Understanding the trends and developments in artificial intelligence research in science education, which has rapidly advanced in recent years, is crucial for technological innovations and applications in education. Therefore, this study examines research on artificial intelligence in science education conducted between 2019 and 2023 (the last…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…

Even though big data offers new opportunities to organizations, big data adoption (BDA) is still in the early stages of introduction, and its determinants remain unclear in many sectors. Therefore, this research intended to identify the determinants of BDA in the education sector. A theoretical model was developed based on the integration of the…

Accelerating advancements in learning analytics and artificial intelligence (AI) offers unprecedented opportunities for improving educational experiences. Without including students' perspectives, however, there is a potential for these advancements to inadvertently marginalize or harm the very individuals these technologies aim to support. This…

This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program's…

In this study, we examine the role of AI-driven marketing in international student recruitment, focusing on how perceived usefulness, trust, and personalization influence decision-making. Grounded in the Technology Acceptance Model (TAM), the Trust-Based Decision-Making Model, and the Personalization--Privacy Paradox, we studied how AI-powered…

Purpose: The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the "trust deficit" in learning analytics. Design/methodology/approach: "Trust" has always been part and parcel of learning analytics research and practice,…

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…

This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…

Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…

This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…

Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…

In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education. Emerging technologies, such as artificial intelligence, virtual reality, machine learning, and data analytics, are redefining the dynamics of higher education. Active…

What are missing in the U.S. education policy of "college for all" are supporting data and indicators on K-16 education pathways, i.e, how well all students get ready and stay on track from kindergarten through college. This study creates synthetic national longitudinal education database that helps track and support students'…