Probability literacy has gained importance in educational curricula. The aim of this research was to analyse secondary education teachers' attitudes towards probability and its teaching and to examine differences across the factors of gender, academic training, and work experience. From a positivist paradigm, a quantitative methodology was used.…

To ensure the learning of mathematics, teachers must be able to analyse their students' mathematical practices when solving tasks, interpret the difficulties that students encounter, and decide how to manage students' difficulties. This competence in didactic analysis and intervention allows teachers to adapt their teaching to meet individual…

Learning a spoken language requires learning a phonological inventory and phonotactics, or the sequences of phonemes possible in the language. Laboratory investigations of phonotactic learning include tongue-twister studies that show that speech errors respect artificial phonotactic constraints, for example that /k/ never appears as a syllable…

The Karlson-Holm-Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to…

The standard regression technique for modeling binary response variables in education research is logistic regression. The odds ratios from these models are used to quantify and communicate variable effects. These effects are sometimes pooled together as in a meta-analysis. We argue that this process is problematic as odds ratios calculated from…

Propensity score methods account for selection bias in observational studies. However, the consistency of the propensity score estimators strongly depends on a correct specification of the propensity score model. Logistic regression and, with increasing popularity, machine learning tools are used to estimate propensity scores. We introduce a…

When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

In a randomized controlled trial (RCT), some subjects assigned to the treatment condition may not fully comply. Often there is interest in the effect of the treatment within the "principal stratum" of subjects who would comply if assigned to treatment. However, it is unknown which control subjects would have complied if treated and which…

Judgments of learning (JOL) are often used to assess memory monitoring at encoding. Participants study a cue-target word pair (e.g., mouse-cheese) and are asked to rate the probability of correctly recalling the target in the presence of the cue at test (e.g., mouse -?). Prior research has shown that JOL accuracy is sensitive to perceptual cues.…

In this article, we explore the use of Facebook targeted advertisements for the collection of survey data. We illustrate the potential of survey sampling and recruitment on Facebook through the example of building a large employee--employer linked data set as part of The Shift Project. We describe the workflow process of targeting, creating, and…

Background: Studies have reported difficulties in job acquisition and retention as well as unstable employment status among individuals with intellectual disabilities. Method: Chi-square, one-way ANOVA, and binary logistic regression analysis were employed to investigate the factors that affect the labour market transition of 374 individuals with…

Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…

The internal validity of observational study is often subject to debate. In this study, we define the counterfactuals as the unobserved sample and intend to quantify its relationship with the null hypothesis statistical testing (NHST). We propose the probability of a robust inference for internal validity, that is, the PIV, as a robustness index…

The first stage of a study in Québec enabled us to draw up a statistical portrait of probability teaching practices self-reported by 626 teachers at the elementary and secondary levels. For the second stage of the study, discussed here, we wanted to elaborate on some of the questionnaire answers and to discuss professional development avenues…

Over the last two decades, twenty-two states have moved away from traditional defined benefit (DB) pension systems and toward pension plan structures like the defined contribution (DC) plans now prevalent in the private sector. Others are considering such a reform as it is seen as a means of limiting future pension funding risk. It is important to…