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…

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…

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…

This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques,…

In today's information age, developing data science competencies has become vital to fostering responsible citizenry. However, the actual techniques learners need to become proficient in are still somewhat "in-construction", as the relatively new field of data science is constantly expanding to meet new data-related demands. Data science…

The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…

The Powerful Learning with Computational Thinking report explains how the Digital Promise team works with districts, schools, and teachers to make computational thinking ideas more concrete to practitioners for teaching, design, and assessment. We describe three powerful ways of using computers that integrate well with academic subject matter and…

To respond to the needs of digital transformation, universities must continue to play their role as proving ground for educating the future generation and innovation. The article is devoted to overview, discussion, and investigation of application in higher education of two modern information technologies: big data and internet of things. The…

Powder diffraction is one of the most widely used analytical techniques for characterizing solid state materials. It can be used for phase or polymorph identification, quantitative analysis, cell parameter determination, or even full crystal structure analysis using the powerful Rietveld refinement method. As with much of modern crystallography,…

The distributed practice effect suggests that students retain learning content better when they pace their practice over time. The key factors are practice dosage (intensity) and timing (when to practice and how in between). Inspired by the thriving development of image recognition, this study adopts one of the successful techniques,…

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…

Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…

I first met Jim Greer at the NATO Advanced Study Institute on Syntheses of Instructional Sciences and Computing Science for Effective Instructional Computing Systems in 1990 in Calgary, Canada. It was during this meeting that I came to realize that Jim was one of those rare individuals that could help "translate" computer science…

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…