Election forecasting has become the centerpiece of media coverage of elections. Yet for all the attention paid to forecasting, public understanding remains low and increasingly distrustful. We can improve citizen knowledge and comprehension and increase student engagement by giving students the opportunity to develop their own election forecast.…

Scaled analog modeling ("sandbox modeling") allows deformational processes, such as the development of a mountain belt, to be observed in real time in a classroom setting. However, the actual learning gains from exposure to sandbox modeling in geology courses in higher education settings have not been explicitly studied. We begin to…

Objective: Investigate whether psychosocial risk in the childhood family environment moderates the relationship between childhood socioeconomic status (SES) and sleep, and the relationship between childhood SES and ambulatory blood pressure (ABP) in college students, two factors that are linked to future risk for cardiovascular disease.…

Previous studies on value-driven attentional capture (VDAC) have demonstrated that the uncertainty of reward value modulates attentional allocation via associative learning. However, it is unclear whether such attentional exploration is executed based on the amount of potential reward information available for refining value prediction or the…

The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…

The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…

This article argues that Agent-Based Modelling, owing to its capabilities and methodology, has a distinctive contribution to make to delivering coherent social science prediction. The argument has four parts. The first identifies key elements of social science prediction induced from real research across disciplines, thus avoiding a straw person…

In the present study, we designed a dynamic measure to assess emerging morphological awareness in Chinese children and examined its concurrent and longitudinal relations with character recognition. The initial question of the dynamic assessment of morphological awareness (DAMA) task asked children to judge whether the first morphemes in a pair of…

This article presents a conceptual replication of Hashimoto and Egbert (https://doi.org/10.1111/lang.12353), a study that featured multivariate models where lexical sophistication variables accounted for word difficulty (yes-no recognition) better than frequency alone among learners of English as a second or foreign language from North America.…

The simple average of student growth scores is often used in accountability systems, but it can be problematic for decision making. When computed using a small/moderate number of students, it can be sensitive to the sample, resulting in inaccurate representations of growth of the students, low year-to-year stability, and inequities for…

The purpose of this quantitative correlational-predictive study was to determine if and to what extent teachers' Leader-Member Exchange (LMX) and organizational citizenship behavior (OCB) individually and combined predict teachers' Class Reading Growth in grades K-5 at a school district in a southeastern coastal state. The theoretical foundations…

Questionnaire designers use readability measures to ensure that questions can be understood by the target population. The most common measure is the Flesch-Kincaid Grade level, but other formulas exist. This article compares six different readability measures across 150 questions in a self-administered questionnaire, finding notable variation in…

Learning analytics (LA) is considered a promising field of study as it's helping to improve learning and the context in which it occurs. A learner's performance can be defined as how well students are learning in terms of knowledge and skills development and can be analyzed based on students' outcomes and engagement in the course. We have…

The Dunning-Kruger effect refers to low performing individuals' tendency to overestimate their performance. The metacognitive deficit is thought to be responsible for this inflated self-assessment observed among the low performers. The present study investigated whether the Dunning-Kruger effect occurs in college students during online distance…

Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…