Log data from educational assessments attract more and more attention and large-scale assessment programs have started providing log data as scientific use files. Such data generated as a by-product of computer-assisted data collection has been known as paradata in survey research. In this paper, we integrate log data from educational assessments into a taxonomy of paradata. To provide a generic framework for the analysis of log data, finite state machines are suggested. Beyond its computational value, the specific benefit of using finite state machines is achieved by separating platform-specific log events from the definition of indicators by states. Specifically, states represent filtered log data given a theoretical process model, and therefore, encode the information of log files selectively. The approach is empirically illustrated using log data of the context questionnaires of the Programme for International Student Assessment (PISA). We extracted item-level response time components from questionnaire items that were administered as item batteries with multiple questions on one screen and related them to the item responses. Finally, the taxonomy and the finite state machine approach are discussed with respect to the definition of complete log data, the verification of log data and the reproducibility of log data analyses.

A definition of basic computer skills (BCS) is proposed and the psychometric properties of a newly developed BCS scale are investigated. BCS is defined as the ability and speed of performing basic actions in graphical user interfaces of computers to access, collect, and provide information. BCS is thus considered a basic component skill of the much broader construct of ICT literacy. Data from the German PISA 2009 field trial was used to determine the factor structure of the BCS scale as well as convergent and discriminant validity. The latent factor structure underlying the BCS scale was investigated by testing confirmatory factor analysis (CFA) models for response times and responses. CFA results suggest that there is one dimension of BCS speed and BCS ability, respectively. With respect to convergent validity, practical computer knowledge and skill in digital reading had strong associations with BCS speed and ability. With respect to discriminant validity, only moderate associations were found with lower level reading skills and self-reported computer skills. Differences between BCS speed and ability and further developments of the BCS scale are discussed.

The concept ICT engagement is proposed.ICT engagement integrates metacognitive and motivational facets.The factors of interest, self-concept and social exposure were empirically confirmed.Correlations with constructs of ICT knowledge and emotion were as expected. The use of Information and Communication Technology (ICT) is of immense importance in today's digital knowledge society. As a basis for private and vocational participation in society, ICT literacy has been widely discussed in recent decades. Although motivational and metacognitive facets play an important role in developing ICT literacy and competence, studies assessing media, computer or ICT literacy often fail to present a comprehensive concept on these motivational and metacognitive facets. This article addresses this issue by integrating them into the concept of ICT engagement. Its theoretically deduced dimensions of ICT-related interest, self-concept related to the use of ICT, and social exposure to ICT were analyzed in an explorative study assessing N=445 students aged between 14 and 17years in the German federal state of Baden-Wuerttemberg. The obtained dimensional structure included the assumed factors, and suggested to distinguish a positive and a negative self-concept on using ICT as well as to separate interest in computers and interest in mobile devices factor. The ICT engagement dimensions were related to individual differences in behavioral, cognitive and emotional ICT constructs as expected.