This study examines the relationship between instructional quality and mathematics achievement, taking into account socioeconomic status. Data from ten European countries participating in PISA 2012 and 2022 were analysed using the framework of the Dynamic Modelling of Educational Effectiveness. In PISA 2012, instructional quality was defined by student-oriented instruction, classroom management, teacher support, disciplinary climate, and cognitive activation. The finding indicated that teacher support, disciplinary climate, and cognitive activation positively predict student achievement, but dimensions of student-oriented instruction and classroom management were negatively related in several countries. Instructional quality was captured by four dimensions in PISA 2022, namely, teacher support, disciplinary climate, cognitive activation in mathematics of encouraging mathematical thinking and of fostering reasoning. Teacher support and disciplinary climate had a positive effect on achievement, but two aspects of cognitive activation had opposite effects on achievement. SES also had significant indirect effects on achievement through various instructional quality dimensions. Across two PISA cycles, teacher support, disciplinary climate, and cognitive activation consistently benefited low-SES students, while classroom management and student-oriented instruction tended to harm their performance. These results underscore the role of instructional quality in promoting equity for disadvantaged students. Trend data from these two cycles of PISA, give an indication of specific instructional strategies that do consistently contribute to student achievement. Implications and findings are discussed in relation to the policy and practice context in different education systems.

The probabilistic index (PI), also known as the probability of superiority or the common language effect size, refers to the probability that the outcome of a randomly selected subject exceeds the outcome of another randomly selected subject, conditional on the covariate values of both subjects. This summary measure has a long history, especially for the 2-sample design where the covariate value typically refers to 1 of 2 treatments. Despite some of the attractive features of the PI, it is often not used beyond the 2-sample design. One reason is the lack of a flexible regression framework that embeds the PI and that allows the user to estimate it for more complicated designs. However, Thas, De Neve, Clement, and Ottoy (2012) recently developed such a regression framework, named probabilistic index models (PIMs). In this tutorial we provide an introduction to PIMs where we discuss several theoretical properties, motivate why we think PIMs could be useful for behavioral sciences, and illustrate how it can be used in practice using the R package pim. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

EDM event attendees are a high-risk population for substance use and associated adverse effects. The aim of this study was to examine substance use at EDM events, focusing on associations between attendance motives and substance use. Sociodemographic characteristics, event specifics, past-year use, and attendance motives were assessed through an online survey. Participants were 1345 Belgian EDM event attendees (69.44% male, M_age = 22.63, SD_age = 4.03). Ecstasy/MDMA/Molly (52.28%), other synthetic hallucinogens (53.68%), ketamine (42.13%), amphetamines (40.45%), and alkyl nitrites (poppers) (32.76%) were most frequently used at festivals/outdoor parties/raves. In nightclubs, cocaine (32.29%) was shown to be prevalent as well, while other synthetic hallucinogens (15.79%) were less often consumed. At events with a more private character, cannabis (68.88%) and magic mushrooms (66.44%) were most frequently used. Aside from alcohol (47.76%), substance use in pubs/bars was negligible. Overall enjoyment was demonstrated to be the key attendance motive, which was succeeded by those relating to music and socialization. A wide range of motives proved to be more important to users (e.g., dance, exploration, escapism, excitement, alcohol, drugs) than non-users, while some were associated with the use of particular substances. The prevalence of substance use was shown to be dependent on the specifics of the setting. Moreover, the idea of a three-dimensional classification of the most principal motives for music event attendance was supported. Finally, correlations were estimated between attendance motives and substance use as well as specific substances. Results could enable more tailored approaches in prevention and harm reduction efforts as well as event management strategies.

This study investigated the effectiveness of clinical simulations (CS) as an instructional strategy to prepare student teachers to conduct parent-teacher conferences. A pre-test/post-test study was set up in order to study the impact of online (n = 181) and face-to-face CS (n = 95) on student teachers’ parent-teacher communication competence (PTCC). Assessment of PTCC development was based on a video-based instrument and a self-efficacy scale. Results suggested that both types of CS are effective instructional strategies to improve student teachers’ PTCC. Both student teachers’ self-efficacy beliefs and situation-specific skills regarding parent-teacher communication improved. Implications and directions for future research are discussed.

We propose a measure for interaction for factorial designs that is formulated in terms of a probability similar to the effect size of the Mann–Whitney test. It is shown how asymptotic confidence intervals can be obtained for the effect size and how a statistical test can be constructed. We further show how the test is related to the test proposed by Bhapkar and Gore [Sankhya A, 36:261–272 (1974)]. The results of a simulation study indicate that the test has good power properties and illustrate when the asymptotic approximations are adequate. The effect size is demonstrated on an example dataset.