Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…

Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…

Engaging with primary researchers during qualitative secondary analysis is a practice much recommended but rarely written about. In this article, I reflect on my experience of crossing an imagined boundary between the discrete textual dataset and its creators, of acknowledging and engaging with those researchers who invested in constructing the…

There have been numerous iterations of naming convention specified for myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS). As health care turns to "big data" analytics to gain insights, the Google Trends database was mined to ascertain worldwide trends of public interest in several ME- and CFS-related search categories…

The digital era has significantly reshaped journalism, emphasizing the pivotal role of data-driven reporting. This review delves into the nexus of data journalism and journalism education, investigating dominant study characteristics, challenges, and gaps for future research. Examining 41 relevant articles through the Arksey and O'Malley…

Retrospective confidence refers to the phenomenological experience of the level of certainty that retrieved information is, in fact, correct. Retrospective confidence judgments are examined across a range of sub-disciplines in psychology from perception to memory research, and in education and legal applications. This paper focuses on…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…

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.…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

This paper explores using data mining in English teaching assessment in higher education within the 'Internet + Education' era. Traditional assessment methods struggle to meet modern teaching needs. By collecting diverse data like student performance and learning behavior, and employing data mining, a comprehensive assessment model is built. This…

Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…

The current study details the development of an undergraduate business analytics course that combines components of both active and experiential learning. The course offering is designed to expose students from different backgrounds to an intermediate-to-advanced level of business analytics. The course is unique in that it was designed to be…

Shoeprints are a common type of evidence found at crime scenes and are regularly used in forensic investigations. However, their utility is limited by the lack of reference footwear databases that cover the large and growing number of distinct shoe models. Additionally, existing methods for matching crime-scene shoeprints to reference databases…

The National Institute of Mental Health created the National Database for Autism Research (NDAR) to accelerate autism knowledge through data sharing and collaboration. However, our experience using NDAR reveals systematic challenges across several aspects of data submission, selection, management, and analysis that limit utility of this resource.…