedu.2018.07.021 ↗
63. Lefa B. · Educational Psychology. · 2014 · 1 · 1
64. Vygotsky L. S. · 1981
65. 10.1038/nrn.2017.1510.1038/nrn.2017.15 ↗
66. 10.1016/j.neuron.2014.09.02210.1016/j.neuron.2014.09.022 ↗
67. 10.1038/2017810.1038/20178 ↗
68. 10.1146/annurev.neuro.24.1.16710.1146/annurev.neuro.24.1.167 ↗
69. 10.1523/JNEUROSCI.1166-19.201910.1523/JNEUROSCI.1166-19.2019 ↗
70. 10.1073/pnas.230905412110.1073/pnas.2309054121 ↗
71. 10.3389/fnhum.2013.0046510.3389/fnhum.2013.00465 ↗
72. 10.1126/science.113593510.1126/science.1135935 ↗
73. 10.1126/science.120527410.1126/science.1205274 ↗
74. 10.3390/brainsci1303049110.3390/brainsci13030491 ↗
75. 10.1093/scan/nsaa15110.1093/scan/nsaa151 ↗
76. 10.1016/j.bandc.2019.10551310.1016/j.bandc.2019.105513 ↗
77. 10.1016/j.bandc.2021.10580310.1016/j.bandc.2021.105803 ↗
78. 10.3758/BF0319314610.3758/BF03193146 ↗
79. 10.1016/j.cub.2021.08.04510.1016/j.cub.2021.08.045 ↗
80. 10.1038/s41467-021-22202-310.1038/s41467-021-22202-3 ↗
81. 10.1016/0028-3932(71)90067-410.1016/0028-3932(71)90067-4 ↗
82. 10.1016/j.cortex.2019.11.02010.1016/j.cortex.2019.11.020 ↗
83. 10.1111/cdev.1351010.1111/cdev.13510 ↗
84. 10.1016/j.neuroimage.2009.02.00610.1016/j.neuroimage.2009.02.006 ↗
85. 10.1016/j.neuroimage.2005.02.01810.1016/j.neuroimage.2005.02.018 ↗
86. 10.1006/nimg.2001.097810.1006/nimg.2001.0978 ↗
87. 10.1016/j.neuroimage.2008.08.03610.1016/j.neuroimage.2008.08.036 ↗
88. 10.1117/1.280491110.1117/1.2804911 ↗
89. 10.1162/edfp_a_0038310.1162/edfp_a_00383 ↗
90. Entwisle D R. · First Grade and Educational Attainment by Age 22. · 2005 · 110 · 1458
91. 10.1093/cercor/bhac12210.1093/cercor/bhac122 ↗
92. 10.1016/j.brs.2022.12.00910.1016/j.brs.2022.12.009 ↗
93. 10.1364/AO.48.00D28010.1364/AO.48.00D280 ↗
94. 10.1088/0967-3334/33/2/25910.1088/0967-3334/33/2/259 ↗
95. 10.1117/1.185255210.1117/1.1852552 ↗
96. Klein F. · Neurophotonics. · 2023 · 10
97. 10.1109/TBME.2009.203866710.1109/TBME.2009.2038667 ↗
98. 10.7554/eLife.8703710.7554/eLife.87037 ↗
99. 10.1038/s42003-022-03418-510.1038/s42003-022-03418-5 ↗
100. 10.1038/s41467-020-19630-y10.1038/s41467-020-19630-y ↗