关注和不关注任务相关信息的读者如何扫描:眼动追踪研究

Jing Chen , Lu Zhang , Quan Lu
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引用次数: 0

摘要

目的所有读者在进行任务阅读时,关注与任务相关的信息应该是最优先考虑的。对专心阅读和不专心阅读的扫描行为进行研究,为研究顺序认知过程提供了新的思路,但这方面的研究很少。本研究在全局尺度上研究了它们的全局模式,涉及到扫描路径的整个长度,并进一步比较了局部战术、局部策略和局部尺度上的局部策略转换,涉及到扫描路径的孤立区域。设计/方法/方法在眼动追踪实验中设计了一个常规风格的阅读系统,其界面上有问题、导航和文本区域,并设计了两种类型的任务,即事实发现(FF)和内容理解(CU)。根据对任务相关段落的注视时间,将24名参与者分为注意(AR)和不注意(IAR)两组。全局序列分析算法Needleman-Wunsch被用于揭示整个扫描路径(whole-scanpaths)长度的全局模式。采用与频繁子扫描路径相关的局部序列分析方法,提取针对读者和任务的局部策略。通过对局部策略进行分类,对局部策略进行编码识别。局部策略转换被进一步确定为在开始、中间和结束阶段频繁的局部策略序列。尽管两组没有全局模式,但AR的全扫描路径与IAR有显著差异。局部策略分为定位信息策略(LI)、文本相关性评估与验证策略(EVR)、导航启发式策略(NH)、综合信息策略(SI)和语境线索策略(CC)。AR在两项任务中都应用了所有类型,而IAR只应用了两种类型,并坚持使用EVR。在此基础上,提出了两种局部战略转换类型:综合探索型和迭代内容评估型。AR在FF任务中采用前者的线性特征,在CU任务中采用螺旋特征,而IAR在两个任务中都采用后者。本研究从注意和不注意到任务相关信息的角度推进了动态认知加工的认识。为获取全局模式、局部策略、局部策略和局部策略转换提供了客观的分析视角,为读者自动分类提供了新的思路。研究结果还为改进阅读系统设计和培养读者提供了详细而有价值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How readers attentive and inattentive to task-related information scan: An eye-tracking study

Purpose

Attentive to task-related information should be the highest priority for all readers engaged in task-reading. Investigating the scanning behaviors of attentive versus inattentive readers shed new insights into the sequential cognitive processes, but it has seldom been studied. This study investigates their global patterns on a global scale, pertaining to the whole length of scanpaths, and further compares local tactics, local strategies, and local strategy transitions on a local scale, related to the isolated regions of scanpath.

Design/methodology/approach

A regular style reading system with the question, navigating, and text areas on its interface, and two types of task, namely fact-finding (FF) and content understanding (CU), were designed in an eye-tracking experiment. 24 participants were placed into attentive (AR) or inattentive (IAR) readers groups according to their fixation duration on task-related paragraphs. A global sequence analysis algorithm, Needleman-Wunsch, was applied to uncover global patterns across the whole length of scanpaths (whole-scanpaths). A local sequence analysis method related to frequent sub-scanpaths was adopted to extract local tactics specific to the reader and task. Coding was performed to identify local strategies by classifying local tactics. A local strategy transition was further identified as a sequence of frequent local strategies at the beginning, middle, and ending phases.

Findings

Whole-scanpaths of AR significantly differed from those of IAR, despite the absence of global patterns for each group. Five types of local strategy were identified, namely locating information (LI), evaluating and verifying text relevance (EVR), navigation heuristics (NH), synthesizing information (SI), and contextual clues (CC). AR applied all types in both tasks, whereas IAR applied only two types and stuck with EVR. Furthermore, two types of local strategy transition were identified: comprehensive exploration and iterative content evaluation. AR employed the former with the linear feature in FF and the spiral feature in CU, while IAR employed the latter in both tasks.

Originality

This study advances the knowledge of dynamic cognitive processing from an attentive and inattentive to task-related information perspective. An objective analysis perspective for obtaining global patterns, local tactics, local strategies, and local strategy transitions is provided, then it can provide new insights into automatically classifying readers. The results also generate detailed and valuable guidance for improving reading system design and training readers.
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来源期刊
Data and information management
Data and information management Management Information Systems, Library and Information Sciences
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