In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach…

This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an "interest" parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's…

AI tutors are promised to expand access to personalized learning, improving student achievement and addressing disparities in resources available to students across socioeconomic contexts. The rapid development and introduction of AI tutors raises fundamental questions of epistemic trust in education. What criteria should guide students' critical…

Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…

Web-based learning systems with adaptive capabilities to personalize content are becoming nowadays a trend in order to offer interactive learning materials to cope with a wide diversity of students attending online education. Learners' interaction and study practice (quizzing, reading, exams) can be analyzed in order to get some insights into the…

This study explores the development and evaluation of a chatbot model designed to facilitate learning within a department of a university. The project aims to enhance the learning experience by incorporating customized data into the chatbot's knowledge base, enabling personalized and context-aware interactions. The research investigates the…

Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…

Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using…

This study investigates methods and effectiveness of implementing Differentiated Instruction (DI) in intelligent education based on learners' learning needs. The paper employs a mixed-method approach to collect and analyze data from various learner groups. Guided by the assessment results of the KANO model, the research prioritizes attributes for…

The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…

Building on previous research that has demonstrated close connections between constructivism, technology, and artificial intelligence, this article investigates the constructivist underpinnings of strategically integrating GenAI experiences in higher educational contexts to catalyze student learning. This study presents a new model for leveraging…

The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…

The purpose of this study is to propose an e-learning system model for learning content personalisation based on students' emotions. The proposed system collects learners' brainwaves using a portable Electroencephalogram and processes them via a supervised machine learning algorithm, named K-nearest neighbours (KNN), to recognise real-time…

Advances in data analytics and intelligent technologies are enabling smart learning environments that promote personalized learning. Personalized learning systems where learners engage with information in a manner tailored to their unique needs, goals, and abilities have garnered significant academic research attention. If students can achieve…