With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…

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…

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…

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.…

English has long been regarded as the universal language. Countries that were earlier reluctant to learn English have also changed their stand due to its global reach. The nonnative English speaker's proficiency largely depends on the College English Teaching (CET) and its evaluation methods. Traditional teaching evaluation models failed to…

Text analytics in education has evolved to form a critical component of the future SMART campus architecture. Sentiment analysis and qualitative feedback from students is now a crucial application domain of text analytics relevant to institutions. The implementation of sentiment analysis helps understand learners' appreciation of lessons, which…

The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…

E-learning readiness (ELR) is critical for implementing digital education strategies, particularly in developing countries where online learning faces unique challenges. This study aims to provide a concise and actionable framework for assessing and predicting ELR in Algerian universities by combining the ADKAR model with advanced machine learning…

Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…

Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…

Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…

Computational thinking (CT) skills of pre-service teachers have been explored extensively, but the effectiveness of CT training has yielded mixed results in previous studies. Thus, it is necessary to identify patterns in the relationships between predictors of CT and CT skills to further support CT development. This study developed an online CT…

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…

Progress tests (PT) are a popular type of longitudinal assessment used for evaluating clinical knowledge retention and long-life learning in health professions education. Most PTs consist of multiple-choice questions (MCQs) whose development is costly and time-consuming. Automatic Item Generation (AIG) generates test items through algorithms,…

The study of robotics has become a popular course among many educational programs, especially as a technical elective. A significant part of this course involves having the students learn how to program the movement of a robotic arm by controlling the velocity of its individual joint motors, a topic referred to as joint programming. They must…