No abstract

International large-scale assessments such as PISA or PIAAC have started to provide public or scientific use files for log data; that is, events, event-related attributes and timestamps of test-takers’ interactions with the assessment system. Log data and the process indicators derived from it can be used for many purposes. However, the intended uses and interpretations of process indicators require validation, which here means a theoretical and/or empirical justification that inferences about (latent) attributes of the test-taker’s work process are valid. This article reviews and synthesizes measurement concepts from various areas, including the standard assessment paradigm, the continuous assessment approach, the evidence-centered design (ECD) framework, and test validation. Based on this synthesis, we address the questions of how to ensure the valid interpretation of process indicators by means of an evidence-centered design of the task situation, and how to empirically challenge the intended interpretation of process indicators by developing and implementing correlational and/or experimental validation strategies. For this purpose, we explicate the process of reasoning from log data to low-level features and process indicators as the outcome of evidence identification. In this process, contextualizing information from log data is essential in order to reduce interpretative ambiguities regarding the derived process indicators. Finally, we show that empirical validation strategies can be adapted from classical approaches investigating the nomothetic span and construct representation. Two worked examples illustrate possible validation strategies for the design phase of measurements and their empirical evaluation.

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Background With digital technologies, competence assessments can provide process data, such as mouse clicks with corresponding timestamps, as additional information about the skills and strategies of test takers. However, in order to use variables generated from process data sensibly for educational purposes, their interpretation needs to be validated with regard to their intended meaning. Aims This study seeks to demonstrate how process data from an assessment of multiple document comprehension can be used to represent sourcing, which summarizes activities for the consideration of the origin and intention of documents. The investigated process variables were created according to theoretical assumptions about sourcing, and systematically tested for differences between persons, units (i.e., documents and items), and properties of the test administration. Sample The sample included 310 German university students (79.4% female), enrolled in several bachelor's or master's programmes of the social sciences and humanities. Methods Regarding the hierarchical data structure, the hypotheses were analysed with generalized linear mixed models (GLMM). Results The results mostly revealed expected differences between individuals and units. However, unexpected effects of the administered order of units and documents were detected. Conclusions The study demonstrates the theory‐informed construction of process variables from log‐files and an approach for empirical validation of their interpretation. The results suggest that students apply sourcing for different reasons, but also stress the need of further validation studies and refinements in the operationalization of the indicators investigated.

Zusammenfassung. Das Verständnis multipler Dokumente (Multiple Document Comprehension, MDC) wird als Fähigkeit verstanden, aus verschiedenen Informationsquellen eine integrierte Repräsentation eines inhaltlichen Gegenstandsbereichs zu konstruieren. Als solche ist sie sowohl für die erfolgreiche Bewältigung eines Studiums als auch für gesellschaftliche Partizipation eine wichtige Kompetenz. Bislang gibt es jedoch kein etabliertes Diagnostikum in diesem Bereich. Um diese Lücke zu schließen, wurde ein Test entwickelt, der vier zentrale kognitive Anforderungen von MDC abdeckt und auf Basis der Daten von 310 Studierenden sozial- und geisteswissenschaftlicher Fächer überprüft wurde. Die im MDC-Test gemessene Kompetenz erwies sich als eindimensional. Der MDC-Testwert wies theoriekonforme Zusammenhänge mit der Abiturnote, dem Studienabschnitt und der Leistung in einer Essay-Aufgabe auf. Insgesamt liefern die Ergebnisse empirische Belege dafür, dass der Testwert aus dem MDC-Test die fächerübergreifende Fähigkeit von Studierenden wiedergibt, multiple Dokumente zu verstehen.