The Perceptions of Success Inventory for Beginning Teachers: Measuring its psychometric properties

This study investigated the construction and evaluation of an instrument called the Perceptions of Success Inventory for Beginning Teachers (PSI-BT) intended to measure factors documented in research that contribute to beginning teachers’ perceptions of success. The PSI-BT was found to assess the following factors using exploratory factor analysis: (1) Administrative Support, (2) Classroom Climate, (3) Mentor Support, (4) Colleague and Instructional Resource Support, (5) Commitment, and (6) Assignment and Workload. Internal reliability, content validity, and concurrent validity were also measured in the validation process. Our findings suggest that the PSI-BT provides a reliable and valid instrument that can provide schools with valuable feedback to ensure the success of their beginning teachers.     

In these uncertain times: Educators build cultural awareness through planned international experiences

This narrative inquiry explored the effectiveness of planned international experiences in promoting cultural awareness, understanding and appreciation among American educators. Participating educators (n=12) were immersed in foreign cultures for 2–3 weeks during three different summers. To document the effectiveness of cultural immersion, participants completed pre- and post-visit surveys. Pre-visit data showed lack of cultural awareness. After the visit, however, participants had gained broader awareness, understanding and appreciation of host cultures such that familiar cultural practices were rarely used as the only point of reference. Follow-up interviews showed possible sustained acculturation.     

Genetic and environmental influences on reading and listening comprehension

We report preliminary behaviour genetic analyses of reading and listening comprehension from The Colorado Learning Disabilities Research Center. Although the twin sample with these new measures is still of limited size, we find substantial, and significant, genetic influences on individual differences in both reading and listening comprehension. In addition, word recognition and listening comprehension each accounted for significant independent genetic influences on reading comprehension. Together, they accounted for all the genetic influence on reading comprehension, indicating a largely genetic basis for the ‘simple model’ of individual differences in reading comprehension proposed by Hoover and Gough (1990) .     

One and One is Sometimes Three in Small Group Mathematics Learning

In recent years, Mathematics teaching has been confronted by demands for higher standards and better pupil achievement in several parts of the world. Researchers have suggested the shift from teacher‐centred instruction towards more active participatory learning methods as one way to improve the quality of the teaching and learning process. The tension between whole‐class teaching versus small group learning in Mathematics has been particularly apparent in many education systems. This article analyses the development of Mathematics teaching by asking whether small group learning is an effective arrangement in teaching school Mathematics. We conclude that although there is no unanimity about the affects of small group learning on student achievement in school Mathematics, it seems that it produces at least equal academic outcomes among all students compared to more traditional methods of instruction. Working in pairs is a particularly effective form of learning Mathematics and that small groups are beneficial for developing mathematical problem‐solving skills. We also conclude that the present educational policies and increased quality assurance structures in many countries conflict, or are not consistent with scientific‐professional thinking and research on the teaching of Mathematics.     

The representation and attainment of students with dyslexia in UK higher education

Using a database of allstudents in higher education in the UK in1995–1996, students with dyslexia and those withno reported disability were compared in termsof demographic properties, programmes of studyand academic attainment. Students with dyslexiaconstituted 0.42% of all students resident inthe UK. Their representation varied with age,gender, ethnicity and entrance qualificationsand with their level, mode and subject ofstudy. Students with dyslexia were more likelyto withdraw during their first year of studyand were less likely to complete theirprogrammes of study, although with appropriatesupport the completion rate of students withdyslexia can match that of students with nodisabilities. In addition, students withdyslexia who completed first-degree programmestended to gain a poorer class of honours thanstudents with no reported disability, but 40%obtained first-class or upper second-classhonours. In short, dyslexia may havedeleterious consequences for progression,completion and achievement in higher education,but it is by no means incompatible with a highlevel of success, given appropriate commitmenton the part of the students and appropriateresources on the part of their institution.     

FRP Retrofitted RC Slabs Using Finite Difference Model

Current guidelines recommend using single-degree-of-freedom(SDOF) method for dynamic analysis of reinforced concretec (RC) structures against blast loads, which is not suitable for retrofitted members. Thus, a finite difference procedure developed in another study was used to accurately and efficiently analyze the dynamic response of fibre reinforced polymer (FRP) plated members under blast loads. It can accommodate changes in the mechanical properties of a member's cross section along its length and through its depth in each time step, making it possible to directly incorporate both strain rate effects (which will vary along the length and depth of a member) and non-uniform member loading to solve the partial differential equation of motion. The accuracy of the proposed method was validated in part using data from field blast testing. The finite difference procedure is implemented easily and enables accurate predictions of FRP-plated-member response.     

Testing Measurement Invariance Across Unobserved Groups: The Role of Covariates in Factor Mixture Modeling

Factor mixture modeling (FMM) has been increasingly used to investigate unobserved population heterogeneity. This study examined the issue of covariate effects with FMM in the context of measurement invariance testing. Specifically, the impact of excluding and misspecifying covariate effects on measurement invariance testing and class enumeration was investigated via Monte Carlo simulations. Data were generated based on FMM models with (1) a zero covariate effect, (2) a covariate effect on the latent class variable, and (3) covariate effects on both the latent class variable and the factor. For each population model, different analysis models that excluded or misspecified covariate effects were fitted. Results highlighted the importance of including proper covariates in measurement invariance testing and evidenced the utility of a model comparison approach in searching for the correct specification of covariate effects and the level of measurement invariance. This approach was demonstrated using an empirical data set. Implications for methodological and applied research are discussed.     

Latent Variable Modeling and Adaptive Testing for Experimental Cognitive Psychopathology Research

The adaptation of experimental cognitive tasks into measures that can be used to quantify neurocognitive outcomes in translational studies and clinical trials has become a key component of the strategy to address psychiatric and neurological disorders. Unfortunately, while most experimental cognitive tests have strong theoretical bases, they can have poor psychometric properties, leaving them vulnerable to measurement challenges that undermine their use in applied settings. Item response theory–based computerized adaptive testing has been proposed as a solution but has been limited in experimental and translational research due to its large sample requirements. We present a generalized latent variable model that, when combined with strong parametric assumptions based on mathematical cognitive models, permits the use of adaptive testing without large samples or the need to precalibrate item parameters. The approach is demonstrated using data from a common measure of working memory—the N-back task—collected across a diverse sample of participants. After evaluating dimensionality and model fit, we conducted a simulation study to compare adaptive versus nonadaptive testing. Computerized adaptive testing either made the task 36% more efficient or score estimates 23% more precise, when compared to nonadaptive testing. This proof-of-concept study demonstrates that latent variable modeling and adaptive testing can be used in experimental cognitive testing even with relatively small samples. Adaptive testing has the potential to improve the impact and replicability of findings from translational studies and clinical trials that use experimental cognitive tasks as outcome measures.