EEG Correlates of Engagement During Assessment

Q3 Social Sciences ETS Research Report Series Pub Date : 2021-01-09 DOI:10.1002/ets2.12312
Laura K. Halderman, Bridgid Finn, J.R. Lockwood, Nicole M. Long, Michael J. Kahana
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引用次数: 2

Abstract

In educational assessment, low engagement is problematic when tests are low stakes for students but have significant consequences for teachers or schools. In the current study, we sought to establish the electroencephalographic (EEG) correlates of engagement and to distinguish engagement from mental effort. Forty university students participated in a simulated GRE® General Test session while scalp EEG was recorded from 128 channels. Participants completed two verbal and two quantitative GRE test blocks for a total of 40 items each, and after each item, rated either their engagement or mental effort on a scale of 1–6. We computed power for seven frequency bands (delta, theta, alpha, beta, and low, medium, and high gamma) across six regions of interest: left hemisphere (LH) and right hemisphere (RH) frontal, temporal, and parietal. Preliminary results suggested that gamma power (30–150 hertz [Hz]) indexed differences between high- and low-engagement ratings. This pattern was similar but weaker for mental effort. A cumulative logit model with cross-classified random effects determined that high gamma (90–150 Hz) over the LH temporal cortex predicted engagement ratings, while controlling for reaction time and accuracy. However, for effort ratings, reaction time was the sole significant predictor. These results suggest that high gamma may be a correlate of engagement during complex cognitive tasks, but not a correlate of effort. The findings are a promising step toward the goal of objectively measuring engagement during assessment tasks.

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评估过程中参与的脑电图相关性
在教育评估中,当考试对学生来说是低风险的,但对教师或学校却有重大影响时,低参与度是有问题的。在当前的研究中,我们试图建立参与的脑电图(EEG)相关性,并区分参与和精神努力。40名大学生参加了模拟GRE普通考试,同时记录了128个通道的头皮脑电图。参与者完成了两个口头和两个定量的GRE测试块,每个测试块总共有40个项目,每个项目之后,他们在1-6的范围内对他们的投入或精神努力进行评分。我们计算了六个感兴趣区域(左半球(LH)和右半球(RH)额叶、颞叶和顶叶)的七个频段(δ、θ、α、β以及低、中、高γ)的功率。初步结果表明,伽马能量(30-150赫兹[Hz])反映了高参与度和低参与度评级之间的差异。这种模式与脑力劳动相似,但较弱。一个具有交叉分类随机效应的累积logit模型表明,在控制反应时间和准确性的同时,左颞叶皮层的高伽马(90-150 Hz)预测了参与评级。然而,对于努力等级,反应时间是唯一有意义的预测因子。这些结果表明,在复杂的认知任务中,高伽马可能与参与有关,但与努力无关。这些发现是朝着客观衡量评估任务中参与度的目标迈出的有希望的一步。
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来源期刊
ETS Research Report Series
ETS Research Report Series Social Sciences-Education
CiteScore
1.20
自引率
0.00%
发文量
17
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