Due to severe time constraints, goalkeepers regularly face the challenging task to make decisions within just a few hundred milliseconds. A key finding of anticipation research is that experts outperform novices by using advanced cues which can be derived from either kinematic or contextual information. Yet, how context modulates decision-making…

Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

In this paper we present a novel adaptation of a tri-phase assessment tool, originally devised to investigate students' linear equations-related strategy flexibility, to evaluate Danish grade-six students' multidigit arithmetic-related strategy adaptivity and flexibility. Participants, 731 students, median age 12 years and drawn from 20…

This study investigated the relationships between school resilience strength, cognitive flexibility, emotion regulation, and school engagement in high school students. A hypothetical model test was conducted for this purpose. This study was designed according to a predictive correlational model. Through convenience sampling, this study collected…

This study tested whether encouraging prediction enhances prediction in second language (L2) speakers. L2 English speakers listened to English sentences like "The woman … will read/buy one of the newspapers" while viewing the target (a newspaper) and distractor objects (a rose, a bowl, and a mango) on a screen and clicked on the target…

This study highlights how health insurance predicts the job performance of secondary school teachers in Cross River State, Nigeria. Using a descriptive survey design, data were collected from 190 public secondary school teachers and 72 principals, vice-principals across the three senatorial districts. Instruments employed were structured…

Digital textbooks are widely used in various educational contexts, such as university courses and online lectures. Such textbooks yield learning log data that have been used in numerous educational data mining (EDM) studies for student behavior analysis and performance prediction. However, these studies have faced challenges in integrating…

The proliferation of digital learning platforms has revolutionized the generation, accessibility, and dissemination of educational resources, fostered collaborative learning environments and producing vast amounts of interaction data. Machine learning (ML) algorithms have emerged as powerful tools for analyzing these complex datasets, uncovering…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…

Analyzing how participants learn from each other during online forums on discussion boards or social media platforms is often challenging. One of the predominant methods of analyzing such learning is through qualitative content analysis or interaction analysis. The Interaction Analysis Model (IAM), developed by Gunawardena, Lowe and Anderson which…

Background: Professor-student rapport is associated with various important student success outcomes, highlighting the need for a good measure of this construct. Objective: The current study attempted to replicate the components of the Professor-Student Rapport Scale (PSRS) reported in Wilson and Ryan (2013). Method: 760 undergraduate students…

In education, understanding the determinants of learners' achievement is crucial. This study aimed to explore the correlation between emotional intelligence (EI) and academic achievement in primary schools. Using Goleman's Emotional Intelligence Assessment Scale adapted for local use, 444 primary school students were assessed via random sampling.…

Neural and symbolic architectures are key techniques in AI for learner modelling, enhancing adaptive educational services. Symbolic models offer explanation and reasoning for decisions but require significant human effort. On the other hand, neural architectures demand less human input and yield better predictions, yet lack interpretability. Given…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…