Mapping relational structure in spatial reasoning

Three experiments investigated whether the similarity of relational structures influences the interpretation of spatial representations. Adults were shown diagrams of hand gestures paired with simple statements and asked to judge the meaning of new gestures. In Experiment 1 the gestures were paired with active declarative statements. In Experiment 2, the gestures were paired with conjunctive and disjunctive relations. Experiment 3 used statements similar to those used in Experiment 1, but eliminated the initial object-to-object mapping provided in Experiments 1 and 2. In all three experiments, most participants chose an interpretation that set up a parallel relational structure between the gesture and its meaning: spatial elements were paired with conceptual elements and spatial relations were paired with conceptual relations. These results are consistent with the hypothesis that similarity of relational structures influences spatial reasoning, and have implications for analogical reasoning, diagrammatic reasoning, and language processing.     

The Experiences in Close Relationships Scale-Revised Child version: Reliability and structural validity of the Polish adaptation

The Experiences in Close Relationships Scale-Revised Child version (ECR-RC) is a self-report questionnaire measuring attachment anxiety and attachment avoidance. The aim of this study was to validate a Polish version of the ECR-RC, assess its reliability and factorial structure based on the results obtained from a community sample of 277 children aged between 10 and 13. The results of confirmatory factor analyses revealed a two-factor structure of the Polish ECR-RC that showed an adequate internal structure and consistency. Moreover, a model fit of an abbreviated, 12-item version and a three-factor structure were tested. Overall, the results of this study offer a valid and reliable tool for assessing attachment anxiety and avoidance in Polish-speaking children.     

Factor structure of the CNS Vital Signs computerized cognitive battery in youth with neurological diagnoses

Computerized cognitive batteries, such as CNS Vital Signs (CNSVS), can provide valuable information in clinical and research settings. However, psychometric properties, especially in children and adolescents, remain relatively understudied. The aim of this study was to investigate the factor structure of CNSVS in children and adolescents with neurological diagnoses.

Participants with neurological diagnoses (N = 280) age 7–19 years were assessed as part of their clinical care at a tertiary hospital. All participants received the full CNSVS computerized cognitive battery, which contains seven subtests designed to measure attention, executive functioning, psychomotor speed, and memory. Principal components analyses were used to examine factor structure.

Scores from CNSVS subtests loaded onto a three-component solution and accounted for 46% of the variance. The three components were deemed to best represent (1) speed, (2) memory, and (3) inhibition, with subtest scores loading differently than the original 11 primary and secondary domain scores would have suggested.

Although the CNSVS program generates numerous primary and secondary domain scores, a three-component solution represents a more parsimonious approach to interpreting performance on the CNSVS in youth with neurological diagnoses. Confirmation of this factor solution in other samples is warranted.     

A diagnostic tree model for polytomous responses with multiple strategies

Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students’ problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students’ partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM.