Recent years have seen increased interests in applying the latest technological innovations, including artificial intelligence (AI) and machine learning (ML), to the field of education. One of the main areas of interest to researchers is the use of ML to assist teachers in assessing students' work on the one hand and to promote effective…

As one of the fundamental tasks in the online learning platform, interactive course recommendation (ICR) aims to maximize the long-term learning efficiency of each student, through actively exploring and exploiting the student's feedbacks, and accordingly conducting personalized course recommendation. Recently, deep reinforcement learning (DRL)…

We created a list of more than 140 tools that can be used to create tutoring systems, from complete tutoring systems to low-level tools for preparing instructional materials. Based on this list, we present a preliminary ontology of system dimensions that can serve as a base for a comprehensive review or in building systems. We also note that: (a)…

Pearson's Learning Foundations describe the optimal conditions for learning and reflect the learner experience Pearson hopes their products will create. Pearson does this by incorporating the Learning Design Principles. Each of the Learning Design Principles goes into detail about a key principle, supporting product design and marketing by…

Several researchers studied the impact of collaboration between the learners, but few studies have been carried out on the impact of collaboration between teachers. In the previous work, the authors have studied the impact of the collaboration among the learners with a specific collaborative CEHL(K. Boussaha et al.,2015). In this work, the authors…

Intelligent Tutoring Systems (ITS) and Augmented Reality (AR) have become greatly popular in current scenario, especially for helping students in mastering difficult subjects through a variety of different methods with the implementation of smart algorithms. There are many papers in the current literature that discuss the ITS architecture and the…

Differentiated instruction contends that teachers should vary their instructional strategies to match the learners' individual differences. However, this is challenging due to various constraints of classroom and contextual variables. Adaptive systems offer a solution to this challenge, especially as instruction has increasingly moved towards an…

Artificial intelligence (AI) based education represents a significant transformation in the field of education of our age. Artificial intelligence (AI) technology has great potential to enrich the learning experience of special needs students, provide support to teachers, and reduce inequalities in education. Artificial intelligence (AI)…

Assessments of natural language can provide vast information about individuals' thoughts and cognitive process, but they often rely on time-intensive human scoring, deterring researchers from collecting these sources of data. Natural language processing (NLP) gives researchers the opportunity to implement automated textual analyses across a…

Generative artificial intelligence (AI) technologies, such as large language models (LLMs) and diffusion model image and video generators, can transform learning and teaching experiences by providing students and instructors with access to a vast amount of information and create innovative learning and teaching materials in a very efficient way…

The landscape of writing is evolving in the era of generative AI. James Paul Gee introduces the concept of "cybersapien writing literacy," which emphasizes a synergistic partnership between humans and AI. He outlines four essential types of writing and discusses their potential benefits for personal growth, critical thinking, and…

Artificial Intelligence is a fast-evolving technology with enormous potential for education, higher education, and learning. AI can also negatively impact how societies and their citizens engage ethically with these generated, still-unexplored tools. These technological breakthroughs present both opportunity and potential peril. The problem of any…

ITSs have the requirement to be adaptive to the student with AI. The classical ITS architecture defines three components to split the data and to keep it flexible and thus adaptive. However, there is a lack of abstract descriptions how to put adaptive behavior into practice. This paper defines how you can structure your data for case based systems…

Although cognitive load (CL) and self-regulated learning (SRL) have been widely recognized as two determinant factors of students' performance, the integration of these two factors is still in its infancy. To further specify why and how CL links with SRL, we first conducted an overview to describe the multiple dimensions of cognitive load (i.e.,…

The current work develops intelligent tutoring aspects for the DiscoverOChem learning platform. Intelligent tutoring systems are technology-based learning systems that can adapt the learning experience to better serve individual users. DiscoverOChem (www.discoverochem.com) is a free Internet-based platform for learning undergraduate-level organic…