The rapid integration of artificial intelligence (AI) into higher education has revolutionised academic research and teaching, offered transformative opportunities while raising significant ethical challenges. This Delphi study investigates the ethical dilemmas and institutional requirements for maintaining academic integrity in AI-driven…

School choice systems increasingly use common applications, where students can apply to multiple schools on a single form, though schools make admission decisions independently. We model three application systems: a common application, a decentralized system with costly separate applications, and a ranked-choice system using a matching algorithm.…

Certification organizations aim to assess candidates on their breadth and depth of knowledge to determine eligibility for certification in their field of specialty. Assessments used for certification, when appropriately constructed, should use questions (or items) that assess the entirety of the field. However, comparing the plethora of the…

Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic…

The Miller-Rabin test is a useful probabilistic method for finding large primes. In this paper, we explain the method in detail and give three variations on this test. These variations were originally developed as student projects to supplement a course in error correcting codes and cryptography.

Online learning has developed rapidly and billions of learners have participated in various courses. However, the high dropout rate is universal and learning performance is not satisfactory. Fortunately, learners have posted a large number of reviews which express their feedback opinions. The fine-grained aspects and opinions existing in reviews…

In e-learning environments, most adaptive systems do not consider the learner's emotional state when recommending activities for learning difficulties, blockages, or demotivation. In this paper, we propose a new approach of emotion-based adaptation in e-learning environments. The system will allow recommendation resources/activities to motivate…

Testing for differential item functioning (DIF) has undergone rapid statistical developments recently. Moderated nonlinear factor analysis (MNLFA) allows for simultaneous testing of DIF among multiple categorical and continuous covariates (e.g., sex, age, ethnicity, etc.), and regularization has shown promising results for identifying DIF among…

Understanding the nature of science is an essential component of scientific literacy. In a technology and media-oriented environment, text-processing algorithms and various artificial learning approaches are crucial and continue to develop. Latent Dirichlet Allocation is a topic modeling algorithm that has been used frequently for many years to…

Multidimensional Item Response Theory (MIRT) has been widely used in educational and psychological assessments. It estimates multiple constructs simultaneously and models the correlations among latent constructs. While it provides more accurate results, the unidimensional IRT model is still dominant in real applications. One major reason is that…

In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…

In order to explore the maturity of online concerts and the digital content of music resources, this article analyzes the role of artificial intelligence in music education, discusses the application of artificial intelligence in music education and the development trend of artificial intelligence in education, and studies the quality of vocal…

Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of…

QR decomposition is widely used for solving the least squares problem. However, existing materials about it may be too abstract for non-mathematicians, especially STEM students, and/or require serious background in linear algebra. The paper describes theoretical background and examples of GNU Octave compatible MATLAB scripts that give relatively…

Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…