Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML approaches used for educational data analysis in the last decade and provided recommendations for further research. Using a systematic literature review (SLR), we examined 77 publications from two large and high-impact databases for educational research using bibliometric mapping and evaluative review analysis. Our results suggest that the top five most frequently used keywords were similar in both databases. The majority of the publications (88%) utilised supervised ML approaches for predicting students’ performances and finding learning patterns. These methods include decision trees, support vector machines, random forests, and logistic regression. Semi-supervised learning methods were less frequently used, but also demonstrated promising results in predicting students’ performance. Finally, we discuss the implications of these results for statisticians, researchers, and policymakers in education.

This study analyzed the latest four PISA surveys, 2009, 2012, 2015, and 2018, to explore the association between students’ ICT-related use and math and science performance. Using ICT Engagement Theory as a theoretical framework and a three-level hierarchical linear modeling approach, while controlling for confounding effects, ICT-related independent variables of interest were added to the models at the student, school, and country levels. The series of models revealed that, in general, an increase in ICT availability and ICT use both inside and outside school had a negative association with learning outcomes, while students’ positive attitude toward ICT demonstrated a strong positive relationship. However, students’ perceived autonomy related to ICT use had the strongest association with academic performance, which is consistent with the changing nature of the modern learning environments. Findings revealed that virtually all forms of student ICT use, both inside and outside of school and whether subject related or not, had no substantive positive relationship with student performance in math or science. Conversely, higher student attitude toward, confidence in, belief in utility of, and autonomous use of ICT was associated with higher math and science performance for each of the four years of the study. Incidentally, we also found that while country GDP per capita had no consistent association with student performance, a school’s provision of extra-curricula activities did. Recommendations for educational leaders, teachers, and parents are offered.

TeachLivE™, a mixed-reality simulated classroom technology, has been used in initial teacher education programs to provide repeatable experiential learning opportunities for students now for more than a decade and in more than 80 universities worldwide. However, no broad scale investigation has been conducted into how the platform has been used or what research has been generated as a result. The aim of this study is to provide insight into the types of TeachLivE™ research carried out since its inception and to identify trends and potential gaps in this research. Peer-reviewed academic primary research publications—journal articles (23), conference proceedings (12), and thesis dissertations (20)—were reviewed for participants, research methods, analysis, research design, data collection tools, and design approaches. Of the 102 articles identified as relevant, “instructional skills development” and “integration of TeachLivE™ in teacher education” were the most commonly researched topics. Findings indicate that preservice teachers were the most commonly studied group of participants, research methods were predominately qualitative, single-subject experimental research design was employed most often, and the most used data collection tools were surveys and observation. These findings highlight that the range of topics is increasing, with studies on in-service teachers in school-based contexts beginning to emerge as a new area of interest. This systematic review has implications for researchers and the developers of TeachLivE™. It provides valuable insight and recommendations for future studies in this emerging teacher education field, where technology is not simply used “in the classroom” but rather “as the classroom.”

TeachLivETM, a mixed reality learning environment originating from University of Central Florida (2011), has recently been introduced to the Australian preservice teaching context by Murdoch University (2016) and the University of Newcastle (2017). This paper, the first of a program of research...

The goal of this study is to analyse the publications on mathematics anxiety to contribute to the development of the related literature. A total of 537 papers on mathematics anxiety published in various databases of Web of Science between 2000 and 2018 years were retrieved and analysed through...

Mathematics anxiety is a significant problem in education that affects students’ learning outcomes, academic success, and well-being. This systematic literature review aimed to explore the role of technological interventions in reducing mathematics anxiety and promoting positive learning experiences in mathematics learning. Our findings revealed a mixed picture, where learning mathematics through online distance education increases mathematics anxiety, especially among primary school students, while interventions such as game-based learning and digital tools show positive results in reducing students’ mathematics anxiety levels. Additionally, the results of this study contribute to ongoing discussions on effective strategies to reduce mathematics anxiety and improve mathematics education through the integration of technology, providing new understanding among educators, parents, researchers, and policymakers in creating inclusive and effective learning environments. Using technology to reduce mathematics anxiety and increase student achievement emphasizes the importance of collaborative efforts.