北京生物醫(yī)學(xué)工程

動(dòng)畫(huà)演示教學(xué)模式下大學(xué)生課堂短時(shí)注意力腦電信號(hào)研究

Study on short-term attention EEG of college students; classroom based on the animation demonstration teaching mode

作者：黃婧婕程麗瑩石佳佳杜若瑜

單位：南京郵電大學(xué)地理與生物信息學(xué)院（南京 210023）江蘇省智慧健康大數(shù)據(jù)分析與位置服務(wù)工程實(shí)驗(yàn)室（南京 210023）

關(guān)鍵詞：腦電信號(hào)；動(dòng)畫(huà)演示教學(xué)模式；短時(shí)注意力；時(shí)頻分析；特征值

分類(lèi)號(hào)：R318.04

出版年·卷·期（頁(yè)碼）：2021·40·2（139-144）

摘要：

目的通過(guò)不同教學(xué)模式視頻刺激實(shí)驗(yàn)分析人腦專(zhuān)注度特征，探討動(dòng)畫(huà)演示教學(xué)模式對(duì)于大學(xué)生課堂短時(shí)注意力的影響。方法從30位被試者中篩選出20份觀看動(dòng)畫(huà)演示法、傳統(tǒng)講授法教學(xué)視頻的腦電信號(hào)，經(jīng)過(guò)預(yù)處理后，采用事件相關(guān)頻譜擾動(dòng)（event-related spectral dynamics，ERSP）進(jìn)行時(shí)頻分析，同時(shí)結(jié)合主觀調(diào)查問(wèn)卷，分析動(dòng)畫(huà)演示教學(xué)模式對(duì)大學(xué)生課堂短時(shí)注意力的影響。結(jié)果時(shí)頻分析結(jié)果顯示，在動(dòng)畫(huà)演示教學(xué)模式下，時(shí)間窗30~150 s內(nèi)被試者腦電信號(hào)能量更高，在beta波段（20~35 Hz）時(shí)與傳統(tǒng)講授教學(xué)模式之間差異具有高度統(tǒng)計(jì)學(xué)意義，F(xiàn)3、AF4、FC6通道處尤為明顯。結(jié)論動(dòng)畫(huà)演示教學(xué)模式能夠提升大學(xué)生課堂短時(shí)注意力，同時(shí)beta波段的部分特殊頻段存在可識(shí)別注意力集中程度的特征值，這能夠?yàn)楦咝Ｕn程改革采取動(dòng)畫(huà)演示教學(xué)方法與可穿戴腦機(jī)接口設(shè)備智能化課堂教學(xué)的應(yīng)用研究提供理論基礎(chǔ)。

Objective The paper aims at discussing the influence of animation demonstration [] teaching mode on short term attention of college students in class by using video stimulation experiments of different teaching modes to analyze the characteristics of human brain concentration. Methods We filtered 20 EEG signals during watching animation demonstration and traditional teaching videos were selected from 30 subjects. After pre-processing, event-related spectral dynamics (ERSP) were used for time-frequency analysis, and the influence of animation demonstration teaching mode on short-term attention of college students in class was analyzed in combination with subjective questionnaire. Results Time-frequency analysis results showed that, under the animation demonstration teaching mode, the eeg signal energy of the subjects was higher within 30-150 s in the time window, and the difference between the Beta band (20-35 Hz) and the traditional teaching mode was highly statistically significant, especially at the channel F3, AF4 and FC6. Conclusions The animation demonstration teaching mode can improve the short-term attention of college students in class. Meanwhile, some special frequency bands in the Beta band have the characteristic values that can identify the degree of attention concentration, which can provide a theoretical basis for the application research of animation demonstration teaching method and wearable BRAIN-machine interface device intelligent classroom teaching in the curriculum reform of colleges and universities.

參考文獻(xiàn)：

[1]?楊偉文,蔣月婷,肖洪廣,等.影響大學(xué)生上課注意力集中原因的調(diào)查和對(duì)策[J].中國(guó)高等醫(yī)學(xué)教育,2012(12):44-45.

[2]?李陽(yáng),許倩倩,吳麗霞.智能手機(jī)對(duì)高校課堂的影響與相關(guān)防范措施[J].教育教學(xué)論壇,2019(24):?6-8.

Li Y,Xu QQ,Wu LX. The effect of smart phones on college class and related?preventive measures [J]. Education Teaching Forum,?2019(24):?6-8.

[3]?林書(shū)兵,張倩葦.我國(guó)信息化教學(xué)模式的20年研究述評(píng):借鑒、變革與創(chuàng)新[J].中國(guó)電化教育,2015(9):103-110, 117.

Lin SB,?Zhang QW. 20 years review of research on information teaching mode in China：reference, change and innovation[J].?China Educational Technology,?2015(9):?103-110, 117.

[4]?史曉原.動(dòng)畫(huà)演示教學(xué)在物流管理專(zhuān)業(yè)實(shí)踐教學(xué)中的應(yīng)用——以物流技術(shù)與裝備課程為例[J].對(duì)外經(jīng)貿(mào),2018(1):139-140.

[5]?吳彬,黎劍云,羅藝徽.微視頻演示對(duì)就業(yè)指導(dǎo)課程教學(xué)效果的影響[J].護(hù)理研究,2016,30(16):2011-2014.

Wu B,?Li JY,?Luo YH. Influence of micro-video demonstration on teaching effect of career guidance course [J]. Nursing research,2016,30(16):?2011-2014.

[6]??Eagleton S, Muller A. Development of a model for whole brain learning of physiology[J].?Advances in Physiology??Education, 2011, 35(4):421-426.

[7]?白芷嫣,卞毓彩,朱穎穎，等.基于腦電信號(hào)的抑郁情緒傾向研究[J].北京生物醫(yī)學(xué)工程,2018,37(1):21-26.

Bai ZY,?Bian YC,?Zhu YY,?et al. Depressive emotion based on electroencephalography[J]. Beijing Biomedical Engineering, 2008,37(1):21-26.

[8]?賈雯. 大學(xué)生英語(yǔ)課堂注意力調(diào)查及相關(guān)因素分析[D]. 南京: 南京農(nóng)業(yè)大學(xué), 2007.

Jia W. A survey of college students' attention in efl classroom and the analysis of?the related?factors[D]. Nanjing: Nanjing Agricultural University, 2007.

[9]?Joshi?A, Kale?S, Chandel?S,et al. Likert scale: explored and explained[J]. British Journal of Applied Science and Technology,2015,7(4): 396-403.

[10]?賀陽(yáng).“翻轉(zhuǎn)課堂”教學(xué)模式在高職公共英語(yǔ)教學(xué)中的應(yīng)用[J].校園英語(yǔ),2018(48):86.

[11]?方良,楊浩.陣發(fā)性40Hz腦電信號(hào)的自動(dòng)檢測(cè)[J].華北電力大學(xué)學(xué)報(bào),2002,29(4):19-21.

Fang L,Yang H. Automatic detection of 40?Hz EEG bursts?[J]. Journal of North China Electric Power University,?2002, 29(4):19-21.

[12]?黃小娜,石硯.腦電EEG信號(hào)的分析方法[J].甘肅科技,2010,26(9):17-18.

[13]?李穎潔,樊飛燕,陳興時(shí).腦電分析在認(rèn)知研究中的進(jìn)展[J].北京生物醫(yī)學(xué)工程,2006, 25(3):321-324.

Li YJ,?Fan FY,?Chen XS. Development of EEG analysis in the research of cognitive science[J]. Beijing Biomedical Engineering,?2006, 25(3):321-324.

[14]?Shimamura AP,?Squire LR.?The relationship betweenfact and sourcememory: findings　from amnesic patients andnormal subjects[J].Psychobiology,1991,19:1-10.

禹東川.基于腦電的課堂注意力監(jiān)測(cè):構(gòu)建“可視化”教學(xué)生態(tài)[J].中小學(xué)管理,2016(7):18-19.

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