The higher the level of development of higher education, the larger its contribution to socioeconomic development. In order to predict the trend of higher education development in a country more accurately, a new methodology is employed in this study. A weakening buffer operator-based GM (1, 1) model is constructed using Kazakhstan's gross…

The author of this article demonstrates how the unified approach to answering economic questions employed in modern quantitative macroeconomics research can be taught to undergraduate students using the Solow model. Through an application to post-WWII Japan, students get hands-on experience with (1) documenting empirical facts, (2) developing a…

Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…

This case study examines the use of electronic resources in academic institutions and the difficulties in forecasting their usage. By employing time series analysis-based models, the study forecasts the utilization of e-resources from 2012 to 2021. It concludes that both Autoregressive Integrated Moving Average (ARIMA) and Error, Trend, Seasonal…

This study aims to predict accounting students' inclination toward a career in accounting in Indonesia by integrating the Social Cognitive Career Theory (SCCT) and the Theory of Reasoned Action (TRA). The research relies on primary data obtained through an online, closed-ended questionnaire. We employ Structural Equation Modeling (SEM) for the…

The objective of this paper is the design of a predictive model of students' desertion in Educational Institutions based on the Analytic Hierarchy Process (AHP). The proposed model is based on a weighted sum of individual probabilities of desertion associated with various factors (explanatory variables) by experts in the combined use of the AHP…

On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…

Purpose: This study aims to investigate the merits of the unified model of task-specific motivation (UMTM) in predicting transfer of training and to investigate (relationships between) changes in UMTM components over time. In doing so, this study takes the multidimensionality of transfer motivation into account. Design/methodology/approach: The…

Predictive research on the enrollment proportion of general education and vocational education is crucial to optimizing the regional talent structure and industrial structure adjustment. The reasonable enrollment proportion of general education and vocational education also plays an important role in the adjustment of the overall employment…

Digital technology is profoundly transforming various aspects of life, thus highlighting the need to enhance digital literacy on a national scale. In primary and secondary schools, artificial intelligence (AI) education plays a pivotal role in fostering digital literacy. To comprehensively investigate the variables influencing AI education in…

School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…

Many studies show that augmented reality (AR) provides multiple benefits to science education, including learning gains, motivation to learn, and collaborative learning. However, while using AR largely depends on the teachers' willingness, existing literature lacks studies that identify teachers' intentions to use this technology. This study…

In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…

The article is in the second phase of research is about "the big data architecture for pre-teacher preparation supply chain with prescriptive analytics of higher education in Thailand". The objectives of the study were (1) to study the pre-teacher preparation supply chain in Thailand, (2) to develop a model the big data system for the…

This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…