The main objective of this article is to highlight the importance of training in digital tools at the university level to foster the development of innovative and efficient data analysis from a scientific perspective. In an increasingly digitised world, the acquisition of digital skills has become a fundamental requirement for success in various…

Recent advances in publicly available natural language processors (NLP) may enhance the efficiency of analyzing student short-answer responses in physics education research (PER). We train a state-of-the-art NLP, IBM's Watson, and test its agreement with human coders using two different studies that gathered text responses in which students…

Computer-Assisted Qualitative Data Analysis (CAQDAS) is becoming increasingly prevalent in the social and health sciences and an expected skill for many researchers. CAQDAS is much less structured than the use of quantitative analysis software. However, actual CAQDAS practices and challenges have been insufficiently studied, especially among…

The Java software jBar consists of a graphical user interface that allows the user to customize and assemble an included script for R. The scripted R pipeline calculates means and standard errors/deviations for replicates of numerical bivariate data and generates presentations in the form of bar graphs. A two-sided Student's t test is carried out…

"Doing economics" is an important theme of undergraduate economics programs. Capstone courses increasingly include instruction in "data literacy" and the STEM-related skills of quantitative and empirical methods. Because the professional discipline has moved in this direction and because of greater employer demand for these…

This paper describes the integration of geographic information system (GIS) technology in a high school environmental science classroom, specifically examining the impact of GIS technology on student engagement, critical thinking, and interdisciplinary learning for Education for Sustainability (EfS). This environmental science classroom utilized…

Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the…

With the emergence of big data as a strategic weapon in business, the need for hands-on activities in undergraduate courses is essential for preparing the next wave of technical talent. As the availability of programs in data analytics and data science grows based on market demands, the need for foundational technical skills is important to equip…

Research that tackles the pedagogical use of geolocated social media as an investigative tool for understanding cities in Geography and Urban Studies higher education programs has not been fully exploited. This study contributes by addressing the transferability of these sources as a research medium for enhancing student knowledge of urban…

The increasing integration of software and automation in modern chemical laboratories prompts special emphasis on two important skills in the chemistry classroom. First, students need to learn the technical skills involved in modern scientific computing and automation. Second, applying these techniques in practice requires effective collaboration…

The age of data analytics requires "data scientists" across a wide range of business disciplines with deep knowledge of how to manage and analyse vast amounts of data to support decision-making. As a result, new analytical tools are being taught in the Management Information Systems (MIS) or business analytics (BA) programs to foster…

While research on teaching qualitative methods in education has increased, few studies explore teaching qualitative data analysis software within graduate-level methods courses. During 2013, we required students in several such courses to use ATLAS.ti™ as a project management tool for their assignments. By supporting students' early experiences…

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

Previous research has demonstrated how young children can identify the signal in data. In this exploratory study we considered how they might also express meanings for noise when creating computational models using recent developments in software tools. We conducted extended clinical interviews with four groups of 11-year-olds and analysed the…

In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…