Sage

Cognizance, or the self-awareness individuals have of their cognitive processes, is a critical factor in adult learning and literacy, which are fundamental for personal and social development. This study aims to explore the psychometric properties of the instrument used and investigate how cognizance affects the academic achievement of new learners in literacy programs in Morocco. The research included 560 male and female learners, who were assessed using a cognizance scale designed for novice learners. The results showed significant correlations between cognizance and academic performance among these learners, indicating their ability to continue learning independently despite facing new challenges in learning to read, write, and do mathematics. This suggests that learners can overcome challenges through self-representation, self-regulation, self-adaptation, and understanding their abilities. This study has implications for improving education and developing programs to enhance cognizance and adult learning, as well as strategies to combat illiteracy. It also aims to deepen human understanding and enrich societies with knowledge and culture.

Linear models are extensively used in the analysis of clinical trials. However, required model assumptions (e.g. homoscedasticity) may not be satisfied in practice, resulting in low power of treatment–covariate interaction tests. Various interaction tests have been proposed to improve the efficiency of detecting differences in treatment–covariate interactions. Aiming to fundamentally improve the power of treatment–covariate interaction tests, for heteroscedasticity of treatment responses, we develop a model-based optimal randomization procedure, referred to as model-based Neyman allocation (MNA) in this article. The derived limiting allocation proportion indicates that the procedure MNA is a generalization of response-adaptive randomization targeting Neyman allocation (RAR-NA). In theory, we demonstrate that the procedure MNA can maximize the power of treatment–covariate interaction tests. The issue of sample size estimation is also addressed. Simulation studies show, in the framework of the heteroscedastic linear model, compared with Pocock and Simon's minimization method and RAR-NA, the procedure MNA has the greatest power of tests for both systematic effects and treatment–covariate interactions, even under model misspecification. Finally, the efficiency of the procedure MNA is illustrated by a hypothetical case study based on a real schizophrenia clinical trial.

Covariate-adjusted response adaptive (CARA) designs are effective in increasing the expected number of patients receiving superior treatment in an ongoing clinical trial, given a patient's covariate profile. There has recently been extensive research on CARA designs with parametric distributional assumptions on patient responses. However, the range of applications for such designs becomes limited in real clinical trials. Sverdlov et al. have pointed out that irrespective of a specific parametric form of the survival outcomes, their proposed CARA designs based on the exponential model provide valid statistical inference, provided the final analysis is performed using the appropriate accelerated failure time (AFT) model. In real survival trials, however, the planned primary analysis is rarely conducted using an AFT model. The proposed CARA designs are developed obviating any distributional assumptions about the survival responses, relying only on the proportional hazards assumption between the two treatment arms. To meet the multiple experimental objectives of a clinical trial, the proposed designs are developed based on an optimal allocation approach. The covariate-adjusted doubly adaptive biased coin design and the covariate-adjusted efficient-randomized adaptive design are used to randomize the patients to achieve the derived targets on expectation. These expected targets are functions of the Cox regression coefficients that are estimated sequentially with the arrival of every new patient into the trial. The merits of the proposed designs are assessed using extensive simulation studies of their operating characteristics and then have been implemented to re-design a real-life confirmatory clinical trial.

In this study, we explored the contribution of instructional strategies in nurturing critical thinking skills in Non-Formal Secondary Education (NFSE) in Tanzania. It was carried out in the Dar es Salaam Region. A qualitative approach with phenomenology design was employed and it involved 44 learners and 8 teachers making a total of 52 participants. Data were collected through interviews, focus group discussions (FGD), document analysis, and observations and were analysed thematically. The findings indicate that teachers in NFSE mostly employed the lecture method in teaching. Although problem-solving, questions and answers, group discussion, and oral presentation were viewed to contribute towards the inculcation of critical thinking, such methods were rarely employed by teachers. It was further found that teachers used questions and answers to enable learners to pass the National Examinations and most of the people who taught in NFSE did not attend teacher education that could help them possess the pedagogical knowledge and skills to nurture critical thinking in learners. The key argument in this study is that if NFSE is to inculcate critical thinking in learners, teachers need to use interactive instructional strategies. For this to take place, training programmes for teachers in pedagogical knowledge and skills are imperative.

Previous studies have shown that educational expectations of individuals with high socioeconomic status (SES) are relatively unaffected by low academic performance, a phenomenon called “sticky expectations.” However, this result might be biased by endogeneity and reverse causality between academic achievement and educational expectations. Using data from the Trends in International Mathematics and Science Study from 11 countries with a strict school-entry rule and building on the well-established finding that children born in the months before the school-entry cutoff underperform at school, we use birth month as an instrument to identify the causal effect of early academic achievement on parents' expectations of university completion by parental education. Our findings based on the instrumental variable (IV) regression show that the moderation of social origin in the relationship between children's performance and parental expectations is moderately overestimated in cross-sectional data. Nonetheless, the stickiness of high-SES parental expectations is confirmed in the IV model, proving that parental expectations are less affected by children's early achievement when the parents are highly educated.

Abstract Background: Young female athletes may have higher rates of overuse injuries and sport specialization than male athletes.

Abstract Objective: As highlighted in Australia's Productivity Commission Inquiry into mental health, subgroups of individuals are

The Dunning-Kruger effect describes how poor performers overestimate their abilities while top performers underestimate their abilities. This study explores whether this effect explains the ineffectiveness of cross-cutting discussions in reducing affective polarization. We propose a moderated mediation model in which the relationship between cross-cutting discussion (wave 1) and affective polarization (wave 2) is mediated by oppositional responses to disagreements, and this indirect relationship, specifically between cross-cutting discussion and opposition responses, is moderated by political overconfidence. Analyzing panel data from a two-wave online survey, the results suggest that the Dunning-Kruger effect is widespread in political knowledge and influences social media users' behaviors and attitudes. Specifically, for example, those who are more overconfident engage in cross-cutting discussions, have more oppositional responses (e.g., posting criticisms or clicking “dislike”), and thus become more affectively polarized. This suggests that correcting the public's perceived bias about their level of political knowledge may help reduce affective polarization.

The advancement of artificial intelligence (AI) has expanded the potential for human-machine communication and collaboration in complex contexts, necessitating AI to exhibit human-like behavior in order to align with its human counterpart. Consequently, understanding human behavioral traits becomes advantageous for developing AI agents that resemble humans. This study investigated how individuals process visual information from others to inform the future design of intelligent vision systems. Through four experiments, participants were tasked with assessing whether a given number corresponds to the number of balls while manipulating the gaze direction of an avatar by averting its eyes or altering its head orientation. The results indicate that participant response times were influenced regardless of the avatar's gaze direction. Specifically, when the avatar was positioned with its back facing the balls, any disparity in participant performance across different conditions is eliminated. These findings suggest that implicit level-1 visual perspective-taking may not primarily rely on gaze direction but rather on perceiving affordances within the environment. Such insights contribute to a deeper understanding of cognitive mechanisms underlying level-1 visual perspective-taking and can serve as a theoretical foundation for advancing AI vision algorithms in human-machine communication and collaboration.

Abstract Background While the Liaison Committee on Medical Education emphasizes the teaching of cultural competence in medical