Eye tracking and early detection of confusion in digital learning environments: proof of concept
Eye tracking and early detection of confusion in digital learning environments: proof of concept
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数字学习环境中的眼动追踪和混乱的早期检测：概念验证
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
J. Lodge
中科院分区：
文献类型：
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作者：
M. Pachman;A. Arguel;Lori Lockyer;G. Kennedy;J. Lodge
研究复杂学习和问题解决过程中混淆的发生率和变化，需要先进的数字学习环境（DLEs）混淆检测方法。在这项研究中，我们试图解决这个问题，通过调查使用多种措施，包括心理生理指标和自我评级，以检测混乱的DLE。参与者以视觉数字谜题的形式接受两个本质上令人困惑的洞察力问题。他们被要求解决问题，而他们的眼睛轨迹被记录下来，这些数据与自我评价的混乱和线索回顾性口头报告进行三角测量。所有参与者对相关（即，与解决方案相关的区域）和在解决问题过程的早期阶段不相关的区域。然而，只有固定在不相关的领域呈正相关的混乱评级。此外，显著解决问题的参与者在相关和不相关领域的注视持续时间与非解决者不同。早期发现的混乱和为此目的的新兴技术的启示的重要性进行了讨论。
Research on incidence of and changes in confusion during complex learning and problem-solving calls for advanced methods of confusion detection in digital learning environments (DLEs). In this study we attempt to address this issue by investigating the use of multiple measures, including psychophysiological indicators and self-ratings, to detect confusion in DLEs. Participants were subjected to two intrinsically confusing insight problems in the form of visual digital puzzles. They were asked to solve problems while their eye trajectories were recorded and these data were triangulated with self-ratings of confusion and cued retrospective verbal reports. All participants had a significant increase in fixations on relevant (i.e., related to the solution) and not-relevant areas at an early stage of the problem-solving process. However, only fixations on not-relevant areas were positively correlated with confusion ratings. Moreover, participants who significantly solved the problem differed in their fixations duration on relevant and not-relevant areas from non-solvers. The importance of early detection of confusion and the affordances of emerging technologies for this purpose are discussed.