Artificial intelligence technology has become widely used in many industries, including healthcare, agriculture, banking, social security, and home furnishings, due to the rise and development of this discipline. One of the newest areas of technology in the education industry is AI in Education, where extensive research supports instructional…

Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…

Since the late twentieth century, with the development of the Internet of Things (IoT), the IoT covers the application of comprehensive knowledge and technology in the fields of circuitry, physics, mechanics, and information, making it a suitable topic for hands-on science, technology, engineering, and mathematics (STEM) activities. The IoT covers…

Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…

Software modeling is an integral practice for software engineers, especially as the complexity of software solutions increases. Unified Modeling Language (UML) is the industry standard for software modeling. however, it is often used incorrectly and misunderstood by novice software designers. This study is centered around understanding patterns of…

Software modeling is an integral practice for software engineers especially as the complexity of software solutions increase. There is precedent in industry to model information systems in terms of functions, structures, and behaviors. While constructing these models, abstraction and systems thinking are employed to determine elements essential to…

The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…

The research and data aim to (a) examine instructors' evaluation of Microsoft Teams as reflected in their teaching at the Public Authority for Applied Education and Training (PAAET) and (b) identify significant correlation between three determinants of the Technology Acceptance Model: perceived usefulness (PU), perceived ease of use (PEOU), and…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Blended learning sets solid foundations for the utilization of educational technology in authentic student learning experiences within traditional educational contexts as well as in distance education. The author introduces an integrated and distributed model of blended learning, utilizing educational technology for authentic student learning…

Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…

In the European academic systems, the public funding to single universities depends on many factors, which are periodically evaluated. One of such factors is the rate of success, that is, the rate of students that do complete their course of study. At many levels, therefore, there is an increasing interest in being able to predict the risk that a…

This paper focuses on examining the effectiveness of three-dimensional (3D) computer models on student teachers' academic achievement, mental model construction, and spatial ability used in learning the "atomic models" topic in this study. The students were randomly assigned into two groups: the treatment group (TG) where 3D computer…