Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

The field of "learning design" studies how to support teachers in devising suitable activities for their students to learn. The field of "learning analytics" explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and…

This paper proposes the theoretical context for a course development framework to address the specific needs and challenges of teaching and learning in interdisciplinary studies (IDS). User-centred design (UCD) principles are used for this development process. Traditional course development frameworks provide a helpful guide in terms of setting…

In the era of big data, many business organizations consider data analytics skills as important criteria in the acquisition of qualified applicants. As numerous managerial decisions in the field of marketing are becoming evidence-based, business schools have integrated case studies about different stages of data analytics such as problem…

In this article, the authors introduce the "Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education" report. This report, which was published by the American Statistical Association (ASA) and endorsed by the National Council of Teachers of Mathematics…

Activity Theory (AT) is increasingly employed as a lens to guide data analysis in information systems (IS) studies. The theory is also applied to assess and evaluate information systems and technologies (IS/IT) in organisations. Even though its popularity continues to increase in both business and academic domains, there is no formal or assessment…

To learn with data, students need "data" to explore. This can be deceptive--data-rich experiences typically involve much more than a straightforward science lab. Solving real problems with data means identifying authentic questions that are meaningful to students and provide a foundation for deep inquiry. Such situations often lend…

Educators are tasked with continually updating course objectives, content, assignments, and assessment to meet model curriculum guidelines. IS2020 proposes program level outcomes for required and elective areas. Two elective areas in IS2020 are Data and Business Analytics and Data and Information Visualization. IS2020 details 14 program level…

This article presents the Data Science Ethos Lifecycle, a tool for engaging responsible workflow developed by an interdisciplinary team of social scientists and data scientists working with the Academic Data Science Alliance. The tool uses a data science lifecycle framework to engage data science students and practitioners with the ethical…

A prominent goal of colleges and universities today is to enact data-driven teaching and learning. Faculty clearly play a key role, and yet they tend to have limited time, a lack of training in assessment or education research, and few incentives for engaging in this work. We describe a framework designed to address the practical and cultural…

Nowadays, the virtual learning environment has become an ideal tool for professional self-development and bringing courses for various learner audiences across the world. There is currently an increasing interest in researching the topic of learner dropout and low completion in distance learning, with one of the main concerns being elevated rates…

With the emerging use of analytics tools and methodologies in marketing, marketing educators have provided students training and experiences beyond the soft skills associated with understanding consumer behavior. Previous studies have only discussed how to apply analytics in course designs, tools, and related practices. However, there is a lack of…

Responding to the industry need for professionals to employ data-driven decision-making, educational institutions offer courses in business analytics (BA). Since BA professionals require a unique set of skills different from those found in specific business disciplines, a pedagogical framework to impart such knowledge and skills was developed. The…

Currently, much research on cognitive diagnostic assessment (CDA) focuses on the development of statistical models estimating individual students' attribute profiles. However, little is known about how to communicate model-generated statistical results to stakeholders, and how to translate formatively diagnostic information into teaching…

An important goal in the design and development of Intelligent Tutoring Systems (ITSs) is to have a system that adaptively reacts to students' behavior in the short term and effectively improves their learning performance in the long term. Inducing effective pedagogical strategies that accomplish this goal is an essential challenge. To address…