The ever-changing landscape of distance learning AI and learning analytics transforms engagement and efficiency in education. AI systems analyze behavior and performance data to provide real-time feedback for improved outcomes. Learning analytics further help educators to identify at-risk students while fostering better teaching strategies. By…

This systematic literature review explores learning analytics (LA) in serious games within virtual reality (VR) environments, focusing on studies from the International Conference on Learning Analytics and Knowledge (LAK) and the Journal of Learning Analytics (JLA). Conducted in two stages, the review identifies key domains where serious games in…

Early identification of student success is crucial for enabling timely interventions, reducing dropout rates, and promoting on-time graduation. In educational settings, AI-powered systems have become essential for predicting student performance due to their advanced analytical capabilities. However, effectively leveraging diverse student data to…

The integration of advanced learning analytics and data-mining technology into higher education has brought various opportunities and challenges, particularly in enhancing students' self-regulated learning (SRL) skills. Analyzing developed features for SRL support, it has become evident that SRL support is not a binary concept but rather a…

Due to the use of online learning platforms and learning management systems, students are now working unsupervised on quiz-taking platforms. These unsupervised online forms of assessment are replacing traditional supervised quizzes in conventional classrooms. It is unclear whether the quiz-taking behaviors of students in these settings align with…

This study focuses on learning analytics from the perspective of elementary and secondary classroom teachers (grades one to nine). The aim is to explore teachers' perceptions about the use of learning analytics, the challenges and opportunities associated with the tools, and the future of the analytics. The research is based on qualitative data:…

Educational games help reinforce educational concepts. They help students learn through hypothesizing, probing, and reflecting upon the game environment. Understanding the impact of a game is important before deploying it in a class. Recent studies in learning analysis describe methodologies and approaches for analyzing educational games. However,…

Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major selection using a large language model (LLM), GPT-4. Through a three-phase survey, we compare GPT suggestions and responses for undeclared first- and second-year students…

Today, the importance of artificial intelligence in science learning and teaching is rapidly increasing. The growing interest in this field and the resulting increase in academic publications on the subject make it challenging to understand its progress and trends on a global scale. Furthermore, a literature review reveals a notable lack of…

Computational thinking (CT) is a critical 21st-century skill that equips undergraduate students to solve problems systematically and think algorithmically. A key component of CT is computational creativity, which enables students to generate novel solutions within programming constraints. Humanoid robots are increasingly explored as promising…

This study investigates the integration of artificial intelligence into the Think-Pair-Share (TPS) methodology through a learning analytics lens. Using a mixed-methods quasi-experimental design (N=140), we examined how an AI-enhanced collaborative platform influences creative thinking among computer science undergraduates. The experimental group…

Learning analytics provides a novel means to support the development and growth of students into self-regulated learners, but little is known about student perspectives on its utilization. To address this gap, the present study proposed the following research question: what are the perceptions of higher education students on the utilization of a…

Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

The rise of generative artificial intelligence (GAI), especially with multimodal large language models like GPT-4o, sparked transformative potential and challenges for learning and teaching. With potential as a cognitive offloading tool, GAI can enable learners to focus on higher-order thinking and creativity. Yet, this also raises questions about…