This paper introduces the LEGO® Database, a large natural dataset that can be used to teach Structured Query Language (SQL) and relational database concepts. This dataset is well-suited for introductory and advanced database assignments and end-of-semester group projects. The data is freely available from Kaggle.com and contains eight tables with…

The significance of ethics in data science research has attracted considerable attention in recent years. While there is widespread agreement on the importance of teaching ethics within computing contexts, there is no clear method for its implementation and assessment. Studies focusing on methods for integrating ethics into data science courses…

Classification, a fundamental data analytics task, has widespread applications across various academic disciplines, such as marketing, finance, sociology, psychology, education, and public health. Its versatility enables researchers to explore diverse research questions and extract valuable insights from data. Therefore, it is crucial to extend…

The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered…

In recent years, big data has become ubiquitous in our day-to-day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and…

This article discusses the key elements of the Data Science Technology course offered to postgraduate students enrolled in the Master of Data Science program. This course complements the existing curriculum by providing the skills to handle the Big Data platform and tools, in addition to data science activities. We tackle the discussion about this…

Despite the increasing interest in data science education in the world, its teaching is not included in the curricula (junior secondary) and there is little information about it. Google Trends is discussed as a tool and database in school data science. Also, in different subjects, students were able to create and interpret graphs using this tool.…

Data preparation (also called "wrangling" or "cleaning") -- the evaluation and manipulation of data prior to formal analysis -- is often dismissed as a precursor to meaningful engagement with a dataset. Here, we re-envision data preparation in light of calls to prepare students for a data-rich world. Traditionally, curricular…

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…

This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…

Business analytics is a fast-growing field that requires a combination of technical, analytical, and communication skills. This article aims to identify the most sought after skills for business analytics jobs based on a content analysis of over 2600 online job postings. The results show that the top skills include analytics, communication,…

Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…

Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…

We describe a unique environment in which undergraduate students from various STEM and social science disciplines are trained in data provenance and reproducible methods, and then apply that knowledge to real, conditionally accepted manuscripts and associated replication packages. We describe in detail the recruitment, training, and regular…

Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…