This paper reports on an exploratory study about probabilistic intuition in learning mathematics for decision-making. The analysis was carried out on a group of high school students in relation to their probabilistic intuition in problem-solving, after performing playful learning activities on a simulation platform specifically designed for this…

Purpose: Clinical supervision is a crucial workplace practice for professional learning and development. Research is needed to investigate in detail what happens in supervision to understand how this practice contributes to learning. This paper aims to examine how professionals work with knowledge and navigate epistemic challenges in working with…

Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…

Recently, the field of adaptive learning has significantly attracted researchers' interest. Learning path adaptation problem (LPA) is one of the most challenging problems within this field. It is also a well-known combinatorial optimization problem, its main target is the knowledge resources sequencing offered to a specific learner with a specific…

Research carried out through the last 20 years gave us undeniable evidence that to learn anything we need to be active participants, not passive observers. One of the important aspects of learning physics is constructing explanations of physical phenomena. To support and guide students toward constructing their explanations, teachers need to be…

Resonance is a crucial concept in Organic Chemistry that enables both deriving chemical properties from molecular structures and predicting reactions by considering electron density distribution. Despite its importance for problem-solving and learning success, learners encounter various difficulties with this concept. Although prior research…

In agreement with the main tenets of the anthropological theory of the didactic (ATD), this study uncovers dependencies between what students can learn, the established curriculum and the current state of mathematicians' mathematics ('scholarly mathematics'). One main result is that the mathematics taught, too often taken for granted by curriculum…

Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…

The core function of science education is to equip students with scientific literacy, enabling them to understand complex environmental challenges and actively engage in proenvironmental behaviors. Therefore, understanding students' conceptions of environmental education is crucial for advancing environmental education. In this study, we explored…

Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…

Mathematics intervention research has established several effective interventions for building accuracy and fluency of math fact computation, as well as components that may improve student learning rates. While several evidence-based interventions promoting math fact accuracy and fluency exist, further work is needed to determine additional…

"Productive Struggle: How Artificial Intelligence is Changing Learning, Effort, and Youth Development in Education," recently released by Bellwether, considers the role of GenAI in education. It proposes a criterion for evaluating these new technologies' impact on student learning: When does ease afforded by GenAI enable greater…

This research examines the application of students' computational thinking (CT) in solving numerical method problems through computer software. Data collection involved observing their learning process and conducting tests to evaluate their CT skills within the context of the root approach material using Newton-Raphson method. The results indicate…

Contribution: This study uses a qualitative research method to analyze interviews where participants simplified an electric circuit while explaining their thought process. Background: Rearranging circuit diagrams is a fundamental skill in electrical and electronic engineering, yet students can struggle with unfamiliar configurations. Current…

Emotions play a crucial role in the learning process, yet there is a scarcity of studies examining emotion dynamics in problem-solving with fine-grained data and advanced tools. This study addresses this gap by investigating the emotional trajectories during self-regulated learning (SRL) phases (i.e., forethought, performance, and self-reflection)…