A priori assumptions about specific behavior in test items can be used to process log data in a rule-based fashion to identify the behavior of interest. In this study, we demonstrate such a top-down approach and created a process indicator to represent what type of information processing (flimsy, breadth-first, satisficing, sampling, laborious) adults exhibit when searching online for information. We examined how often the predefined patterns occurred for a particular task, how consistently they occurred within individuals, and whether they explained task success beyond individual background variables (age, educational attainment, gender) and information processing skills (reading and evaluation skills). We analyzed the result and log file data of ten countries that participated in the Programme for the International Assessment of Adult Competencies (PIAAC). The information processing behaviors were derived for two items that simulated a web search environment. Their explanatory value for task success was investigated with generalized linear mixed models. The results showed item-specific differences in how frequently specific information processing patterns occurred, with a tendency of individuals not to settle on a single behavior across items. The patterns explained task success beyond reading and evaluation skills, with differences across items as to which patterns were most effective for solving a task correctly. The patterns even partially explained age-related differences. Rule-based process indicators have their strengths and weaknesses. Although dependent on the clarity and precision of a predefined rule, they allow for a targeted examination of behaviors of interest and can potentially support educational intervention during a test session. Concerning adults’ digital competencies, our study suggests that the effective use of online information is not inherently based on demographic factors but mediated by central skills of lifelong learning and information processing strategies.

中文翻译：

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基于规则的信息处理过程指标解释了 PIAAC 网络搜索任务中的性能差异

关于测试项目中特定行为的先验假设可用于以基于规则的方式处理日志数据，以识别感兴趣的行为。在这项研究中，我们展示了这种自上而下的方法，并创建了一个过程指标来表示成人在网上搜索信息时表现出的信息处理类型（脆弱、广度优先、满意、抽样、费力）。我们检查了特定任务的预定义模式出现的频率、它们在个体中出现的一致性，以及它们是否能在个体背景变量（年龄、受教育程度、性别）和信息处理技能（阅读和评估技能）之外解释任务成功。我们分析了参与国际成人能力评估计划 (PIAAC) 的十个国家的结果和日志文件数据。信息处理行为是针对模拟网络搜索环境的两个项目得出的。使用广义线性混合模型研究了它们对任务成功的解释值。结果显示特定信息处理模式发生频率的特定项目差异，个人倾向于不在项目之间解决单一行为。这些模式解释了阅读和评估技能之外的任务成功，在哪些模式对正确解决任务最有效方面存在差异。这些模式甚至部分解释了与年龄相关的差异。基于规则的过程指标有其优点和缺点。虽然依赖于预定义规则的清晰度和精确度，但它们允许对感兴趣的行为进行有针对性的检查，并可能支持测试期间的教育干预。关于成年人的数字能力，我们的研究表明，在线信息的有效使用并非固有地基于人口因素，而是受终身学习和信息处理策略的核心技能的影响。