Background: As immersive virtual reality (IVR) is increasingly being used by teachers worldwide, it becomes pressing to investigate how this technology can foster learning processes. Several authors have pointed to this need, as results on the effectiveness of IVR for learning are still inconclusive. Objectives: To address this gap, we first…

As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…

There is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools.…

Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…

This study explored the integration of neural networks and artificial intelligence in image recognition for object identification. The aim was to enhance students' learning experiences through a "Learning by Teaching" approach, in which students act as instructors to train AI robots in recognizing objects. This research specifically…

As AI increasingly enters classrooms, educational designers have begun investigating students' learning processes vis-à-vis simultaneous feedback from active sources--AI and the teacher. Nevertheless, there is a need to delve into a more comprehensive understanding of the orchestration of interactions between teachers and AI systems in educational…

Multilingual learners (MLs) often struggle with science conceptual learning partly due to the abstractness of the concepts and the complexity of scientific texts. This study presents a case of a Virtual Reality (VR) enhanced science learning unit to support middle-school students' science conceptual learning. Using a transformative mixed methods…

The aim of this research is to investigate the educational potential of AI-powered chatbots in Social Studies learning-teaching processes. The study was conducted using embedded design, evaluated within the framework of mixed methods research. The study group consists of 78 6th-grade students studying in three different classes, along with one…

Drama learning is helpful for English speaking, however, few studies provided students with opportunities to practice drama conversations individually. This study proposed a Context-Awareness Smart Learning Mechanism (CASLM) and integrated into SmartVpen that consisted of context-aware learning content, context-aware input assistance, oral…

Educational chatbots promise many benefits for teaching and learning. Although chatbot use cases in this research field are rapidly growing, most studies focus on individual users rather than on collaborative group settings. To address this issue, this paper investigates how chatbot-mediated learning can be designed to foster middle school…

Reading requires appropriate strategies to spark initial interest and sustain engagement. One promising strategy is the pedagogical approach of learning-by-teaching, transforming learners into active participants. Integrating this approach into digitalized and individualized reading contexts has the potential to foster the development of young…

Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…

Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…