When facing many options, we narrow down our focus to very few of them. Although behaviors like this can be a sign of heuristics, they can actually be optimal under limited cognitive resources. Here, we study the problem of how to optimally allocate limited sampling time to multiple options, modeled as accumulators of noisy evidence, to determine…

Purpose: Evaluating emergency preparedness exercises is crucial for assessing enhanced knowledge, facilitating learning and implementing knowledge in organizations. The cognitive process of motivation for action is a precursor for action, coping behavior and individual learning. This study aims to focus on how guided evaluation of emergency…

The notion of children's working theories is an overarching outcome of Aotearoa New Zealand's early childhood curriculum document "Te Whariki." An ever-growing base of research and literature is available about the working theories children hold and ways that teachers might support working theory development. In this article, I draw on…

The adoption of virtual learning environments (VLEs) in education has grown significantly due to their potential to enhance learning. Effective learning in VLEs depends on managing cognitive load and sustaining motivation, particularly for complex tasks like developing teachers' professional vision -- the ability to notice and interpret classroom…

This book provides a comprehensive examination of teacher design thinking and practice, structured across ten chapters that can be read either as a complete narrative or as standalone works. The content is organized into three parts--Part 1: Foundations and frameworks (Chapters 1-3)--Establishes the theoretical groundwork for understanding…

Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…

A key goal in cognitive training research is understanding whether cognitive training enhances general cognitive capacity or provides only task-specific improvements. Here, we developed a quantitative model for describing the temporal dynamics of these two processes. We analyzed data from 1300 children enrolled in an 8 week working memory training…

Event-based prospective memory (PM) tasks require individuals to remember to perform a previously planned action when they encounter a specific event. Often, the natural environments in which PM tasks occur are embedded are constantly changing, requiring humans to adapt by learning. We examine one such adaptation by integrating PM target learning…

Background: This study breaks new ground by presenting a new, more sophisticated model of learning engagement that goes beyond the current state of the art embodied in the widely used Affective-Behavioral-Cognitive (ABC) model. This work synthesizes and builds upon neglected lines of research in the structure of affective engagement. It also…

Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

Noticing students' mathematical thinking is foundational to responsive teaching. However, it is cognitively demanding because teachers must attend to important details in students' strategies, interpret their understandings, and decide on next steps--all in the moment. This article introduces the Big Ideas of Measurement (BIM), a research-based…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

The phenomenon of misconception and poor conceptual understanding is a problem that often occurs in science learning, not least in physics learning. Learning models that specifically aim to improve conceptual understanding and remediate misconceptions are not widely available. This study aims to determine the effect of the CCBL model in improving…

Student performance is affected by their knowledge which changes dynamically over time. Therefore, employing recurrent neural networks (RNN), which are known to be very good in dynamic time series prediction, can be a suitable approach for student performance prediction. We propose such a neural network architecture containing two modules: (i) a…

Years and Centuries are the measurement units used to quantify a longer time duration, while subtraction is the operation required to determine the duration based on two given time points. However, subtraction of time is a difficult skill to be mastered by many elementary students. To identify the root cause of the student's failure in performing…