In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…

We studied collaborative skill acquisition in a dynamic setting with the game Co-op Space Fortress. While gaining expertise, the majority of subjects became increasingly consistent in the role they adopted without being able to communicate. Moreover, they acted in anticipation of the future task state. We constructed a collaborative skill…

Research on gamification's effects in educational environments has been a growing domain in recent years. As research has demonstrated the power of gamified systems to effectively motivate learners in educational settings, it has also become clear that not all individuals are motivated in the same way, or to the same extent, by the same gamified…

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…

There has been great progress towards Reinforcement Learning (RL) approaches that can achieve expert performance across a wide range of domains. However, researchers have not yet applied these models to learn expert models for educationally relevant tasks, such as those taught within tutoring systems and educational games. In this paper we explore…

In tutoring systems, a pedagogical policy, which decides the next action for the tutor to take, is important because it determines how well students will learn. An effective pedagogical policy must adapt its actions according to the student's features, such as knowledge, error patterns, and emotions. For adapting difficulty, it is common to…

This article discusses a three-phase model aimed at obtaining vocal speech with students who display selective mutism at school. The three phases discussed include: (1) establishing reinforcer influence; (2) enhancing motivation to speak; and (3) generalize to nontherapy settings. The utilization of this approach to get speech to occur and…

The current study investigated the effect of moral stories in promoting kindergarteners' sharing behaviour. One hundred eight children were randomly assigned to one of three conditions: two experimental conditions (a moral story with a sharing model and good consequences and a moral story with a selfish model and bad consequences) and a control…

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…

This study examined a behavioral intervention package to promote the use of target vocalizations alongside speech-generating device (SGD) mands. Six minimally verbal children with autism spectrum disorder participated, including three with no prior SGD experience. During baseline, SGD responses resulted in access to a preferred item and there was…

This paper studies the use of Reinforcement Learning (RL) policies for optimizing the sequencing of online learning materials to students. Our approach provides an end to end pipeline for automatically deriving and evaluating robust representations of students' interactions and policies for content sequencing in online educational settings. We…

The present paper offers a definition of peer assessment and then reviews the major syntheses on its effectiveness. However, the main part of this paper is preoccupied with how to do PA successfully. A typology of 44 elements explains the differences between the many types of peer assessment. Then a theoretical model outlines some of the processes…

Self-regulation of cognition and behavior is an important aspect of student learning and academic performance in the 21st-century classroom. The purpose of the chapter is to present how an integrated framework of cyclical phases and developmental levels of self-regulated learning play a significant role in modeling and self-regulatory learning as…

Personalized education systems recommend learning contents to students based on their capacity to accelerate their learning. This paper proposes a personalized exercise recommendation system for online self-directed learning. We first improve the performance of knowledge tracing models. Existing deep knowledge tracing models, such as Dynamic…