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 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…

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 this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

Undergraduate research is considered to be a high-impact practice; however, research into the data literacy of students conducting undergraduate research is lacking. In addition, institutionwide assessments of data practices are challenging because of varied disciplinary approaches to data. This study investigates the data practices of…

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…

Both graph comprehension and data analysis and interpretation are influenced by one's prior knowledge and experiences. To understand how one's prior knowledge and experiences interact with their analysis of a graph, we conducted think-aloud interviews with general chemistry students as they interpreted a graph to determine optimal conditions for…

The aim of this study is to compare the master's (MA) theses in Türkiye (TR) and Finland (FIN) published between 2015-2019. A total of 765 theses were analysed in terms of year, discipline, methodological approach, research method, didactic foci, data collection tool, target group, and sample size. The results showed that FIN theses grounded on…

An inquiry-based learning approach was implemented into comprehensive organic chemistry experiments focusing on the formation process of N-phenylbenzamide from the reaction between N-benzylideneaniline and benzoyl peroxide in commercial dimethyl sulfoxide. Students conducted comparative experiments using alternative reagents or reaction conditions…

This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented--but how has this affected teaching of this important topic? Although the purpose of marketing…

Higher education leaders have repeatedly called for improved diversity, equity, and inclusion efforts, but many institutions continue to fall short. Data can play an integral role in this work; key among them are data on student demographics, including race/ethnicity. Meeting diversity, equity, and inclusion goals requires a thorough and nuanced…

Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental…

Understanding data analysis and interpreting data are key components of teaching interdisciplinary undergraduate students. We detail a semester-long research project that introduces students to long-term data sets, incorporates the use of widely available statistical analysis, and underscores an inquiry-based method of teaching climate change. Our…

Ubiquitous datafication surrounds agriculture stakeholders with data as the raw material for additional value creation, resilience and innovation. Technical and soft competencies of data literacy (DL) are not comprehensively addressed in formal secondary education as an interdisciplinary and general concept. Aiming to assess DL structure set for…