Jan Marten Ihme

How Representational Pictures Enhance Students’ Performance and Test-Taking Pleasure in Low-Stakes Assessment

Pictures are often used in standardized educational large-scale assessment (LSA), but their impact on test parameters has received little attention up until now. Even less is known about pictures’ affective effects on students in testing (i.e., test-taking pleasure and motivation). However, such knowledge is crucial for a focused application of multiple representations in LSA. Therefore, this study investigated how adding representational pictures (RPs) to text-based item stems affects (1) item difficulty and (2) students’ test-taking pleasure. An experimental study with N = 305 schoolchildren was conducted, using 48 manipulated parallel science items (text-only vs. text-picture) in a rotated multimatrix design to realize within-subject measures. Students’ general cognitive abilities, reading abilities, and background variables were assessed to consider potential interactions between RPs’ effects and students’ performance. Students also rated their item-solving pleasure for each item. Results from item-response theory (IRT) model comparisons showed that RPs only reduced item difficulty when pictures visualized information mandatory for solving the task, while RPs substantially enhanced students’ test-taking pleasure even when they visualized optional context information. Overall, our findings suggest that RPs have a positive cognitive and affective influence on students’ performance in LSA (i.e., multimedia effect in testing) and should be considered more frequently.

Motivational factors predicting ICT literacy

The ability to use information and communication technologies (ICT) is essential for private and vocational participation in society. Although motivational facets play an important role in developing ICT knowledge and skills, only few studies assessing computer-related knowledge and skills present a comprehensive concept on these motivational facets. This article addresses this issue by presenting the construction and first validation of an ICT motivation inventory on the basis of social cognitive theory. The focus of this newly developed concept is to predict computer-related knowledge and skills. Its theoretically deduced dimensions of three ICT-related usage motives (instrumental, hedonic and social interaction), ICT-related selfefficacy, and ICT-related self-regulation were analyzed in a study assessing N = 323 German students between 16 and 27 years of age. Confirmatory factor analyses supported the assumed dimensional structure in the form of a hierarchical five-factor model. The reliability and construct validity of the measure were explored. As expected, the ICT motivation inventory dimensions were related to individual differences in ICT Literacy and relevant person characteristics (social background, need for cognition). A conceptualization and measure of an ICT motivation inventory is proposed.The factors of usage motives, self-efficacy, and self-regulation were confirmed.Correlations with ICT literacy and person characteristics were as expected.

Assessment of Computer and Information Literacy in ICILS 2013: Do Different Item Types Measure the Same Construct?.

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and information literacy in order to balance technological and information-related aspects of computer and information literacy. The item types differ in the cognitive processes and the type of knowledge they measure and in the strands and aspects of the ICILS 2013 framework they address. In this article, we explored which factor models that assume item type factors or type of knowledge factors fit the data. For the factors of the best fitting models, regression analyses on SES, frequency of computer use, self-efficacy, and gender were computed to work out the different meanings and the convergent and discriminant validity of the factors. The results show that three-dimensional models with correlated factors for item type or type of knowledge fit best. Regression analyses discover substantive implications of between-item and within-item models. The effects are discussed and an outlook is given.