The authors acknowledge the financial support of the Social Sciences and Humanities Research Council of Canada (SSHERC), Natural Sciences and Engineering Research Council of Canada (NSERC), Fonds de Recherche Nature et Technologies du Qu&#233;bec (FQRNT) and Fonds de Recherche sur la Soci&#233;t&#233; et Culture du Qu&#233;bec (FQRSC).

该协议由法国精品行业institutionnel德拉RECHERCHE AVEC DESêtreshumains（CIER）DE L&#39;魁北克大学蒙特利尔（分校），这是赞同HEC-蒙特利尔的Tech3Lab研究机构获得了道德证书。该协议描述了每个那在我们的实验室环境和设备进行了具体步骤。尽管提供精确的软件的路径，以澄清的方法，这种技术是转让，并且可以与其他专有眼睛跟踪，自动面部情感识别，皮肤电活动和脑电图设备和软件被复制。 1.设置实验室环境<ol><li>打开眼跟踪器，脑电图放大器，四个记录计算机和扬声器。 </li><li>准备录音设备的设置： <ol><li>根据制造商的recomme准备脑电图设置与所需的材料nded程序。准备脑电图软件为即将到来的参与者。启动眼球跟踪软件，并创建了软件的一个新的参与者的个人资料。开始摄像软件和摄像机。 </li><li>启动同步软件，用于在60秒标记的项目创建的具体子程序。启动生理测量软件（记录电活动），并打开该项目创建的具体布局。调整参与者的椅子来的最高水平。 </li></ol></li></ol> 2.参与者准备<ol><li>请参与者阅读并签署道德的知情同意书。 </li><li>开展颅骨测量脑电图： <ol><li>查找（按10 - 20参照系）的锆石的位置上参与者的头部。沉浸脑电图净在盐水溶液（氯化钾）（见步骤1.2.1），并按照制造商的标准启动一个定时器（10分钟）。&lt;/ LI&gt; </ol></li><li>阅读研究和实验参与者的步骤的目的，“ 这项研究的目的是观察你的大脑活动，而你回答物理问题。首先，我们将安装传感器，那么你将被要求解决在电脑上10牛顿物理学的问题。我们会要求你采取45秒休息后每个问题闭上你的眼睛。每个问题之后，你会被要求对您的问题进行评估。“ </li><li>告诉主体，该实验的总持续时间将是90分钟。 </li><li>左侧的顶部的两个凝胶化传感器：安装生理传感器，根据制造商的建议。 </li><li>安装EEG帽，根据制造商的建议和（根据制造商的规格）中，在40千欧的阈值执行阻抗检查。 </li></ol> 3.数据收集<ol><li>确保所有的录音软件是在准备要同步启动： <ol><li>生理学（EDA数据）：点击“开始”按钮。 </li><li>视频拍摄：点击“打开”按钮。 </li><li>眼睛跟踪：点击“暂停”按钮。 </li><li>脑电图：点击“记录”按钮。 </li><li>同步软件：点击“绿色循环”按钮。 </li></ol></li><li>眼睛注视校准： <ol><li>执行了五点屏幕上的校准，并观察参与者，而他/她跟随红点（点击“工具/设置/校准......”）。重复此过程，直到足够的精度实现时，根据制造商的标准。 </li></ol></li><li>到参与者的屏幕项目任务说明：问他/她有阅读后有任何问题，如果他/她准备开始实验。 </li><li>请参与者解决10牛顿physics问题。 </li><li>如果需要的话，在45秒休息的一个执行阻抗检查（之前没有问题5）。 </li><li>确保参与者需要全45秒突破每一个问题前（以确定基线）。 </li></ol> 4.结束数据收集<ol><li>停止数据采集上的所有​​计算机，并从参与者中删除传感器。 </li></ol> 5.在参与者都有左<ol><li>清洁脑电帽杀菌剂和整理设备，根据制造商的建议。收集保存所有的数据文件，并创建FTP服务器上的备份。 </li><li>在参与者填写电子表格：注意数据收集过程中的任何特定事件或问题。擦除从Web浏览器的所有Cookie。 </li></ol> 6，数据预处理和导出到集成软件<ol start="1"><li>脑电图<ol><li>脑电图导入数据到脑电数据分析软件： <ol><li>创建一个名为“原始数据”，“历史”和“出口”的计算机上的三个空文件夹，以原始脑电数据粘贴到新创建的原始数据文件。 </li><li>在脑电数据分析软件，点击“文件/新建项目...”，并通过点击浏览，然后选择新创建的原始数据文件选择原始数据位置。选择的“历史”和以相同的方式“导出”文件夹的位置。 </li><li>点击“确定”。 （窗口应包含所有参与者的脑电数据）。 </li></ol></li><li>预处理脑信号： <ol><li>应用一个过滤器和一个凹口（点击“变换/ IIR滤波器...”）。在窗口中，使在1.5赫兹的低截止以12dB的斜率和高截止，在50赫兹与12 dB的斜率。也使一个凹口60赫兹的频率。 </li><li>因为一个直流放大器，直流detrend信号（点击“茶nsformations / DC Detrend ......“，并启用”基于时间“的标志前100毫秒和DC连接前100毫秒）。 </li><li>执行原始数据的检查（点击“转换/原始数据的检查......”，然后选择半自动神器去除）。选择以下内容：最大电压60μV/ MS;最大最小：200μV在200毫秒的时间间隔;振幅：-400至+400μV）。 </li><li>执行自动ICA与经典球形为眨眼去除（myographic工件不需要被删除，因为其范围是感兴趣的频率的外侧）。 （点击“变换/ ICA ......”。在ICA，过程的逆ICA的末端。） </li><li>再参考（“转换/重新引用...”）的信号，并选择“共同平均”。 </li><li>导出（单击“导出/通用数据导出...”）的文本格式的信号和标记（选择“.vhdr”;箱）为最终Matlab的建设的参与指数的。还可以选择“写入头文件”和“写入标记文件”框。 </li></ol></li><li>导入Matlab的信号。 <ol><li>运行MATLAB等EEGLab的GUI出现，并导入一个参与者的数据在同一时间输入“eeglab”。在GUI中，选择项目菜单“文件/导入数据/使用EEGLab功能和插件/脑可见光拍摄.vhdr文件”。 </li><li>在命令窗口中粘贴一个脚本16生成一个参与指数。 注：认知参与脚本由每个测试/（阿尔法+西塔）比率的平均值内的20秒的滑动窗口前述时间T计算重复这一过程每秒钟和一个新的滑动窗口来更新索引。 </li></ol></li><li>在MS Excel，打开是在用Matlab脚本结束时生成的参与指数的文本文件和应用Z-SCOR脑电图数据E正常化允许个体间的比较。 （对于每一个值，计算该公式在Excel中：Z =（值 - 总体均值）/总标准差）。 </li><li>保存z得分参与指数信号在MS Excel的CSV文件。 （点击文件/另存为...并在格式类型选择CSV）。 </li><li> （步骤6.1.2.2。）重复步骤，对每个参与者。 </li></ol></li><li>生理学： <ol><li>在生理数据分析软件导入EDA数据。 </li><li>应用这些参数进行预处理的生理信号： <ol><li>应用对数变换正常化电导的分布按维纳布尔斯和佳士得的23方法。 </li><li>平放在一个10秒的滑动窗口24的信号。 </li></ol></li><li>在生理软件，计算上的EDA数据z得分正常化，使个体间的比较。 （Z =（值 - 总体均值）/总标准差）。 <ol><li>突出与来自EDA通道光标的所有数据。 </li><li>在顶部的菜单中，选择EDA通道，并选择“的意思是”获得整个信道的平均值。还可以选择的EDA信道和“STDDEV”，以获得整个信道的标准偏差值。 </li><li>为了计算Z值方程，点击“转换/波形数学运算......”，并选择在源1的EDA通道。选择“ - ”（减号），在数学运算窗口和源2.选择在目的地菜单中的“新目标”选择K和进入EDA通道的平均值（见步骤6.2.3.2）。选择“转换整个浪潮”，单击确定，然后单击“转换/波形数学......”。选择源1 EDA-K通道，选择“/”（除）在数学操作窗口，在源2选择K，在目的地和恩特选择“新建目标”r是EDA信道（步骤6.2.3.2）的标准偏差值。选择“转换整个浪潮”，然后单击确定。 </li></ol></li><li>在导出CSV文件的信号（觉醒）。 （点击文件/另存为...并在格式类型选择CSV）。 </li></ol></li><li>自动面部情感识别： <ol><li>从媒体记录到自动面部表情识别软件导入的视频数据。 （点击“文件/新建... /参与者......”。通过点击选择在项目菜单中新的参与者后，单击“文件/新建/分析/视频...”。单击放大镜旁边的分析1，然后选择所需视频文件。 <ol><li>选择脱机分析“每三架”并激活“连续校准”。 </li><li>在一个CSV文件导出数据的价。 （点击“选项/设置/记录......”，勾选“写入价值的日志文件”对话框，点击“文件/导出...“，选择其中的日志文件将被出口的位置，并勾选”保存详细的日志“框。） </li><li>打开MS Excel的CSV文件。价数据列复制SPSS软件中的一列。点击“分析/描述性统计/描述性”，然后选择刚刚粘贴的变量名。勾选“保存标准值的变量”。与z得分列会出现。复制粘贴这些z得分超过在Excel文件中的旧数据。 </li></ol></li><li>保存与z分数以CSV格式信号（价）的Excel文件。 </li></ol></li></ol> 7.数据集成和同步<ol start="1"><li>在行为分析软件： <ol><li>进口眼球追踪视频（行为参与）。 （点击“文件/导入/视频在一个新的观察......”命名新的观察和选择所需的视频文件。） </li><li>代码相关的每次视频haviors和上下文事件（时间标记，正确/错误的答案）。 </li><li>所有导入外部数据与相应的头：z得分脑电信号（认知参与）中，z得分EDA信号（情感投入），Z值价的数据（情感投入）的。 （点击“文件/导入/外部数据...”，选择相应的文件类型，并选择正确的CSV文件。） </li></ol></li><li>根据这些公式同步计算机之间的时间： <ol><li>第一标记的眼睛注视 - 从一次脑电图=时间眼睛注视+脑电图第二标记的眼睛注视时间。 </li><li>时间从时间眼睛注视的情绪认知=时间眼睛注视+面部情感第一标记 - 标记第一次在眼睛注视。 </li><li>不时在眼睛凝视时间在电活动=时间眼睛注视+第一标记的电活动 - 在眼睛注视第一标志。 </li></ol></li><li>按“输入偏移量数据按Ctrl + Shift + =221 ;,打开偏移量菜单。选择“数值偏移”到每对数据源之间秒进入时间[确定]），根据上述的计算。 </li><li>根据在研究感兴趣的变量产生一个报告。 <ol><li>选择将在报告中生成有趣的变量（点击“分析/选择数据/新配置文件数据......”）。从左边的“开始”框和“结果”框之间滑动所需要的变量，在右边。 </li><li>生成报告。 （点击“分析/数值分析/新建...”，单击“统计”，并点击“计算”检查外部数据菜单完成的平均箱。） </li></ol></li><li>将数据导出到统计分析软件，并根据该研究的目标执行分析。 </li></ol>

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J., Martin, I., Venables, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrodermal+activity.">Electrodermal activity.</a> Techniques in Psychophysiology. , 3-67 (1980).</li><li>Boucsein, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Electrodermal Activity. , (2012).</li><li>Sarlo, M., Palomba, D., Buodo, G. M., Minghetti, R., Stegagno, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blood+pressure+changes+highlight+gender+differences+in+emotional+reactivity+to+arousing+pictures.">Blood pressure changes highlight gender differences in emotional reactivity to arousing pictures.</a> Biol. Psychol. 70 (3), 188-196 (2005).</li><li>Martens, R. 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The authors have nothing to disclose.

在该协议中的关键步骤方面，首先应当指出，数据的质量始终是神经生理学收集技术的主要焦点。在这种方法中，研究助理必须特别注意​​指示主题，以尽量减少头部运动，这将干扰价监测（失去正确的杆面角度的摄像头），或产生的脑电图myographic文物。在另一方面，平衡必须保持真正的解决问题和干预措施更符合人体工程学的数据集合所做的真实性之间。同样重要的是要注意，脑电图数据收...

参与起着学习了至关重要的作用。对于克拉克和迈耶2，“所有的学习要求参与，”不管交货媒体。张某等 3还建议，增加学生的参与可以提高学习效果，如解决问题和批判性思维能力。定义参与仍然是一个挑战。在他们的文献综述，Fredricks，布鲁门菲尔德和巴黎1定义参与其多面性：“行为参与借鉴了参与的念头;它包括参与学术和社交或课外活动。 （...）情感投入包括正面和负面的反应老师，同学，学者和学校，被推定为创建联系的对象和影响力的意愿做的工作。最后，认知参与借鉴心理投资的理念;它采用体贴，并愿意尽努力NEC埃森理解复杂的思想，掌握高难度的技巧。“ Fredricks，布鲁门菲尔德和巴黎1还声称，注重行为，情绪和认知，参与的概念中，可提供学习更丰富的特性。这些作者指出，研究一个健壮体分别针对接合的每个部件，但这些部件并没有被研究结合。他们还观察到的信息很少关于尺寸之间，更多的研究可能有助于规划微调教学干预的相互作用。作为在这个方向迈出的一步，本文介绍的开发是为了收集，并在学习任务分析的定量和定性数据，同步，对行为，情绪和认知参与研究的方法论。 使神经科学到教育 BehavIOR，因此行为的参与，一直是教育研究中央重点：主要集中于发生在长时间内的时间，前后测试之间的变化，在知识和行为的研究设计，并在间隔小时，周，几个月或几年。行为，情感和认知参与区分仍然是一个挑战，因为最后两个维度是没有系统观察到外部。认知和情绪必须被从观察推断或评价与自我报告的措施。从外部来看，它仍然难以确定学生是否正在试图让他们的工作尽可能快地或使用深层次的学习策略，掌握了具体的内容进行。就事实而言，Fredricks，布鲁门菲尔德和巴黎1无法找到使用认知参与的直接，客观的任何措施发表的研究报告。 在最近的技术发展神经科学领域创造了科研教育新的可能性。新的数据收集方法和神经人体工程学的领域发展分析算法看起来非常有前途的定性和定量研究的过程中学习任务。其他学科，如经济学，心理学，市场营销，和人体工程学，一直在使用神经生理学测量，以评估认知参与了一段时间4-8。神经生理学的措施，再加上高效的分析算法，允许一个学习的现象，而不会干扰它。就其性质而言，自我报告的问卷脱离学习的学生。神经生理学的措施让研究设计，以更真实的学习环境中进行。这些工具包括设备监测心脏速率，呼吸速率，血压，体温，瞳孔直径，皮肤电活动，脑电图（EEG） 等 。 <st荣&gt;聚会同步数据的行为，情绪，认知和参与作为代表性的成果继用此协议，本文将提出一个研究中，学习者需要解决，在电脑屏幕上，在机械物理学十大难题的部分结果。在以往的工作进行了9开发了这些问题。收集的数据神经生理学，而学生是解决问题和45秒休息时放松，用自己的眼睛闭上，每个​​问题之后。 如上所述，行为接合数据由软件相互作用（鼠标移动和点击），眼睛注视，性能和回答由学习者与系统而完成任务1相互作用产生的问题。一种眼球追踪系统来收集软件的交互和眼睛注视数据。性能数据（时间解决一个问题，答案的正确性）收集在调查网站被用来呈现的任务。该网站也被用来收集与改编自布拉德利和朗10调查问卷收集自我报告的数据。情感投入涉及情感的表征。据郎11，情绪的特征价方面（愉快/不愉快的）和觉醒（CALM /激起）。情感投入数据进行了相应的收集，使用量化情绪价和皮肤电活动编码器/传感器觉醒12,13自动面部表情识别软件。皮肤电活动（EDA）指的是当一个非常弱的电流稳定地在它们之间传递的两个电极之间所记录的电阻。卡西奥普，Tassinary和Berntson 14表明，记录的电阻根据被检者的觉醒而变化。因此，心理生理数据，例如化合价或觉醒，被认为是情感接合的相关因素。 <p类=“jove_content”&gt;最后，认知参与数据通过脑电图（EEG）收集。脑电图措施，在头皮上，同步于脑的神经元群体的电活动。从头皮记录的电信号往往振荡和频率分量组成。按照惯例，这些频率被分组序列中，被称为带。例如，α，β和θ频带是本研究的焦点。根据神经科学的研究14，这些频带反映在大脑的特定区域不同的认知处理能力。因此，特定频率的功率谱密度（PSD）的分析，结合对警觉性和注意力大量研究7,15，使研究人员能够在任务中量化认知参与。作为米库尔卡等人 16指出，有研究表明β活度和认知警觉和alpha一个之间的间接关系之间的直接关系ðTHETA活动和警觉性。因此，教皇，鲍嘉和Bartoleme 7开发了计算的三个波段的PSD参与指数：公测/（阿尔法+ THETA）。这比在其他研究中的参与16,17,18验证。随着时间的推移表征认知参与，快速傅立叶变换（FFT）将来自每个活性部位（F3，F4，O1，O2）脑电图信号转换成一个功率谱。在时间T脑电图参与指数是由每个接合比率的平均值中时间T重复这一过程每秒钟和一个新的滑动窗口来更新索引之前的20秒的滑动窗口来计算。 由于这种方法的目的是提供接合的多个尺寸的富分析，数据同步是至关重要的。由于莱热等 19提醒读者，设备制造商强烈推荐使用每次测量工具只有一台电脑，以保证其指定的精度乐VEL。因此，当多台计算机被使用，记录在计算机之间的同步成为一个关键步骤。录音不能在完全相同的时间都被启动，并且每个数据流具有其特定的时间框架（ 例如 ，秒0的眼跟踪≠脑电图或生理数据秒0）。这是极为重要的：数据流之间的去同步化装置中的错误接合的每一维的量化。有并发的生理和行为同步录音的方式不同。这些方法可分成两种主要方法;直接和间接的20。在下一节介绍的协议是基于在那里的外部设备，一个syncbox，用于晶体管-晶体管逻辑（TTL）信号发送到所有的记录设备（ 如图1）的间接的方法。由于每一件设备具有不同的开始时间，将TTL标记被记录在日志文件中以相对<html>延迟。标记，然后用于重新对准信号，从而保证在每个记录后正确的同步。甲行为分析软件程序，它允许外部文件集成用于重新同步每个数据流的时间轴，并执行接合的每个维的定量和定性分析。 <img alt="图1" src="/files/ftp_upload/52627/52627fig1.jpg" /> 图1.架构的数据采集系统，实验室环境中的行为（眼动跟踪），情感（EDA和面部表情）和认知（EEG）参与收集数据包含多台计算机。这就提出了一个同步挑战对于那些在它们各自的计算机的时钟被引用的数据。为了能够分析所有数据以相同的参考时间，在实验室安装涉及发送TTL信号到所有数据流的syncbox。NK“&gt;点击此处查看该图的放大版本。 为了评估在同步方面的方法的精确度，45秒的暂停每个的机械物理问题之前进行了介绍。在这些暂停，受试者放松，闭上眼睛。正如在其他研究4,9,16,17,18，这些暂停应该引起在采集到的信号显著的变化：在眼球追踪立即消失（行为参与）两个眼瞳点和认知参与立刻降（EEG信号）被观察到。信号的这些特定组件被用来评估该同步的普遍有效性。最近出版的完全或部分地依赖于该同步过程，在信息系统19，人机交互21和教育9,22领域论文，提供它的有效性的证据。

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>EGI GSN-32&#160;</td>
			<td>EGI</td>
			<td>n/a</td>
			<td>Dense array EEG</td>
		</tr>
		<tr>
			<td>Netstation v.5.0</td>
			<td>EGI</td>
			<td>n/a</td>
			<td>EEG data collection software: EEG is collected with 32-electrode dense array electroencephalography (dEEG) geodesic sensor net using Netstation acquisition software and EGI amplifiers (Electrical Geodesics, Inc). The vertex (recording site Cz) is the reference electrode for recording. Impedance is kept below 50 k&#937; with a sampling rate of 250 Hz.&#160;</td>
		</tr>
		<tr>
			<td>Facereader v.4</td>
			<td>Noldus</td>
			<td>n/a</td>
			<td>Facial emotion recognition software</td>
		</tr>
		<tr>
			<td>Syncbox</td>
			<td>Noldus</td>
			<td>n/a</td>
			<td>Syncbox start the co-registration of EEG and gaze data by sending a Transistor-Transistor Logic (TTL) signal to the EGI amplifier and a keystroke signal to the Tobii Studio v 3.2.</td>
		</tr>
		<tr>
			<td>Logitech C600&#160; Webcam</td>
			<td></td>
			<td>960-000396</td>
			<td>Webcam used to gather video data sent to mediarecorder and that will be analyzed in Facereader</td>
		</tr>
		<tr>
			<td>The Observer XT</td>
			<td>Noldus</td>
			<td>n/a</td>
			<td>Integration and synchronization software: The Noldus Observer XT (Noldus Information Technology) is used to synchronize all behavioral, emotional and cognitive engagement data.&#160;</td>
		</tr>
		<tr>
			<td>On-Screen LED illumination</td>
			<td>Noldus</td>
			<td>n/a</td>
			<td>Neon positioned on computer screen in order to correctly light the face of subjects</td>
		</tr>
		<tr>
			<td>MediaRecorder</td>
			<td>Noldus</td>
			<td>n/a</td>
			<td>Video data collection software</td>
		</tr>
		<tr>
			<td>Tobii X60</td>
			<td>Tobii</td>
			<td>n/a</td>
			<td>Collect eye-movement patterns :&#160; used to record subjects&#8217; eye movement patterns at 60Hz during the experiment.&#160;</td>
		</tr>
		<tr>
			<td>Tobii Studio v.3.2</td>
			<td>Tobii</td>
			<td>n/a</td>
			<td>Eye-tracking data collection and analysis software</td>
		</tr>
		<tr>
			<td>Analyzer 2</td>
			<td>Brainvision</td>
			<td>n/a</td>
			<td>EEG signal processing software</td>
		</tr>
		<tr>
			<td>Acqknowledge v.4.0</td>
			<td>Biopac</td>
			<td>ACK100M</td>
			<td>Physiological signal acquisition and processing software</td>
		</tr>
		<tr>
			<td>Control III germicide solution</td>
			<td>Maril Products.</td>
			<td>10002REVA-20002-1</td>
			<td>Disinfectant solution used with EEG helmets : recommended by EGI</td>
		</tr>
		<tr>
			<td>Unipark</td>
			<td>QuestBack AG</td>
			<td>n/a</td>
			<td>Online survey environment</td>
		</tr>
	</tbody>
</table>

assessing the multiple dimensions of engagement to characterize learning: a neurophysiological perspective

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: behavioral, emotional and cognitive. They observed that individual types of engagement had not been studied in conjunction, and little information was available about interactions or synergy between the dimensions; consequently, more studies would contribute to creating finely tuned teaching interventions. Benefiting from the recent technological advances in neurosciences, this paper presents a recently developed methodology to gather and synchronize data on multidimensional engagement during learning tasks. The technique involves the collection of (a) electroencephalography, (b) electrodermal, (c) eye-tracking, and (d) facial emotion recognition data on four different computers. This led to synchronization issues for data collected from multiple sources. Post synchronization in specialized integration software gives researchers a better understanding of the dynamics between the multiple dimensions of engagement. For curriculum developers, these data could provide informed guidelines for achieving better instruction/learning efficiency. This technique also opens up possibilities in the field of brain-computer interactions, where adaptive learning or assessment environments could be developed.

<html> 图2和3示出的屏幕截图的整合和行为，情感和认知参与数据的同步在行为分析软件应用程序的结果。在两个图中，左手区组织的研究对象和编码方案。在中间部分，视频（带有红点）示出了在任务期间被检者的眼睛注视。主体的参与行为可以根据他/她的任务中寻找和执行什么操作来推断。在较低部分，一个时间标记同步地滚动数据的三条轨道：将EDA（觉醒）及面部情感价为情感?...

Watch this Scientific Journal Video about Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective at JoVE.com

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners&#8217; engagement during a task.

评估参与的多维度来表征学习：神经生理学角度

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: ...

assessing-multiple-dimensions-engagement-to-characterize-learning

Research

JoVE Journal

Behavior

12.4K 次观看.  Université du Québec à Montréal. This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners’ engagement during a task. 

视频: Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

The Use of the Puzzle Box as a Means of Assessing the Efficacy of Environmental Enrichment

Environmental enrichment can dramatically influence the development and function of neural circuits. Further, enrichment has been shown to successfully delay the onset of symptoms in models of Huntington&#8217;s disease 1-4, suggesting environmental factors can evoke a neuroprotective effect against the progressive, cellular level damage observed in neurodegenerative disorders. The ways in which an animal can be environmentally enriched, however, can vary considerably. Further, there is no straightforward manner in which the effects of environmental enrichment can be assessed: most methods require either fairly complicated behavioral paradigms and/or postmortem anatomical/physiological analyses. This protocol describes the use of a simple and inexpensive behavioral assay, the Puzzle Box 5-7 as a robust means of determining the efficacy of increased social, sensory and motor stimulation on mice compared to cohorts raised in standard laboratory conditions. This simple problem solving task takes advantage of a rodent&#8217;s innate desire to avoid open enclosures by seeking shelter. Cognitive ability is assessed by adding increasingly complex impediments to the shelter&#8217;s entrance. The time a given subject takes to successfully remove the obstructions and enter the shelter serves as the primary metric for task performance. This method could provide a reliable means of rapidly assessing the efficacy of different enrichment protocols on cognitive function, thus paving the way for systematically determining the role specific environmental factors play in delaying the onset of neurodevelopmental and neurodegenerative disease.

Environmental enrichment provides a potential protective effect against neurodegenerative disorders. Currently, however, there is no easy way of determining the efficacy of enrichment procedures. This protocol describes a simple &#8220;Puzzle Box&#8221; method for assessing an animal&#8217;s cognitive function, in order to reveal the effectiveness of environmental enrichment.

该拼图方块的使用作为评价环境富集的功效的一种手段

Environmental enrichment can dramatically influence the development and function of neural circuits.  Further, enrichment has been shown to successfully ...

科研

行为学

Mindfulness in Motion (MIM): An Onsite Mindfulness Based Intervention (MBI) for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement

A pragmatic mindfulness intervention to benefit personnel working in chronically high-stress environments, delivered onsite during the workday, is timely and valuable to employee and employer alike. Mindfulness in Motion (MIM) is a Mindfulness Based Intervention (MBI) offered as a modified, less time intensive method (compared to Mindfulness-Based Stress Reduction), delivered onsite, during work, and intends to enable busy working adults to experience the benefits of mindfulness. It teaches mindful awareness principles, rehearses mindfulness as a group, emphasizes the use of gentle yoga stretches, and utilizes relaxing music in the background of both the group sessions and individual mindfulness practice. MIM is delivered in a group format, for 1 hr/week/8 weeks. CDs and a DVD are provided to facilitate individual practice. The yoga movement is emphasized in the protocol to facilitate a quieting of the mind. The music is included for participants to associate the relaxed state experienced in the group session with their individual practice. To determine the intervention feasibility/efficacy we conducted a randomized wait-list control group in Intensive Care Units (ICUs). ICUs represent a high-stress work environment where personnel experience chronic exposure to catastrophic situations as they care for seriously injured/ill patients. Despite high levels of work-related stress, few interventions have been developed and delivered onsite for such environments. The intervention is delivered on site in the ICU, during work hours, with participants receiving time release to attend sessions. The intervention is well received with 97% retention rate. Work engagement and resiliency increase significantly in the intervention group, compared to the wait-list control group, while participant respiration rates decrease significantly pre-post in 6/8 of the weekly sessions. Participants value institutional support, relaxing music, and the instructor as pivotal to program success. This provides evidence that MIM is feasible, well accepted, and can be effectively implemented in a chronically high-stress work environment.

Mindfulness in Motion MIM: An Onsite Mindfulness Based Intervention MBI for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement

The Mindfulness in Motion (MIM) protocol offers a pragmatic Mindfulness Based Intervention (MBI) on-site, for persons working in chronically high-stress work environments that significantly increases resiliency and work engagement. The protocol has proven feasible, beneficial, and is easily adaptable to other high-stress workplaces.

正念的运动 （MIM）：一种基于现场干预正念（MBI）用于长期的高压力的工作环境，以增加弹性和工作投入

A pragmatic mindfulness intervention to benefit personnel working in chronically high-stress environments, delivered onsite during the workday, is timely ...

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning process. Here a method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process. This discovery-learning task uses an infant activated mobile that rotates and plays music based on specified leg action of infants. Supine infants activate the mobile by moving their feet vertically across a virtual threshold. This paradigm is unique in that as infants independently discover that their leg actions activate the mobile, the infants&#8217; leg movements are tracked using a motion capture system allowing for the quantification of the learning process. Specifically, learning is quantified in terms of the duration of mobile activation, the position variance of the end effectors (feet) that activate the mobile, changes in hip-knee coordination patterns, and changes in hip and knee muscle torque. This information describes infant exploration and exploitation at the interplay of person and environmental constraints that support task-specific action. Subsequent research using this method can investigate how specific impairments of different populations of infants at risk for movement disorders influence the discovery-learning process for task-specific action.

A method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process.

量化学习婴幼儿：跟踪腿操作期间发现，学习任务

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning ...

Vagus Nerve Stimulation as a Tool to Induce Plasticity in Pathways Relevant for Extinction Learning

Extinction describes the process of attenuating behavioral responses to neutral stimuli when they no longer provide the reinforcement that has been maintaining the behavior. There is close correspondence between fear and human anxiety, and therefore studies of extinction learning might provide insight into the biological nature of anxiety-related disorders such as post-traumatic stress disorder, and they might help to develop strategies to treat them. Preclinical research aims to aid extinction learning and to induce targeted plasticity in extinction circuits to consolidate the newly formed memory. Vagus nerve stimulation (VNS) is a powerful approach that provides tight temporal and circuit-specific release of neurotransmitters, resulting in modulation of neuronal networks engaged in an ongoing task. VNS enhances memory consolidation in both rats and humans, and pairing VNS with exposure to conditioned cues enhances the consolidation of extinction learning in rats. Here, we provide a detailed protocol for the preparation of custom-made parts and the surgical procedures required for VNS in rats. Using this protocol we show how VNS can facilitate the extinction of conditioned fear responses in an auditory fear conditioning task. In addition, we provide evidence that VNS modulates synaptic plasticity in the pathway between the infralimbic (IL) medial prefrontal cortex and the basolateral complex of the amygdala (BLA), which is involved in the expression and modulation of extinction memory.

Vagus nerve stimulation (VNS) has emerged as a tool to induce targeted synaptic plasticity in the forebrain to modify a range of behaviors. This protocol describes how to implement VNS to facilitate the consolidation of fear extinction memory.

迷走神经刺激作为一种工具来诱导可塑性相关途径灭绝学习

Extinction describes the process of attenuating behavioral responses to neutral stimuli when they no longer provide the reinforcement that has been ...

Place and Response Learning in the Open-field Tower Maze

This protocol describes how the Open-field Tower Maze (OFTM) paradigm is used to study spatial learning in rodents. This maze is especially useful for examining how rats learn to use a place- or response-learning to successfully navigate in an open-field arena. Additionally, this protocol describes how the OFTM differs from other behavioral maze paradigms that are commonly used to study spatial learning in rodents. The OFTM described in this article was adapted from the one previously described by Cole, Clipperton, and Walt (2007). Specifically, the OFTM was created to test spatial learning in rodents without the experimenter having to consider how &#8220;stress&#8221; might play a role as a confounding variable. Experiments have shown that stress-alone can significantly affect cognitive function1. The representative results section contains data from an experiment that used the OFTM to examine the effects of estradiol treatment on place- and response-learning in adult female Sprague Dawley rats2. Future studies will be designed to examine the role of the hippocampus and striatum in place- and response-learning in the OFTM.

The Open-field Tower Maze (OFTM) is a maze created to study the behavioral and neural mechanisms of spatial learning (e.g., place- or response-learning) in rats. This maze is especially useful for experimenters who want to use a non-stressful maze paradigm to investigate spatial learning in their research.

在打开场塔迷宫的地方，反应学习

This protocol describes how the Open-field Tower Maze (OFTM) paradigm is used to study spatial learning in rodents. This maze is especially useful for ...

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Understanding the mechanisms underlying locomotor learning helps researchers and clinicians optimize gait retraining as part of motor rehabilitation. However, studying human locomotor learning can be challenging. During infancy and childhood, the neuromuscular system is quite immature, and it is unlikely that locomotor learning during early stages of development is governed by the same mechanisms as in adulthood. By the time humans reach maturity, they are so proficient at walking that it is difficult to come up with a sufficiently novel task to study de novo locomotor learning. The split-belt treadmill, which has two belts that can drive each leg at a different speed, enables the study of both short- (i.e., immediate) and long-term (i.e., over minutes-days; a form of motor learning) gait modifications in response to a novel change in the walking environment. Individuals can easily be screened for previous exposure to the split-belt treadmill, thus ensuring that all experimental participants have no (or equivalent) prior experience. This paper describes a typical split-belt treadmill adaptation protocol that incorporates testing methods to quantify locomotor learning and generalization of this learning to other walking contexts. A discussion of important considerations for designing split-belt treadmill experiments follows, including factors like treadmill belt speeds, rest breaks, and distractors. Additionally, potential but understudied confounding variables (e.g., arm movements, prior experience) are considered in the discussion.

We describe a protocol for investigating human locomotor adaptation using the split-belt treadmill, which has two belts that can drive each leg at a different speed. We specifically focus on a paradigm designed to test the generalization of adapted locomotor patterns to different walking contexts (e.g., gait speeds, walking environments).

用分体式跑步机评价人类运动适应的泛化

Understanding the mechanisms underlying locomotor learning helps researchers and clinicians optimize gait retraining as part of motor rehabilitation. ...

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that involves finger-pressing movements while sitting, the modified SRT task requires participants to step with both feet while maintaining a standing posture. This stepping task necessitates whole body actions that impose postural challenges. The foot-stepping task complements the classic SRT task in several ways. The foot-stepping SRT task is a better proxy for the daily activities that require ongoing postural control, and thus may help us better understand sequence learning in real-life situations. In addition, response time serves as an indicator of sequence learning in the classic SRT task, but it is unclear whether response time, reaction time (RT) representing mental process, or movement time (MT) reflecting the movement itself, is a key player in motor sequence learning. The foot-stepping SRT task allows researchers to disentangle response time into RT and MT, which may clarify how motor planning and movement execution are involved in sequence learning. Lastly, postural control and cognition are interactively related, but little is known about how postural control interacts with learning motor sequences. With a motion capture system, the movement of the whole body (e.g., the center of mass (COM)) can be recorded. Such measures allow us to reveal the dynamic processes underlying discrete responses measured by RT and MT, and may aid in elucidating the relationship between postural control and the explicit and implicit processes involved in sequence learning. Details of the experimental set-up, procedure, and data processing are described. The representative data are adopted from one of our previous studies. Results are related to response time, RT, and MT, as well as the relationship between the anticipatory postural response and the explicit processes involved in implicit motor sequence learning.

The &quot;Motor&quot; in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

We introduce the foot-stepping serial reaction time (SRT) task. This modified SRT task, complementing the classic SRT task that involves only finger-pressing movement, better approximates daily sequenced activities and allows researchers to study the dynamic processes underlying discrete response measures and disentangle the explicit process operating in implicit sequence learning.

隐式电机序列学习中的 "马达": 步进串行反应时间任务

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that ...

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Over the last decade, employing computer animations for animal behavior research has increased due to its ability to non-invasively manipulate the appearance and behavior of visual stimuli, compared to manipulating live animals. Here, we present the FishSim Animation Toolchain, a software framework developed to provide researchers with an easy-to-use method for implementing 3D computer animations in behavioral experiments with fish. The toolchain offers templates to create virtual 3D stimuli of five different fish species. Stimuli are customizable in both appearance and size, based on photographs taken of live fish. Multiple stimuli can be animated by recording swimming paths in a virtual environment using a video game controller. To increase standardization of the simulated behavior, the prerecorded swimming path may be replayed with different stimuli. Multiple animations can later be organized into playlists and presented on monitors during experiments with live fish.
In a case study with sailfin mollies (Poecilia latipinna), we provide a protocol on how to conduct a mate-choice copying experiment with FishSim. We utilized this method to create and animate virtual males and virtual model females, and then presented these to live focal females in a binary choice experiment. Our results demonstrate that computer animation may be used to simulate virtual fish in a mate-choice copying experiment to investigate the role of female gravid spots as an indication of quality for a model female in mate-choice copying.
Applying this method is not limited to mate-choice copying experiments but can be used in various experimental designs. Still, its usability depends on the visual capabilities of the study species and first needs validation. Overall, computer animations offer a high degree of control and standardization in experiments and bear the potential to &#39;reduce&#39; and &#39;replace&#39; live stimulus animals as well as to &#39;refine&#39; experimental procedures.

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Using the novel FishSim Animation Toolchain, we present a protocol for non-invasive visual manipulation of public information in the context of mate-choice copying in sailfin mollies. FishSim Animation Toolchain provides an easy-to-use framework for the design, animation and presentation of computer-animated fish stimuli for behavioral experiments with live test fish.

利用fishsim动画工具链调查鱼类行为--以鱼翅钼中的选物复制为例

Over the last decade, employing computer animations for animal behavior research has increased due to its ability to non-invasively manipulate the ...

An Instrumented Pull Test to Characterize Postural Responses

Impairment of postural reflexes, termed postural instability, is a common and disabling deficit in Parkinson's disease. To assess postural reflexes, clinicians typically employ the pull test to grade corrective responses to a backward perturbation at the shoulders. However, the pull test is prone to issues with reliability and scaling (score/4). Here, we present an instrumented version of the pull test to more precisely quantify postural responses. Akin to the clinical test, pulls are manually administered except pull force is also recorded. Displacements of the trunk and feet are captured by a semi-portable motion tracking system. Raw data represent distance traveled (in millimeter units), making subsequent interpretation and analysis intuitive. The instrumented pull test also detects variabilities influencing pull test administration, such as pull force, thereby identifying and quantifying potential confounds that can be accounted for by statistical techniques. The instrumented pull test could have application in studies seeking to capture early abnormalities in postural responses, track postural instability over time, and detect responses to therapy.

Impairment of postural reflexes, termed postural instability, is difficult to quantify. Clinical assessments such as the pull test suffer issues with reliability and scaling. Here, we present an instrumented version of the pull test to objectively characterize postural responses.

一种表征姿势反应的仪器拉力测试

Impairment of postural reflexes, termed postural instability, is a common and disabling deficit in Parkinson's disease. To assess postural reflexes, ...

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Learning disabilities (LDs) encompass disorders of those who have difficulty learning and using academic skills, exhibiting performance below expectations for their chronological age in the areas of reading, writing, and/or mathematics. Each of the disorders making up the LDs involve different deficits; however, some commonalities can be found within that heterogeneity, such in terms of learning self-regulation and metacognition. Unlike in early ages and later educational levels, there are hardly any evidence-based evaluation protocols for adults with LDs. LDs influence academic performance but also have serious consequences in professional, social, and family contexts. In response to this, the current work proposes a multimodal evaluation protocol focused on metacognitive, self-regulation of learning, and emotional processes, which make up the basis of the difficulties in adults with LDs. The assessment is carried out through analysis of the on-line learning process using a variety methods, techniques, and sensors (e.g., eye tracking, facial expressions of emotion, physiological responses, concurrent verbalizations, log files, screen recordings of human-machine interactions) and off-line methods (e.g., questionnaires, interviews, and self-report measures). This theoretically-driven and empirically-based guideline aims to provide an accurate assessment of LDs in adulthood in order to design effective prevention and intervention proposals.

The current work proposes a multimodal evaluation protocol focused on metacognitive, self-regulation of learning, and emotional processes, which make up the basis of the difficulties in adults with LDs.

评估学习困难成人元认知和自我调节的多式联运协议

Learning disabilities (LDs) encompass disorders of those who have difficulty learning and using academic skills, exhibiting performance below expectations ...