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Public management and policy scholars have engaged in extensive development of theory and empirical study of networks and collaborative systems of governance. This scholarship has focused on understanding the mechanisms of network formation…
Describing and analysing learner behaviour using sequential data and analysis is becoming more and more popular in Learning Analytics. Nevertheless, we found a variety of definitions of learning sequences, as well as choices regarding data…
The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for analytics applications. This research paper shares empirical…
In addition to formal learning at universities, like in lecture halls and seminar rooms, students are regularly confronted with self-study activities. Instead of being left to their own devices, students might benefit from a proper design…
Student performance prediction is one of the most important subjects in educational data mining. As a modern technology, machine learning offers powerful capabilities in feature extraction and data modeling, providing essential support for…
In this study, I explored the impact of Generative AI on learning efficacy in academic reading materials using experimental methods. College-educated participants engaged in three cycles of reading and writing tasks. After each cycle, they…
AI-augmented classrooms generate rich teacher and student feedback before graded outcomes become available, yet these signals can be difficult to translate into timely instructional decisions. We propose an interpretable decision layer: a…
The surge in the adoption of Intelligent Tutoring Systems (ITSs) in education, while being integral to curriculum-based learning, can inadvertently exacerbate performance gaps. To address this problem, student profiling becomes crucial for…
The rising interest in Virtual Reality (VR) technology has sparked a desire to create immersive learning platforms capable of handling various tasks across environments. Through immersive interfaces, users can engage deeply with virtual…
AI-supported tools can help learners overcome challenges in programming education by providing adaptive assistance. However, existing research often focuses on individual tools rather than deriving broader design recommendations. A key…
The assessment of source code in university education is a central and important task for lecturers of programming courses. In doing so, educators are confronted with growing numbers of students having increasingly diverse prerequisites, a…
Computational reductions are an important and powerful concept in computer science. However, they are difficult for many students to grasp. In this paper, we outline a concept for how the learning of reductions can be supported by…
The incidence of extramural collaboration in academic research activities is increasing as a result of various factors. These factors include policy measures aimed at fostering partnership and networking among the various components of the…
Student diversity, like academic background, learning styles, career and life goals, ethnicity, age, social and emotional characteristics, course load and work schedule, offers unique opportunities in education, like learning new skills,…
Programming courses in computing science are important because they are often the first introduction to computer programming for many students. Many university students are overwhelmed with the information they must learn for an…
Elite economics PhD programs aim to train graduate students for a lifetime of academic research. This paper asks how advising affects graduate students' post-PhD research productivity. Advising is highly concentrated: at the eight…
Iterative methods are ubiquitous in large-scale scientific computing applications, and a number of approaches based on meta-learning have been recently proposed to accelerate them. However, a systematic study of these approaches and how…
Universities are widely expected to respond to technological transitions through rapid reconfiguration of programme demand and curricular supply. Using four decades of longitudinal administrative cohorts (1980-2019) from a large public…
This paper aims to address the challenge of selecting relevant courses for students by proposing the design and development of a course recommendation system. The course recommendation system utilises a combination of data analytics…
Modeling student learning and further predicting the performance is a well-established task in online learning and is crucial to personalized education by recommending different learning resources to different students based on their needs.…