We develop a structural after measurement (SAM) method for structural equation models (SEMs) that accommodates missing data. The results show that the proposed SAM missing data estimator outperforms conventional full information (FI) estimators in terms of convergence, bias, and root-mean-square-error in small-to-moderate samples or large samples…

Teaching statistics to generalist students oriented toward a profession, rather than academic merits, may be challenging. As statistics courses also tend to have a low student appeal, tailoring a course toward this type of audience is demanding. Framed within the theory of statistical thinking and literacy, this article shows how an investigative…

Nontraditional grading methods have recently become more common, and as with any large pedagogical shift, there are a number of questions to consider when applying a new grading scheme to a course. This article summarizes four types of nontraditional grading and shares experiences from the authors who have applied them to a variety of courses in…

This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…

Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…

To this date, few standardized tests measuring students' performance with regards to statistics exist. Only four tests have been proposed for college or university students. The goal of the present study is to investigate these tests. University professors or instructors experienced in teaching statistics were asked to list the concepts they think…

Statistical thinking is essential to understanding the nature of scientific results as a consumer. Statistical thinking also facilitates thinking like a scientist. Instead of emphasizing a "correct" procedure for data analysis and its outcome, statistical thinking focuses on the process of data analysis. This article reviews frequentist…

Seeking to leverage students' interests into mathematical tasks and noticing how their students excitedly discussed the NCAA's Division 1-A football rankings every year, the authors devised a mathematical modeling task in which students could use mathematics to justify their rankings. The task takes students on a journey to consider the complexity…

Problem solving is considered an essential ability for becoming an expert in physics, and individualized feedback on the structure of problem-solving processes is a key component to support students in developing this ability. Problem-solving processes consist of multiple elements whose order forms the sequential structure of these processes.…

Investigators often rely on the proportion of correct responses in an assessment when describing the impact of early mathematics interventions on child outcomes. Here, we propose a shift in focus to the relative sophistication of problem-solving strategies and offer methodological guidance to researchers interested in working with strategies. We…

The School of Engineering of the Polytechnic of Porto (ISEP) has embraced the DrIVE-MATH project, since September 2017. Active-learning (AL) techniques were implemented in several Math courses, namely Linear Algebra and Analytic Geometry, Probability and Statistics, Statistical Models, Computational Mathematics, and Differential and Integral…

Assessment is necessary, but difficult, in statistics education. Multiple choice assessments are common, particularly for research purposes. Open-ended assessments may be more adept at revealing student understanding, but ensuring their validity can be difficult. The study presented here examines differences in student descriptions of histograms…

Virtual reality simulation has had a significant impact on training of psychomotor surgical skills, yet there is still a lack of work on its use to teach surgical decision making. This is particularly noteworthy given the recognized importance of decision making in achieving positive surgical outcomes. With the objective of filling this gap, we…

The National Council of Teachers of Mathematics (NCTM, 2014) highlights that effective teaching practices promote students' reasoning and sense making through various problem-solving strategies. Rather than telling students what to do and how to solve problems, teachers are expected to engage learners in accessible real-life problem situations…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…