Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…

Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…

The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

Abilities to interpret, analyze, and report data are in-demand job skills that many colleges and universities struggle to incorporate into the curriculum. The client-based project outlined in this study examines the experiential learning pedagogy used to teach students media analytics. This semester-long project encourages students to complete a…

One of the challenges that science teachers face is the lack of strategy/method to train students in data collection and developing analytical skills, which are pre-requisites to resolve socio-scientific problems and an important element in scientific literacy. In this activity, the SWOT analysis proposed by the Stanford Research Institute in the…

Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…

Teachers form expectations that can influence their students' performance, and there are a variety of ways these expectations can be communicated. In the current study, we tested a novel method for communicating expectations via examples of student work--examples that contain basic, entry-level work and communicate low, but manageable expectations…

Purpose: This study aims to explore the findings related to data literacy skills for students to succeed in the digital age labor market and the role of university-industry collaborations (UICs) in the co-design and co-delivery of curriculum for the development of students' data literacy. Design/methodology/approach: The study uses an…

This paper addresses the topical issue of searching for optimum technology for fostering professional competencies in a target audience of business informatics students. The authors discuss the relevance of using the competency-based approach in the context of pedagogical goalsetting. The work describes the key stages in a study that involved…

With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and…

This paper analyzes data from Native American students' attainment in a first-semester Spanish language course at an indigenous-serving institution before, during, and after the pandemic. The gap between Native American and non-Native American students increased during the first post-pandemic semester to the point that just one out of 11 Native…

It is unclear whether the data visualization skills possessed by data-centric practitioners reflect recent advances in computing systems and visual design principles, and their role in generating relevant and insightful output to support decision-making. In this study, the author presents a curriculum designed for teaching basic and advanced…

In the data science courses at the University of British Columbia, we define data science as the study, development and practice of reproducible and auditable processes to obtain insight from data. While reproducibility is core to our definition, most data science learners enter the field with other aspects of data science in mind, for example…

As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model…