The process of turning a doctoral student into an independent researcher is usually guided by a professor. In this work, the supervisor-supervisee relationship is represented by a scheme inspired by Michaelis-Menten kinetics, which has been used to determine the rate of enzyme-catalysed reactions. Here, the time evolution of the number of…

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…

When remembering over the short-term, long-term knowledge has a large effect on the number of correctly recalled items and little impact on memory for order. This is true, for example, when the effects of semantic category are examined. Contrary to what these findings suggest, Poirier et al. in 2015 proposed that memory for order relies on 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…

Immigrant college students often encounter daunting tasks and obstacles when exploring career paths, seeking employment and experiential learning opportunities aligned with their interests within the dominant US higher education structure. Considering that there is a career services and development literature gap on immigrant students (who…

The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…

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,…

Many graduate public affairs programs offer both residential and online options for students. One of the challenges for multi-format programs is creating a sense of belonging among online students who may never set foot on campus. In 2017, the MPA program at the University of North Carolina at Chapel Hill developed an "immersion" course…

Early math skills predict later academic achievement and are of critical importance in preschool. There also are discrepancies in early math skills of preschoolers with disabilities compared with their typically developing peers. We used an experimental single-case research design, multiple probe across skills, to investigate the effectiveness of…

As the drive to move from traditional face-to-face classroom learning to e-learning is ever in demand, the knowledge corpus exposed to students can be overwhelming because there is a need to automate certain functions of the e-learning framework. One of these functions is the course recommendation feature. Course recommendations help students save…

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…

This article presents a conceptual replication of Hashimoto and Egbert (https://doi-org.bibliotheek.ehb.be/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.…

How can novel AI techniques be made and put to use in the library? Combining methods from data and library science, this article focuses on Natural Language Processing technologies, especially in national libraries. It explains how the National Library of Sweden's collections enabled the development of a new BERT language model for Swedish. It…

The randomized response technique (RRT) is an effective method designed to obtain the stigmatized information from respondents while assuring the privacy. In this study, we propose a new two-stage RRT model to estimate the prevalence of sensitive attribute ([pi]). A simulation study shows that the empirical mean and variance of proposed estimator…

When teaching fractions, teachers make instructional decisions about if, when, and how to use the many different types of fraction models and manipulatives. In this study, we sought insights into their pedagogical reasoning with fraction representations via their preferences, both for solving tasks themselves and for teaching (in general and for…