Large-scale Assessments in Education (May 2023)

Rule-based process indicators of information processing explain performance differences in PIAAC web search tasks

  • Carolin Hahnel,
  • Ulf Kroehne,
  • Frank Goldhammer

DOI
https://doi.org/10.1186/s40536-023-00169-5
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 25

Abstract

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Abstract Background 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). Methods 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. Results 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. Conclusions 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.

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