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Record W4290802497 · doi:10.5430/jct.v11n5p289

Analyses of the Effects of Humanities Education on Brain Waves of the Frontal, Parietal, and Temporal Regions

2022· article· en· W4290802497 on OpenAlexvenueno aff
Tae-Young Kim, Yongha Kim, Kyung‐Yae Hyun, Hae-Gyung Yoon

Bibliographic record

VenueJournal of Curriculum and Teaching · 2022
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsnot available
FundersNational Research Foundation of KoreaMinistry of EducationNational Research Foundation
KeywordsElectroencephalographyPsychologyHumanitiesCerebrumAudiologyArtMedicineNeuroscience

Abstract

fetched live from OpenAlex

This study was conducted targeting college students majoring in science and engineering, who were divided into an experimental group who took a humanities course and a control group who did not. After the experimental group took a humanities course, the brain wave activity of the frontal, parietal, temporal, and central regions of the two groups was measured using electroencephalography systems, and the electroencephalogram (EEG) waveforms of the anterior cerebrum were comparatively analyzed. A total of 67 subjects participated in the experiment, with 36 in the experimental group and 31 in the control group. According to the International 10-20 system, an international standard for EEG measurement, 7 electrodes (Cz, F3, F4, P3, P4, T3, T4) were attached to the cerebral scalp, and 2 reference electrodes were attached to both earlobes. These were attached after adjusting the resistance to the minimum value. The experimental group took a humanities course called "Understanding Beauty" for two hours twice a week over a period of 15 weeks. This course aimed to develop students’ imaginations to overcome a fact-centered world. After each lecture, the experimental group was asked to sit in a comfortable position with their eyes closed in a dark and quiet environment, and EEG measurements were started when their brain waveforms became stable. EEG measurements were also taken for the control group who did not take the course, at the same time and in the same manner. The measurements were conducted for about 10 minutes. The pattern in EEG changes between the two groups over time was analyzed by dividing them into alpha waves (8-13 Hz), theta waves (4-8 Hz), and beta waves (13-3 Hz). Based on the analysis results, for relative alpha waves, the difference between the mean vectors of all 7 variables was significant depending on the treatment (lecture attendance) (F(7, 59)=11.790, p<0.001). The variation over time between the experimental and control groups was significant (F(21,45)=3.575, p<0.001), indicating that there was an interaction effect between repeated measures and the groups. For relative beta waves, the difference between the mean vectors of all 7 variables was significant depending on the treatment (F(7, 59)=12.628, p<0.001). The variation over time between the two groups was significant (F(21,45)=3.388, p<0.001), suggesting that there was an interaction effect between repeated measures and the groups. For relative theta waves, the difference between the mean vectors of all 7 variables was significant depending on the treatment (F(7, 59)=5.301, p<0.001). The variation over time between the two groups was significant (F(21,45)=3.388, p<0.001), which means that there was an interaction effect between repeated measures and the groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.305
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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