Article(id=1149743085883670794, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149743083069288795, articleNumber=1003-3033(2024)06-0225-10, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.06.0258, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1703606400000, receivedDateStr=2023-12-27, revisedDate=1711036800000, revisedDateStr=2024-03-22, acceptedDate=null, acceptedDateStr=null, onlineDate=1752049712868, onlineDateStr=2025-07-09, pubDate=1719504000000, pubDateStr=2024-06-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752049712868, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752049712868, creator=13701087609, updateTime=1752049712868, updator=13701087609, issue=Issue{id=1149743083069288795, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='6', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752049712197, creator=13701087609, updateTime=1756468919644, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1168278582599098697, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149743083069288795, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1168278582599098698, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149743083069288795, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=225, endPage=234, ext={EN=ArticleExt(id=1149743086500233484, articleId=1149743085883670794, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Empirical study on virtual teaching of fire emergency escape in subway station, columnId=1149733268699918866, journalTitle=China Safety Science Journal, columnName=Emergency technology and management, runingTitle=null, highlight=null, articleAbstract=

In order to explore the influence of different learning scenarios on the learning effect of learners in the teaching process of fire emergency fire escape in subway stations,and explore the advantages of virtual reality learning. Questionnaires and MP160 physiological instrument were used to obtain different behavioral response data of learners in paper learning,mobile video learning and virtual reality learning scenarios,and these data were processed and analyzed. The results show that there are significant differences in learners' academic performance under the three learning scenarios. Compared with mobile video learning and paper learning scenarios,virtual reality learning scenarios can promote learners' understanding of subway fire escape knowledge and significantly improve academic performance. Under the three learning scenarios,there are significant differences in learners ' interest in learning. Virtual reality learning scenarios show significant advantages in improving learners ' interest in learning subway fire escape knowledge. The virtual reality learning scene reflects a higher level of physiological arousal in terms of physiologic index.

, correspAuthors=Qinling DAI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Siwen YANG, Qinling DAI, Baili XU, Mengmeng QI), CN=ArticleExt(id=1149743095559930201, articleId=1149743085883670794, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=地铁站消防应急火灾逃生虚拟教学实证研究, columnId=1149733268855108116, journalTitle=中国安全科学学报, columnName=应急技术与管理, runingTitle=null, highlight=null, articleAbstract=

为探究地铁站消防应急火灾逃生教学过程中,不同学习场景对学习者学习效果的影响,发掘虚拟现实学习优势,采用调查问卷和MP160生理仪,获取纸质学习、移动端视频学习和虚拟现实学习场景下,学习者不同的行为反应数据,并处理和分析这些数据。研究结果表明:3种学习场景下,学习者的学习成绩存在显著差异,相较于移动端视频学习和纸质学习场景,虚拟现实学习场景能够促进学习者对地铁火灾逃生知识的理解,显著提高学习成绩;3种学习场景下,学习者的学习兴趣存在显著差异,虚拟现实学习场景在提升学习者对地铁火灾逃生知识的学习兴趣方面表现出显著优势;虚拟现实学习场景在生理指标方面体现出更高水平的生理唤醒。

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**代沁伶(1982—)女,重庆人,博士,副教授,主要从事图像传播工程、视觉传达设计及新媒体设计理论方面的研究。E-mail:
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杨斯雯 (2000—),女,云南昆明人,硕士研究生,研究方向为视觉传达及媒体设计与理论。E-mail:

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杨斯雯 (2000—),女,云南昆明人,硕士研究生,研究方向为视觉传达及媒体设计与理论。E-mail:

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Journal of Applied Psychology, 2010, 95(4):618-630., articleTitle=The effect of negative feedback on tension and subsequent performance: the main and interactive effects of goal content and conscientiousness, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1168181548349137428, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, xref=null, ext=[AuthorCompanyExt(id=1168181548357526037, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, companyId=1168181548349137428, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Art and Design,Southwest Forestry University,Kunming Yunnan 650224,China), AuthorCompanyExt(id=1168181548361720342, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, companyId=1168181548349137428, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=西南林业大学 艺术与设计学院,云南 昆明 650224)])], figs=[ArticleFig(id=1168181550425317943, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Fig.1, caption=Subway station scenes in field studies, figureFileSmall=LZO5OBtMNsIG9LgrxZkHXw==, figureFileBig=Pp/FrsfLBveTibiEH8Vg6g==, tableContent=null), ArticleFig(id=1168181550563729976, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=图1, caption=实地调研获得的部分地铁站现实场景, figureFileSmall=LZO5OBtMNsIG9LgrxZkHXw==, figureFileBig=Pp/FrsfLBveTibiEH8Vg6g==, tableContent=null), ArticleFig(id=1168181550656004665, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Fig.2, caption=Some virtual scene of subway stations, figureFileSmall=3v61kSRq/pSx9L63tqZ6kQ==, figureFileBig=bRjdjSE6tNvKdO2k3Oqx0g==, tableContent=null), ArticleFig(id=1168181550756667962, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=图2, caption=地铁站部分虚拟场景, figureFileSmall=3v61kSRq/pSx9L63tqZ6kQ==, figureFileBig=bRjdjSE6tNvKdO2k3Oqx0g==, tableContent=null), ArticleFig(id=1168181550836359739, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Fig.3, caption=Test protocol, figureFileSmall=v0FMemypav4tRV15aRNuPw==, figureFileBig=cRtTFrLRHtNg+oOzqVuJLA==, tableContent=null), ArticleFig(id=1168181550932828732, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=图3, caption=试验流程, figureFileSmall=v0FMemypav4tRV15aRNuPw==, figureFileBig=cRtTFrLRHtNg+oOzqVuJLA==, tableContent=null), ArticleFig(id=1168181550991548989, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Fig.4, caption=Mean and standard deviation of heart rate and electrodermal conductivity during baseline and awakening periods in different learning scenarios, figureFileSmall=2TB3KqBapyTpv04NV0D+dw==, figureFileBig=BDsT8InYqXO0MpjRopxoCQ==, tableContent=null), ArticleFig(id=1168181551075435070, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=图4, caption=不同学习场景下心率和皮电基线期和唤醒期的平均值和标准差, figureFileSmall=2TB3KqBapyTpv04NV0D+dw==, figureFileBig=BDsT8InYqXO0MpjRopxoCQ==, tableContent=null), ArticleFig(id=1168181551129961023, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 1, caption=

Dimensions and questions of the learning interest questionnaire

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维度 题项
挑战与技能平衡 我感觉所面临的学习挑战与我自身的技能水平相匹配
清晰的目标 教学任务的目标在整个学习过程中都非常明确
及时的反馈 我能够获得及时的反馈,帮助我理解学习内容
专注度 在这个学习活动过程中,我能够完全专注于教学任务
控制感 在学习过程中,我能很好地控制和操作学习内容和环境
行动与知觉的融合 我的思考和行动都能紧密地与学习内容结合在一起
时间扭曲 在这个学习活动过程中,我感到时间在迅速流逝
流畅性 我在学习中很少遇到干扰和障碍
沉浸感 我完全沉浸在这个学习活动中
积极的情绪 这个学习活动令我感到非常愉快
学习体验满意度 我对这次学习活动的总体体验感到满意
这个学习活动非常有助于提升我的实际逃生技能
这种学习方式能够有效提高学习效率和学习质量
我愿意再次参与这种学习活动
), ArticleFig(id=1168181551205458496, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表1, caption=

学习兴趣问卷量表的构成维度及题项

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维度 题项
挑战与技能平衡 我感觉所面临的学习挑战与我自身的技能水平相匹配
清晰的目标 教学任务的目标在整个学习过程中都非常明确
及时的反馈 我能够获得及时的反馈,帮助我理解学习内容
专注度 在这个学习活动过程中,我能够完全专注于教学任务
控制感 在学习过程中,我能很好地控制和操作学习内容和环境
行动与知觉的融合 我的思考和行动都能紧密地与学习内容结合在一起
时间扭曲 在这个学习活动过程中,我感到时间在迅速流逝
流畅性 我在学习中很少遇到干扰和障碍
沉浸感 我完全沉浸在这个学习活动中
积极的情绪 这个学习活动令我感到非常愉快
学习体验满意度 我对这次学习活动的总体体验感到满意
这个学习活动非常有助于提升我的实际逃生技能
这种学习方式能够有效提高学习效率和学习质量
我愿意再次参与这种学习活动
), ArticleFig(id=1168181551255790145, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 2, caption=

Descriptive statistics of learning performance in different learning scenarios

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组别 个案数 平均值 标准差 标准误差 平均值的 95% 置信区间 最小值 最大值
下限 上限
虚拟现实学习组 30 12.67 1.398 0.255 12.14 13.19 10 15
移动端视频学习组 30 11.70 1.601 0.292 11.10 12.30 9 15
纸质学习组 30 11.43 1.406 0.257 10.91 11.96 9 15
总计 90 11.93 1.549 0.163 11.61 12.26 9 15
), ArticleFig(id=1168181551318704706, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表2, caption=

不同学习场景下学习成绩描述性统计

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组别 个案数 平均值 标准差 标准误差 平均值的 95% 置信区间 最小值 最大值
下限 上限
虚拟现实学习组 30 12.67 1.398 0.255 12.14 13.19 10 15
移动端视频学习组 30 11.70 1.601 0.292 11.10 12.30 9 15
纸质学习组 30 11.43 1.406 0.257 10.91 11.96 9 15
总计 90 11.93 1.549 0.163 11.61 12.26 9 15
), ArticleFig(id=1168181551423562307, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 3, caption=

One-way ANOVA analysis of learning performance in different learning scenarios

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方差来源 自由度 平方和 均方 F P
组间 2 25.267 12.633 5.836 0.004**
组内 87 188.333 2.165
总和 89 213.600
), ArticleFig(id=1168181551545197124, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表3, caption=

不同学习场景下学习成绩单因素方差分析结果

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方差来源 自由度 平方和 均方 F P
组间 2 25.267 12.633 5.836 0.004**
组内 87 188.333 2.165
总和 89 213.600
), ArticleFig(id=1168181551691997765, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 4, caption=

Multiple comparison of single factors variance in learning performance under different learning scenarios

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组别 平均值差值 标准误差 P 95% 置信区间
下限 上限
虚拟现实学习组 移动端视频学习组 0.967 0.380 0.013* 0.21 1.72
纸质学习组 1.233 0.380 0.002** 0.48 1.99
移动端视频学习组 虚拟现实学习组 -0.967 0.380 0.013* -1.72 -0.21
纸质学习组 0.267 0.380 0.485 -0.49 1.02
纸质学习组 虚拟现实学习组 -1.233 0.380 0.002** -1.99 -0.48
移动端视频学习组 -0.267 0.380 0.485 -1.02 0.49
), ArticleFig(id=1168181551905907270, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表4, caption=

不同学习场景下学习成绩单因素方差多重比较

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组别 平均值差值 标准误差 P 95% 置信区间
下限 上限
虚拟现实学习组 移动端视频学习组 0.967 0.380 0.013* 0.21 1.72
纸质学习组 1.233 0.380 0.002** 0.48 1.99
移动端视频学习组 虚拟现实学习组 -0.967 0.380 0.013* -1.72 -0.21
纸质学习组 0.267 0.380 0.485 -0.49 1.02
纸质学习组 虚拟现实学习组 -1.233 0.380 0.002** -1.99 -0.48
移动端视频学习组 -0.267 0.380 0.485 -1.02 0.49
), ArticleFig(id=1168181552006570567, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 5, caption=

Descriptive statistics of learning interest in different learning scenarios

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组别 个案数 平均值 标准差 标准误差 平均值的 95% 置信区间 最小值 最大值
下限 上限
虚拟现实学习组 30 62.133 3.003 0.548 61.012 63.255 55 67
移动端视频学习组 30 55.367 4.327 0.790 53.750 56.982 46 64
纸质学习组 30 53.933 3.443 0.629 52.648 55.219 46 61
总计 90 57.144 5.083 0.536 56.080 58.209 46 67
), ArticleFig(id=1168181552094650952, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表5, caption=

不同学习场景下学习兴趣描述性统计

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组别 个案数 平均值 标准差 标准误差 平均值的 95% 置信区间 最小值 最大值
下限 上限
虚拟现实学习组 30 62.133 3.003 0.548 61.012 63.255 55 67
移动端视频学习组 30 55.367 4.327 0.790 53.750 56.982 46 64
纸质学习组 30 53.933 3.443 0.629 52.648 55.219 46 61
总计 90 57.144 5.083 0.536 56.080 58.209 46 67
), ArticleFig(id=1168181552258228809, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 6, caption=

One-way ANOVA analysis of learning interest in different learning scenarios

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方差来源 自由度 平方和 均方 F P
组间 2 1 150.822 575.411 43.596 <0.001***
组内 87 1 148.300 13.199
总和 89 2 299.122
), ArticleFig(id=1168181552329531978, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表6, caption=

不同学习场景下学习兴趣单因素方差分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
方差来源 自由度 平方和 均方 F P
组间 2 1 150.822 575.411 43.596 <0.001***
组内 87 1 148.300 13.199
总和 89 2 299.122
), ArticleFig(id=1168181552413418059, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=EN, label=Table 7, caption=

Multiple comparisons of single factors variance in learning interest in different learning scenarios

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组别 平均值差值 标准误差 P 95% 置信区间
下限 上限
虚拟现实学习组 移动端视频学习组 6.767 0.938 <0.001*** 4.902 8.631
纸质学习组 8.200 0.938 <0.001*** 6.336 10.065
移动端视频学习组 虚拟现实学习组 -6.767 0.938 <0.001*** -8.631 -4.902
纸质学习组 1.433 0.938 0.130 -0.431 3.298
纸质学习组 虚拟现实学习组 -8.200 0.938 <0.001*** -10.065 -6.336
移动端视频学习组 -1.433 0.938 0.130 -3.298 0.431
), ArticleFig(id=1168181552522469964, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149743085883670794, language=CN, label=表7, caption=

不同学习场景下学习兴趣单因素方差多重比较

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组别 平均值差值 标准误差 P 95% 置信区间
下限 上限
虚拟现实学习组 移动端视频学习组 6.767 0.938 <0.001*** 4.902 8.631
纸质学习组 8.200 0.938 <0.001*** 6.336 10.065
移动端视频学习组 虚拟现实学习组 -6.767 0.938 <0.001*** -8.631 -4.902
纸质学习组 1.433 0.938 0.130 -0.431 3.298
纸质学习组 虚拟现实学习组 -8.200 0.938 <0.001*** -10.065 -6.336
移动端视频学习组 -1.433 0.938 0.130 -3.298 0.431
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地铁站消防应急火灾逃生虚拟教学实证研究
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杨斯雯 , 代沁伶 ** , 徐百利 , 祁梦梦
中国安全科学学报 | 应急技术与管理 2024,34(6): 225-234
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中国安全科学学报 | 应急技术与管理 2024, 34(6): 225-234
地铁站消防应急火灾逃生虚拟教学实证研究
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杨斯雯 , 代沁伶** , 徐百利, 祁梦梦
作者信息
  • 西南林业大学 艺术与设计学院,云南 昆明 650224
  • 杨斯雯 (2000—),女,云南昆明人,硕士研究生,研究方向为视觉传达及媒体设计与理论。E-mail:

通讯作者:

**代沁伶(1982—)女,重庆人,博士,副教授,主要从事图像传播工程、视觉传达设计及新媒体设计理论方面的研究。E-mail:
Empirical study on virtual teaching of fire emergency escape in subway station
Siwen YANG , Qinling DAI** , Baili XU, Mengmeng QI
Affiliations
  • School of Art and Design,Southwest Forestry University,Kunming Yunnan 650224,China
出版时间: 2024-06-28 doi: 10.16265/j.cnki.issn1003-3033.2024.06.0258
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为探究地铁站消防应急火灾逃生教学过程中,不同学习场景对学习者学习效果的影响,发掘虚拟现实学习优势,采用调查问卷和MP160生理仪,获取纸质学习、移动端视频学习和虚拟现实学习场景下,学习者不同的行为反应数据,并处理和分析这些数据。研究结果表明:3种学习场景下,学习者的学习成绩存在显著差异,相较于移动端视频学习和纸质学习场景,虚拟现实学习场景能够促进学习者对地铁火灾逃生知识的理解,显著提高学习成绩;3种学习场景下,学习者的学习兴趣存在显著差异,虚拟现实学习场景在提升学习者对地铁火灾逃生知识的学习兴趣方面表现出显著优势;虚拟现实学习场景在生理指标方面体现出更高水平的生理唤醒。

地铁站  /  消防应急  /  火灾逃生  /  虚拟现实  /  学习效果  /  生理指标

In order to explore the influence of different learning scenarios on the learning effect of learners in the teaching process of fire emergency fire escape in subway stations,and explore the advantages of virtual reality learning. Questionnaires and MP160 physiological instrument were used to obtain different behavioral response data of learners in paper learning,mobile video learning and virtual reality learning scenarios,and these data were processed and analyzed. The results show that there are significant differences in learners' academic performance under the three learning scenarios. Compared with mobile video learning and paper learning scenarios,virtual reality learning scenarios can promote learners' understanding of subway fire escape knowledge and significantly improve academic performance. Under the three learning scenarios,there are significant differences in learners ' interest in learning. Virtual reality learning scenarios show significant advantages in improving learners ' interest in learning subway fire escape knowledge. The virtual reality learning scene reflects a higher level of physiological arousal in terms of physiologic index.

subway station  /  fire emergency  /  fire escape  /  virtual reality  /  learning performance  /  physiologic index
杨斯雯, 代沁伶, 徐百利, 祁梦梦. 地铁站消防应急火灾逃生虚拟教学实证研究. 中国安全科学学报, 2024 , 34 (6) : 225 -234 . DOI: 10.16265/j.cnki.issn1003-3033.2024.06.0258
Siwen YANG, Qinling DAI, Baili XU, Mengmeng QI. Empirical study on virtual teaching of fire emergency escape in subway station[J]. China Safety Science Journal, 2024 , 34 (6) : 225 -234 . DOI: 10.16265/j.cnki.issn1003-3033.2024.06.0258
2023年7月,我国(不含港澳台地区)开通地铁的城市达54个,地铁运营总里程突破9 000 km,共有296条线路在运营[1],规模居世界前列。世界范围内,地铁灾害中发生频率最高、造成损失最大的是火灾[2]。地铁具有客流量密集、空间狭小且相对封闭的特点[3],乘客在火灾逃生时常因恐慌、缺乏逃生知识和技能以及不熟悉逃生路线等不能有效逃生。因此,有效地开展个体安全意识和逃生能力培训,成为亟需解决的问题。
对此,国内外学者开展了大量研究,TANAKA等[4]利用虚拟现实技术开发出用于电工培训的虚拟变电站,确保学员在安全的环境下进行教学培训。张磊等[5]针对高铁站人群,制作出虚拟仿真火灾教学训练系统。KINATEDER等[6]以危险品运输者为主要研究对象,通过问卷调查的方式,研究了当隧道内火灾风险增加时,逃生人员的疏散行为和心理反应。林晓飞等[7]对地铁逃生人员在火灾状态下的焦虑水平进行干预研究,并通过问卷调查分析了不同性别在心理焦虑水平上的变化。在提升乘客应急逃生能力的过程中,学习效果的评估能更好地分析教学方法的有效性[8]。美国教育评价标准联合委员会认为,学习效果包括认知理解能力、态度与价值观和实际技能及行为[9]。黄海涛[10]认为,学习效果是学习者经过一系列学习后,知识、技能、态度、情感及习得能力的增长。因此,学习效果并不仅仅包括学习成绩,还包括学习者在受教育过程中实现学习目标的各方面变化[11]。FINN等[12]认为,学习效果即认知学习效果,包括学习者对知识的理解、记忆和学习效率等智力层面的表现。WEST等[13]则认为,学习效果还应包含非认知学习效果,包括学习者的情感、学习兴趣和心理努力等非智力因素方面的表现。目前,学者们针对不同教学内容,也开展了学习效果的相关研究。杨健等[14]以记忆、理解、共情和学习成绩等作为主要测量指标,比较不同写作环境下学习效果的差异。王翠如等[15]以人体生物科学作为教学内容,将学习投入和学习成绩作为评价指标,研究不同环境下学习者的学习效果。现有研究利用生理指标测量方法探究学习者在逃生训练中的学习效果和情感体验内在机制的相对较少,且不同研究者所采用的学习效果评价指标并不一致。
鉴于此,笔者拟通过探究学习者在虚拟现实场景下消防应急火灾逃生学习过程中产生的内在情感体验,对比分析学习者在纸质、移动端视频和虚拟现实场景下学习效果的差异,以期为提升学习者火灾应急逃生能力的教学效果提供实践指导和理论支持。
将被试随机分为3组,分别在3种场景下学习同一内容的火灾逃生材料。采用单因素3水平的被试间设计,自变量为学习场景,分为线下纸质学习组、移动端视频学习组、虚拟现实学习组3个水平;因变量为学习效果。认知学习效果即学习成绩,学习成绩试题根据KRATHWOHL[16]修订的维度改编而成,分别从记忆、理解和应用3个维度考察被试对学习材料的掌握程度。从记忆维度考察学习者对火灾逃生基础知识和关键步骤记忆;从理解维度考察学习者对地铁火灾逃生过程的深入理解和推理能力;从应用维度作考察学习者将所学知识应用到实际情景中的能力。共设置15道测试试题,包括7道判断题和8道单选题。所有试题采用统一标准评分方法,答对题目赋予相应分值。
通过生理行为指标(心率、皮电)[17-18]和问卷来衡量非认知学习效果。心率是指单位时间内心脏跳动的次数;皮电是指人体皮肤电阻或电导变化的生理现象。根据PEARCR[19]和CHU[20]等开发的量表改编学习兴趣问卷,分为挑战与技能平衡、清晰的目标、及时的反馈、专注度、控制感、行动与知觉的融合、时间扭曲、流畅性、沉浸感、积极的情绪、学习体验满意度,共计14道题(Cronbach's α =0.745)。学习体验满意程度维度共4道题,其余维度各1题。量表采用Likert 5级计分(5代表非常同意,1代表非常不同意)。学习兴趣问卷量表的构成维度及题项见表1
从云南省某高校选取98名具有地铁乘坐经验的学生作为被试。所有选定的被试均未接受过特定的消防安全培训或应急疏散演练,并且无心脏、皮肤或精神方面的疾病。试验开始前,所有被试需签署知情同意书,并被明确告知所有收集到的数据仅用于学术研究。研究被试需要满足以下条件:①前测试分数满足试验评价;②视力或矫正视力达到正常标准。经过筛选,剔除先前知识过高、数据异常以及试验过程中受到意外干扰或中途退出的被试8名,最终得到有效被试90人。其中,男性46人,女性44人;平均年龄为23.2岁,年龄范围为17~27岁。3组被试性别比例均衡,所有数据不包含缺失值。第1组为控制组,学习纸质的材料;第2组为控制组,学习移动端的材料;第3组为实验组,学习虚拟场景的材料。
根据地铁站消防应急火灾逃生常用知识,结合昆明市地铁5号线白龙寺站的场景,改编试验材料,分别制作成3种学习材料。学习方式为自学,时长均控制在10 min以内。地铁站实景如图1所示,部分虚拟场景如图2所示。
心率及皮电信号数据采集和分析系统主要由MP160生理仪、 BioNomadix发射器和接收器,以及Acqknowledge软件构成,采样率为400 kHz。用于虚拟现实教学场景学习和交互操作的设备为HTC VIVE Pro,视场角为110 °,分辨率为2 880×1 600像素,刷新率为90 Hz。移动端视频学习设备采用Ipad Pro 2022,该设备屏幕大小为11 in,分辨率为2 388×1 668像素,屏幕刷新率为120 Hz。在Steam VR平台上运行的虚拟现实场境,由Unreal Engine 4 2022.4.27版本制作。
实测地点设定在实验室。试验开始前,试验员向被试介绍试验流程及注意事项,并指导被试填写基本信息问卷并签订数据采集同意书。后将90名被试随机分配到3个试验小组,分别进行虚拟现实、移动端视频和纸质学习。
正式学习前,虚拟现实学习组的被试先进行10 min设备熟悉训练,确保能熟练使用虚拟现实设备。随后,试验员调试并连接虚拟现实头戴显示器、操作手柄、电脑软件、接收器、生理传感器等设备,确保软硬件运行正常。最后,为被试佩戴生理传感器。其中,心率传感器固定在被试胸腔位置;皮电传感器分别固定在被试食指和中指指尖。实验室保持安静,室温控制在25℃左右。被试放松2 min后,试验员采集5 min的静息状态数据作为基线期数值。教学期间,被试先进行自由学习,生理仪记录其在学习过程中的心率和皮电等数据。学习结束后,引导被试完成后测问卷和后测试题。数据收集完毕后,由试验员整理、统计和分析。虚拟现实学习组使用头戴显示器和手柄进行相关交互。而移动端视频和纸质学习组则在固定位置仅使用平板和纸质学习材料学习,其余流程则与虚拟现实学习组完全相同。试验流程如图3所示。
对3组学习场景的学习成绩进行正态性检验,不同场景的学习成绩正态性检验P值均大于0.05,说明3组场景的学习成绩分数总体服从正态分布。因此,将学习成绩作为因变量,3组学习场景类型为自变量,做单因素方差分析。不同学习场景下学习成绩描述性统计数据见表2
对3组不同学习场景下学习成绩进行方差齐性检验,显著性P值大于0.05,满足方差齐性条件。单因素方差分析结果表明,3种不同学习场景对学习成绩的主效应显著,F(2,87)=5.836,P=0.004,具体见表3。根据事后多重比较,最小显著差异(Least Significant Difference,LSD)分析,虚拟现实学习组的总体学习成绩显著高于移动端视频学习(P=0.013)和纸质学习组(P=0.002),而移动端视频学习与纸质学习组(P=0.485)的总体学习成绩无显著性差异,具体见表4
学习者的学习成绩总分由记忆、理解与应用3个维度构成。对3组学习场景中的记忆、理解与应用各维度分别进行正态性和方差齐性检验。结果表明:3个维度的正态性和方差齐性检验P值均大于0.05,服从正态分布且满足方差齐性的要求。
对3个维度分别进行单因素方差分析。结果表明:在3种不同学习场景下,除记忆维度无显著性差异外,F(2,87)=0.320,P=0.727,理解和应用2个维度的主效应均显著,F(2,87)=4.157,P=0.019;F(2,87)=5.716,P=0.005。根据事后多重比较LSD分析,在理解维度,虚拟现实学习组的成绩显著高于移动端视频学习(P=0.041)和纸质学习组(P=0.007),移动端视频学习与纸质学习组(P=0.490)无显著性差异。在应用维度,虚拟现实学习组成绩显著高于移动端视频学习(P=0.008)和纸质学习组(P=0.003),移动端视频学习与纸质学习组(P=0.717)无显著性差异。
根据学习成绩试验数据结果,不同学习场景对学习者学习成绩的主效应显著。其中,虚拟现实学习场景下学习者的学习成绩最优,移动端视频次之,纸质学习成绩最差。另外,学习成绩总分由记忆、理解与应用3个维度组成。在理解和应用2个维度上,学习者在虚拟现实学习场景中的成绩,显著优于移动端视频和纸质学习场景,但在记忆维度,3种学习场景无显著差异。在理解维度,虚拟现实学习场景学习成绩最高,显著优于移动端视频和纸质学习。这说明虚拟现实提供的沉浸式和互动环境更有利于学习者理解复杂的知识点和内化学习内容,从而提高学习者对学习内容的推理和理解能力。在应用维度,虚拟现实学习场景表现出了最佳的学习成绩。这说明虚拟场景通过模拟操作的方式,深化了学习者在复杂情境中更深层次的认知处理能力。但在记忆维度上,虚拟现实学习与移动端视频和纸质学习场景无显著差异。这可能是由于虚拟场景中额外信息和环境细节所产生的认知负荷,需要学习者分配部分认知资源来处理与环境交互相关的任务,从而未能增加学习者对基础学习内容的记忆效果。因此,可能导致3种学习场景下的记忆效果无显著差异。
在地铁消防应急火灾逃生场景中,虚拟现实学习场景能提供更为丰富的感官体验,增强了学习者的感知维度[21]。逃生场景中高度仿真的环境通过视觉、听觉和触觉等多通道的感官输入,能够为学习者呈现更为立体和真实的学习内容,进而有效提高学习者的学习成绩。此外,虚拟现实呈现出以交互性为导向的特征[22]。学习成绩的提升不仅依赖于知识的传递,还与学习者对知识的深刻理解和应用能力密切相关。学习者可以通过虚拟现实场景中的实际操作,如手动报警器和地铁紧急开门装置的使用,来增强对真实火灾情景的模拟体验。这种实际操作与真实情景的贴近度更高,有助于学习者将知识转化为实际技能。这一丰富的体验进一步加深了学习者对所学知识的理解程度,从而显著提升学习成绩。然而,移动端视频学习和纸质学习场景的学习成绩不存在显著差异,可能与其教学方式和特点有关。移动端视频学习场景虽具备一定的视觉和听觉体验,但与虚拟现实场景相比,互动性和感官体验较弱,难以使学习者深刻理解和实际应用所学知识。而纸质学习则更注重文字传递,缺少感知体验,因此,在学习成绩方面表现不足。
对3组学习场景的学习兴趣进行正态性检验,不同场景的学习兴趣正态性检验P值均大于0.05,说明3组场景的学习兴趣分数总体服从正态分布。因此,将学习兴趣作为因变量,3组学习场景类型为自变量,做单因素方差分析,得到不同学习场景下学习兴趣描述性统计数据,具体见表5。然后对3组不同学习场景下学习兴趣进行方差齐性检验,显著性P值大于0.05,满足方差齐性条件。单因素方差分析结果表明:3种不同学习场景下的学习兴趣主效应显著,F(2,87)=43.596,P<0.001,见表6。根据事后多重比较LSD分析,虚拟现实学习组总体学习兴趣显著高于移动端视频学习(P<0.001)和纸质学习组(P<0.001),移动端视频学习与纸质学习组的总体学习兴趣无显著(P=0.130)差异,见表7
学习兴趣的总分由挑战与技能平衡、清晰的目标、及时的反馈、专注度、控制感、行动与知觉的融合、时间扭曲、流畅性、沉浸感、积极的情绪和学习体验满意度这11个维度构成。因此,对3组学习场景中学习兴趣的11个维度分别进行正态性和方差齐性检验。正态性和方差齐性检验的P值均大于0.05,服从正态分布且满足方差齐性要求。随后,对11个维度分别进行单因素方差分析。结果表明,在3种不同学习场景下,除流畅性维度无显著性差异外,F(2,87)=2.333,P=0.103,其余挑战与技能平衡、清晰的目标、及时的反馈、专注度、控制感、行动与知觉的融合、时间扭曲、沉浸感、积极的情绪和学习体验满意度10个维度的主效应均显著,F(2,87)=8.680,P<0.001;F(2,87)=4.453,P=0.014;F(2,87)=8.419,P<0.001;F(2,87)=4.869,P=0.010;F(2,87)=8.379,P<0.001;F(2,87)=7.108,P=0.001;F(2,87)=7.416,P=0.001;F(2,87)=22.919,P<0.001;F(2,87)=21.775,P<0.001;F(2,87)=6.301,P=0.003。根据事后多重比较LSD分析,在挑战与技能平衡维度,虚拟现实学习组显著高于移动端视频学习(P<0.001)和纸质学习组(P<0.001),移动端视频学习与纸质学习组(P=0.846)无显著性差异。在清晰的目标维度,虚拟现实学习组显著高于移动端视频学习(P=0.034)和纸质学习组(P=0.005),移动端视频学习与纸质学习组(P=0.475)无显著性差异。在及时的反馈维度,虚拟现实学习组显著高于移动端视频学习(P=0.006)和纸质学习组(P<0.001),移动端视频学习与移动端视频学习组(P=0.258)无显著性差异。在专注度维度,虚拟现实学习组显著高于移动端视频学习(P=0.006)和纸质学习组(P=0.011),移动端视频学习与纸质学习组(P=0.842)无显著性差异。在控制感维度,虚拟现实学习组显著高于移动端视频学习(P=0.023)和纸质学习组(P<0.001),移动端视频学习与纸质学习组(P=0.079)无显著性差异。在行动与知觉的融合维度,虚拟现实学习组显著高于移动端视频学习(P=0.002)和纸质学习组(P=0.002),移动端视频学习与纸质学习组(P=1.000)无显著性差异。在时间扭曲维度,虚拟现实学习组显著高于移动端视频学习(P=0.008)和纸质学习组(P<0.001),移动端视频学习与纸质学习组(P=0.331)无显著性差异。在沉浸感维度,虚拟现实学习组显著高于移动端视频学习(P<0.001)和纸质学习组(P<0.001),移动端视频学习与纸质学习组(P=0.848)无显著性差异。在积极的情绪维度,虚拟现实学习组显著高于移动端视频学习(P<0.001)和纸质学习组(P<0.001),移动端视频学习与纸质学习组(P=0.248)无显著性差异。在学习体验满意度维度,虚拟现实学习组显著高于移动端视频学习(P=0.007)和纸质学习组(P=0.001),移动端视频学习与纸质学习组(P=0.590)无显著性差异。
学习兴趣试验数据分析结果显示,不同学习场景对学习者学习兴趣的主效应显著。学习者在虚拟现实学习场境下学习兴趣效果最佳,其次是移动端视频学习场景,纸质学习场景学习兴趣效果最差。另外,学习兴趣总分由挑战与技能平衡、清晰的目标、及时的反馈、专注度、控制感、行动与知觉的融合、时间扭曲、流畅性、沉浸感、积极的情绪和学习体验满意度这11个维度构成。学习者在虚拟现实学习场景中的学习兴趣,除在流畅性维度下与移动端视频和纸质学习场景无显著差异外,其它维度下均有显著差异。
在挑战与技能平衡和清晰的目标维度上,虚拟现实学习场景得分最高,说明学习者觉得自身的技能水平与虚拟环境中带来的挑战是平衡的,并且帮助学习者理解学习目标和方向。在及时的反馈和专注度维度上,虚拟现实学习场景得分最高,说明虚拟现实通过其独有的视听触觉反馈,能提供即时的学习反馈,从而帮助学习者及时调整学习策略和行为,并保持高度集中的学习注意力。在控制感和行动与知觉的融合维度上,虚拟现实学习场景得分最高,说明学习者在虚拟空间中可通过自主探索和操作学习的灵活性更大,使其感觉是在真实空间中与环境参与互动。在时间扭曲和沉浸感维度上,虚拟现实学习场景得分最高,说明虚拟现实场景通过创造逼真的视觉环境和立体的空间音效,使学习者更能沉浸体验,且时间流逝感更为强烈。在积极的情绪和学习体验满意度维度上,虚拟现实学习得分最高,说明虚拟现实学习场景具有最佳的享乐体验感。但在流畅性维度上,虚拟现实、移动端视频和纸质学习在流畅性维度上的差异并不显著,这可能是因为3种场景中的教学内容和关键信息呈现均保持了一定的连贯性。尽管交互方式和呈现技术不同,但都能帮助学习者顺畅地完成学习任务,因此,可能导致3种学习场景在流畅性维度无显著差异。
在消防应急火灾逃生场景中,虚拟现实学习场景的游戏化教学体验所固有的趣味性和参与感,可能会极大增强学习者的学习兴趣。通过任务的方式参与学习,如在限定时间内找到最佳逃生路线,同时应对可能出现的随机事件,如新的火源、阻碍物或与环境交互过程所触发的声音反馈。学习者需要迅速调整策略以应对挑战。这种具有互动感和挑战性的学习方式不仅提升了学习者的沉浸感和紧迫感,而且通过教育目标与游戏机制的结合,能显著增强学习者的学习兴趣。另外,相较于传统的纸质阅读场景或移动端视频学习场景,虚拟现实技术提供的三维场景能够营造出第一人称视角与高自由度的探索空间,这样的方式能够更好的弥补学习者在旁观者视角上的体验缺失,极大的促进学习者“自在其中”的归属感和“自由”的自主感,从而提升学习者的学习兴趣和学习体验满意度[23-24]。而移动端视频学习因长时间观看视频可能导致视觉和听觉疲劳,缺乏即时的反馈,因此难以让学习者产生较好的学习兴趣。纸质学习场景的学习兴趣在3种学习场景类型中最弱,原因是其教学方式较为单调,使学习内容更加枯燥,从而限制学习兴趣的产生。
根据试验记录的生理数值,对不同学习场景下的心率和皮电数据进行统计分析,排除试验前的基线数值对结果的影响。因此扣除基线数值,将刺激引起的生理反应与参与者之间的内在生物学差异分离开来。在此基础上,对3组学习者的心率和皮电进行协方差分析,以探究不同学习场景对心理生理反应的可能性差异。
针对心率数据,以心率基线期的平均值作为协变量,心率唤醒期的平均值作为因变量,进行协方差分析。结果显示,在不同学习场景下,唤醒期心率平均值之间主效应显著,F(2,87)=55.263,P<0.001。具体而言,在虚拟现实学习组中,唤醒期心率的平均值修正均值为84.135,标准差为0.377。而在移动端视频学习组和纸质学习组中,唤醒期心率的平均值修正均值分别为79.680和78.954,标准差为0.377。进一步比较发现,虚拟现实学习组的唤醒期心率均值M和标准差SD分别为84.377和7.467,心率均值显著高于移动端视频学习组(M=79.545,SD=7.976)和纸质学习组(M=78.848,SD=8.337)。而移动端视频学习组和纸质学习组之间的唤醒期心率均值无显著性差异。其次,对于皮电数据,以皮电基线期的平均值作为协变量,皮电唤醒期的平均值作为因变量,进行了协方差分析。结果显示,在不同学习场景下,唤醒期皮电平均值之间主效应显著,F(2,87)=125.492,P<0.001。具体而言,在虚拟现实学习组中,唤醒期皮电的平均值修正均值为8.508,标准差为0.131。而在移动端视频学习组和纸质学习组中,唤醒期皮电的平均值修正均值分别为6.118和5.803,标准差为0.130。进一步比较发现,虚拟现实学习组的唤醒期皮电均值(M=9.050,SD=2.420)显著高于移动端视频学习组(M=5.744,SD=1.570)和纸质学习组(M=5.635,SD=1.458)。而移动端视频学习组和纸质学习组之间的唤醒期皮电均值无显著性差异,如图4所示。
根据心率和皮电的试验数据结果,不同学习场景下学习者的心率和皮电在唤醒期呈现显著差异。虚拟现实学习场景的唤醒期心率和皮电均值高于移动端视频学习和纸质学习场景,而移动端视频学习和纸质学习场景之间则没有明显的差异。
心率和皮电能够反映个体的情绪唤醒度[25]。虚拟现实学习场景通过其身临其境的特点,创造了更具真实感和参与感的学习体验,使学习者更加深入地融入学习场景中,激发其更强烈的生理唤醒并显著提高其情绪效价,使学习者在虚拟现实环境中呈现更高的生理数值。认知评估是诱发情绪的关键变量,当学习者认为学习任务具有较高价值且为能够自我掌控时,能够诱发其积极的学业情绪[26]。在虚拟现实学习场景中,学习者在教学任务的引导下进行思考和操作,这种互动方式显著增强了学习者的积极性和自主性,这种正向的认知评估可能在生理水平上引起学习者的专注度和兴趣,从而增加心率和皮电反应。另外,生理指标的升高还会体现在心理应激和生理应激上,心率和皮电数值越高,紧张程度也越高[27]。虚拟现实技术构建的写实场景和还原的音效可能会引发学习者更多的心理紧张和生理激活。在逃生环境中,学习者面临强烈的压力,而虚拟现实学习场景能更有效地模拟这种紧急感,使学习者对火灾逃生的紧迫性有更加深刻的认知和情感体验,从而在心率和皮电反应上呈现更高的唤醒程度。然而,学习者在虚拟现实学习场景中的心率和皮电虽然相对较高,但并不代表学习者处于不适或不良状态。相反,适度的紧张感和焦虑可以促进学习者更高层次的认知处理,提升学习表现[28-29]。因此,学习效果所产生的积极影响在一定程度上可能促进心率和皮电的提升。
1) 学习场景的类型显著影响学习者的学习成绩。虚拟现实场景下,学习者的学习成绩最高,移动端视频学习次之,纸质学习最差。
2) 学习场景的类型显著影响学习者的学习兴趣。虚拟现实场景下,学习者的学习兴趣最优,移动端视频学习次之,纸质学习最差。
3) 学习场景的类型显著影响学习者的生理指标。虚拟现实场景下,学习者的心率和皮电变化最显著,移动端视频学习次之,纸质学习最不明显。
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doi: 10.16265/j.cnki.issn1003-3033.2024.06.0258
  • 接收时间:2023-12-27
  • 首发时间:2025-07-09
  • 出版时间:2024-06-28
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  • 收稿日期:2023-12-27
  • 修回日期:2024-03-22
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    西南林业大学 艺术与设计学院,云南 昆明 650224

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**代沁伶(1982—)女,重庆人,博士,副教授,主要从事图像传播工程、视觉传达设计及新媒体设计理论方面的研究。E-mail:
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2种不同金属材料的力学参数

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species
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Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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