The advent of Large Language Models (LLMs) has fundamentally disrupted our thinking about educational technology. Their ability to engage in natural dialogue, provide contextually relevant responses, and adapt to learner needs has led many to envision them as powerful tools for personalized learning. This emergence raises important questions about…

Chatbot research has received growing attention due to the rapid diversification of chatbot technology, as demonstrated by the emergence of large language models (LLMs) and their integration with automatic speech recognition. However, among various chatbot types, speech-recognition chatbots have received limited attention in relevant research…

Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…

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…

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…

Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies to analyse AI-supported student engagement (AIsE) studies regarding research keywords and topics, AI roles, AI systems and algorithms, methods and domains,…

Software assistants have significantly impacted software development for both practitioners and students, particularly in capstone projects. The effectiveness of these tools varies based on their knowledge sources; assistants with localized domain-specific knowledge may have limitations, while tools, such as ChatGPT, using broad datasets, might…

The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within…

This paper presents a comprehensive analysis of the major themes in Natural Language Processing (NLP) applications for personalized learning, derived from a Latent Dirichlet Allocation (LDA) examination of top educational technology journals from 2014 to 2023. Our methodology involved collecting a corpus of relevant journal articles, applying LDA…

Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…

Artificial Intelligence (AI) plays a vital role in the growth and progress of education. Therefore, there is a need to scientifically explore the application of Artificial Intelligence in Education (AIED) and systematically analyze the development trends and research hotspots of AIED to provide reference for researchers. In this study, 1356…

Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

Contribution: This research explores the benefits and challenges of developing, deploying, and evaluating a large language model (LLM) chatbot, MoodleBot, in computer science classroom settings. It highlights the potential of integrating LLMs into LMSs like Moodle to support self-regulated learning (SRL) and help-seeking behavior. Background:…

Efforts to utilize AI in education, and especially in language education, have their roots in the 60s with the appearance of the first rule-based systems. However, recent advances in Artificial Intelligence (AI) and more specifically the introduction of ChatGPT, have given a new perspective to language learning. The integration of AI, natural…