This paper presents a systematic literature review of using Machine Learning (ML) techniques in higher education career recommendation. Despite the growing interest in leveraging Artificial Intelligence (AI) for personalized academic guidance, no previous reviews have synthesized the diverse methodologies in this field. Following the Kitchenham…

The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…

The rapid integration of Artificial Intelligence (AI) in education has led to a surge in research on teachers' adoption of these technologies. However, there is a noticeable lack of comprehensive reviews synthesizing the current state of research on this topic. This study addresses this gap by systematically reviewing 33 studies published since…

Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be used for teacher training, for generating and evaluating hypotheses on human learning, for…

Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…

Interdisciplinary learning requires students to integrate knowledge and methods from different disciplines, prompting advanced skills development and knowledge construction by connecting diverse subjects. Artificial Intelligence (AI), with its rich information base and abilities to track learning and provide personalized support, has the potential…

This study investigated the role of ChatGPT-assisted data analysis in mathematics education research within the post-modern scholarly milieu using a scoping review approach. This examined how ChatGPT contributes to ethical, reliable, rigorous, and context-sensitive data analysis in mathematics education research. The findings reveal five (5)…

This paper presents a systematic review of the application models, affects, and performance outcomes of VR/AR in vocational education. The analysis is based on journal articles retrieved from renowned databases such as Web of Science, Scopus, and EBSCO, spanning from January 2000 to January 2022. It highlights the pedagogical value of VR/AR in…

Based on the UTAUT model, many studies have analyzed the factors influencing the use of artificial intelligence by teachers and students, but the conclusions are not uniform. This study chose high quality studies and encoded them to do meta analysis. After heterogeneity testing, sensitivity analysis and publication bias test, it has been found…

Mathematics education is like many scientific disciplines witnessing an increase in scientific output. Examining and reviewing every paper in an area in detail are time-consuming, making comprehensive reviews a challenging task. Unsupervised machine learning algorithms like topic models have become increasingly popular in recent years. Their…

Learning analytics dashboards (LADs) provide educators and students with a comprehensive snapshot of the learning domain. Visualizations showcasing student learning behavioral patterns can help students gain greater self-awareness of their learning progression, and at the same time assist educators in identifying those students who may be facing…

Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

The successful irruption of AI-based technology in our daily lives has led to a growing educational, social, and political interest in training citizens in AI. Education systems now need to train students at the K-12 level to live in a society where they must interact with AI. Thus, AI literacy is a pedagogical and cognitive challenge at the K-12…