This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

We interrogate the opportunities and challenges of using mixed methods (MM) within a developmental evaluation (DE) context by drawing on two illustrative cases that investigated educational change in Canada. Methods: Multi-case design and cross-case analysis, with a focus on examining common patterns across the two cases, enabling new ways of…

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…

With the rapid advancement of information technology, online education based on big data and artificial intelligence is a hot research topic in education. This study focuses on applying big data and AI in online vocal wisdom classes to enhance personalized teaching and effectiveness. It aims to address issues in traditional vocal education like…

Data analytics and programming skills are increasingly important in the humanities, especially in disciplines like linguistics due to the rapid growth of natural language processing (NLP) technologies. However, attitudes and perceptions of students as novice learners, and the attendant pedagogical implications, remain underexplored. This article…

As we examine the pandemic's impact on higher education, we can see that many previously traditional teaching and learning frameworks have been invalidated, and the need for new teaching and learning approaches has increased. This indicates that the traditional frameworks for higher education may no longer be effective. Consequently, there is a…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

This is the first of four columns by Tim Erikson which introduces us to the Common Online Data Analysis Platform (CODAP). CODAP is a free, web-based software tool that your students can use for many types of tasks. This first column shows how CODAP can be used for mathematical modelling and where it might fit with the "Australian Curriculum:…

In 2003, Holmes [The Statistician 52, Part 4, (2003), 439-474] reviewed 50 years of teaching statistics in English schools and drew out many lessons for more effective teaching. We consider the current relevance of several of these lessons and whether we have learned from them. Many national reports have been published about teaching statistics…

In recent years, China has accelerated the process of internationalization and made more and more achievements in transnational communication and cooperation. English learning is very important for contemporary college students. And English reading is an important means to acquire English language knowledge, understand external information and…

Purpose: The firms use training evaluation practices (TEPs) to determine the return of billions of dollars spent on employee training and development activities. The firms need to modernize the set of TEPs for evidence-based workforce management decisions. This study aims to examine a mediation mechanism to explain how human resource (HR)…

The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…

The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…