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…

When we monitor our learning, often measured via judgments of learning (JOLs), this metacognitive process can change what is remembered. For example, prior work has demonstrated that making JOLs enhances memory for related, but not unrelated, word pairs in younger adults. In the current study, we examined potential age-related differences in…

This study aims to predict accounting students' inclination toward a career in accounting in Indonesia by integrating the Social Cognitive Career Theory (SCCT) and the Theory of Reasoned Action (TRA). The research relies on primary data obtained through an online, closed-ended questionnaire. We employ Structural Equation Modeling (SEM) for the…

Successful language comprehension requires the rapid deployment of working memory resources alongside the capacity to predict upcoming linguistic input. While previous research views these as competing factors, this dissertation explores a unified theory of processing complexity and evaluates the interaction between memory and prediction. The…

The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content of SSM is introduced. Secondly, the BP (Back Propagation) neural network, the LM (Levenberg Marquardt) algorithm, and the BR (Bayesian Regularization)…

PISA aims to serve as a "global yardstick" for educational success, as measured by student performance. For comparisons to be meaningful across countries or over time, PISA samples must be representative of the population of 15-year-old students in each country. Exclusions and non-response can undermine this representativeness and…

The e-learning domain has witnessed a shift from the traditional behavioral approach to an individual centered learning approach based on learning analytics, with the aim of creating personalized and learner sensitive designs. A systematic literature review of 284 articles published between 2011 and 2022 in 133 different journals was conducted to…

Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers' data-driven pedagogical decision-making. While many LADs have been designed, teachers' capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a…

Although academic success among diverse community college students requires effective reading skills, providing support for struggling readers is becoming increasingly more difficult. The problem addressed in this quantitative study was that due to Assembly Bill 705, prohibiting colleges from offering remedial courses without data to substantiate…

The Home Literacy model predicts different outcomes depending on formal and informal literacy practices carried out at home. However, this model does not explicitly consider the potential differences that the media (paper vs. tablets) in which these practices are carried out can have on performance. The present study explored this issue.…