Do people think about genetic inheritance as a deterministic or probabilistic process? Do adults display systematic biases when reasoning about genetic inheritance? Knowing how adults think about genetic inheritance is valuable, both for understanding the developmental endpoint of these concepts and for identifying biases that persist even after…

One expected outcome of physics instruction is for students to be capable of relating physical concepts to multiple mathematical representations. In quantum mechanics (QM), students are asked to work across multiple symbolic notations, including some they have not previously encountered. To investigate student understanding of the relationships…

Purpose: Children with developmental language disorder (DLD) tend to interpret noncanonical sentences like passives using event probability (EP) information regardless of structure (e.g., by interpreting "The dog was chased by the squirrel" as "The dog chased the squirrel"). Verbs are a major source of EP information in adults…

Procedural learning is key to optimal skill learning and is essential for functioning in everyday life. The findings of previous studies are contradictory regarding whether procedural learning can be modified by prioritizing speed or accuracy during learning. The conflicting results may be due to the fact that procedural learning is a multifaceted…

This study investigates a range of non-normative ideas that pre-service teachers (PSTs) employ in reasoning about sampling variability. This issue was studied in the context of a content course on statistics and probability for pre-service middle grade teachers at a Midwestern American university. Analysis of seven PSTs' video and screen records…

The ability to relate physical concepts and phenomena to multiple mathematical representations--and to move fluidly between these representations--is a critical outcome expected of physics instruction. In upper-division quantum mechanics, students must work with multiple symbolic notations, including some that they have not previously encountered.…

To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…

Help-seeking is uncommon among college students with substance use concerns. Perceived access to services is associated with greater help-seeking behavior. This study identifies substance use-related risk factors associated with awareness of campus counseling services. College students aged 18 to 25 (N = 995) self-administered a web-based survey,…

This study aimed to examine the impact of game and simulation-based learning environments on the success, concept knowledge, and attitude of prospective teachers regarding probability. The sample of the study consisted of 94 prospective mathematics teachers. The study was conducted in accordance with the quasi-experimental study design and the…

Concerns about the influence of misconceptions, culture and social setting on probabilistic reasoning of teacher trainees led to a study in this area to explore the reasoning of preservice teachers from a college of education in Ghana. This study investigates preservice teachers' misconceptions and difficulties in probabilistic problems solving…

Proportional reasoning failures seem to constitute most errors in probabilistic reasoning, yet there is little empirical evidence about its role for attaining probabilistic knowledge and how to effectively intervene with students who have less proportional reasoning skills. We examined the contributions of students' proportional reasoning skill…

Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…

Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when…

In this article, we review factors that are associated with science, technology, engineering, and mathematics (STEM) achievement and describe the development of the Predictors of Black Outcomes in STEM Survey (PBOSS). We retain a well-fitted three-factor model (engagement, continuity, and guiding functions) and find that the PBOSS scores are…

Several recent studies have employed item response theory (IRT) to rank incorrect responses to commonly used research-based multiple-choice assessments. These studies use Bock's nominal response model (NRM) for applying IRT to categorical (nondichotomous) data, but the response rankings only utilize half of the parameters estimated by the model.…