The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing…

This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…

The emergence of artificial intelligence (AI) in academia has prompted various debates on the uses, threats, and limitations of tools that can create text for numerous academic purposes. Critics argue that these advancements may provide opportunities for cheating and plagiarism and even replace the art of writing entirely. To reclaim the…

Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

Artificial intelligence in higher education is becoming more prevalent as it promises improvements and acceleration of administrative processes concerning student support, aiming for increasing student success and graduation rates. For instance, Academic Performance Prediction (APP) provides individual feedback and serves as the foundation for…

Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…

In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

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…

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…

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…

Contribution: The proposed work carries out the training and testing of the available data through an artificial neural network and develops a model to allocate the subject for maximum outcome. The system also provides percentagewise correlation among all the possible subjects of best fit to allocate among the faculty members. Background: Data…

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…

Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…