Related papers: The educational process organization in the distan…
In this paper, we provide a theoretical framework that separates the control and learning tasks in a linear system. This separation allows us to combine offline model-based control with online learning approaches and thus circumvent current…
Our entire society is becoming more and more dependent on technology and specifically on software. The integration of e-learning software systems into our day by day life especially in e-learning applications generates modifications upon…
One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new…
Information processes in the society encourage the formation of a revision of the forms and methods of learning; involve the use of didactic capabilities of information and communication technologies in teaching. No less important in this…
The principles on which can be based computer model of process of training are formulated. Are considered: 1) the unicomponent model, which is recognizing that educational information consists of equal elements; 2) the multicomponent model,…
Educational Data Mining (EDM) has emerged as a vital field of research, which harnesses the power of computational techniques to analyze educational data. With the increasing complexity and diversity of educational data, Deep Learning…
There is an increasing interest in learning outside of the traditional classroom setting. This is especially true for topics covering computational tools and data science, as both are challenging to incorporate in the standard curriculum.…
Embedded computing systems are pervasive in our everyday lives, imparting digital intelligence to a variety of electronic platforms used in our vehicles, smart appliances, wearables, mobile devices, and computers. The need to train the next…
Continual learning is essential for all real-world applications, as frozen pre-trained models cannot effectively deal with non-stationary data distributions. The purpose of this study is to review the state-of-the-art methods that allow…
The domain of Information and Communication Technology (ICT) education has garnered significant consideration in recent times. However, several challenges are inherent to this area of study, including monetary expense, temporal factors,…
Virtual laboratories are the new online educational trend for communicating to students practical skills of science. In this paper we report on a comparison of techniques for familiarizing distance learning students with a 3D virtual…
This guide is proposed as an operational instrument for CONFRASIE member universities (Regional Rectors' Conference of AUF member institutions in Pacific-Asia) in their projects to set up a blended learning system for bachelor's, Master's…
Three challenges limit the progress of robot learning research: robots are expensive (few labs can participate), everyone uses different robots (findings do not generalize across labs), and we lack internet-scale robotics data. We take on…
Educational technologies are revolutionizing how educational institutions operate. Consequently, it makes them a lucrative target for breach and abuse as they often serve as centralized hubs for diverse types of sensitive data, from…
In increasingly multicultural and multilingual societies, foreign language learning has become essential not only for communication but also for social cohesion and professional advancement. Distance education has emerged as a flexible and…
Over the past decades, numerous practical applications of machine learning techniques have shown the potential of data-driven approaches in a large number of computing fields. Machine learning is increasingly included in computing curricula…
In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decision process (MDP) and systematically unravel the structural…
Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to new tasks. This review provides a comprehensive technical overview of meta-learning,…
Closure problems are omnipresent when simulating multiscale systems, where some quantities and processes cannot be fully prescribed despite their effects on the simulation's accuracy. Recently, scientific machine learning approaches have…
This paper details an outlook on modern constraint programming (CP) education through the lens of a CP instructor. A general overview of current CP courses and instructional methods is presented, with a focus on online and…