The demand for graduates with coursework in business/data analytics continues to grow, and many career rankings list these skills among the top in demand by industry. This study examines trends in how Information Systems (IS) academic departments have adapted to this demand by incorporating business analytics in their departmental naming…

Technology and data analysis have evolved into a resource-rich tool for collecting, researching and comparing student achievement levels in the classroom. There are sufficient resources to discover student success through data analysis by routinely collecting extensive data on student behaviour and curriculum structure. Educational Data Mining…

A model that maps the requisite skills, or knowledge components, to the contents of an online course is necessary to implement many adaptive learning technologies. However, developing a skill model and tagging courseware contents with individual skills can be expensive and error prone. We propose a technology to automatically identify latent…

Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…

This study aims to use the bibliometric analysis method to examine the scientific articles published between 2000-2022 in the field of Arabic Language Teaching (ALT) and to visualize the obtained data with visual mapping technique. The dataset consists of 861 educational research articles indexed in the "Web of Science" database and…

There is an increasing demand to introduce Introductory Business Analytics (IBA) courses into undergraduate business education. Many real-world business contexts require predictive analytics to understand the determinants of a dichotomous outcome; hence, IBA courses should include binary logistic regression analysis. This article provides our…

This research aims at providing an overview of the research field of digital literacy into learning and education. Using text mining, it reviews 1037 research articles published on the topic between 2000 and 2020. This review reveals that there is a plurality of terms associated with digital literacy. Moreover, our research identifies six key…

Mandatory community college student fees have risen steadily over the past 20 years, outpacing the growth of tuition by a substantial margin. To date, research on postsecondary fees has been limited to public four-year colleges and universities, even as community college fees are growing faster and affecting students who are likely more price…

This paper shows a method for integrating computer programming into a standard physical chemistry laboratory sequence to augment student data analysis abilities and allow them to carry programming skills forward to other courses. The Python programming language is used, taking advantage of the pedagogical benefits of Jupyter notebooks, primarily…

Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…

Machine Learning concept learns from experiences, inferences and conceives complex queries. Machine learning techniques can be used to develop the educational framework which understands the inputs from students, parents and with intelligence generates the result. The framework integrates the features of Machine Learning (ML), Explainable AI (XAI)…

This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research…

Country differences in response styles (RS) may jeopardize cross-country comparability of Likert-type scales. When adjusting for rather than investigating RS is the primary goal, it seems advantageous to impose minimal assumptions on RS structures and leverage information from multiple scales for RS measurement. Using PISA 2015 background…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…