Preparing teacher candidates to analyze achievement data is necessary to develop the understanding of how academic data is collected and used to inform instruction. Collecting achievement data in the area of literacy includes a variety of assessments focused on reading and writing. A critical component of analyzing data involves working in…

We present a two-week active learning chemical engineering hackathon event specifically designed to teach undergraduate chemical engineering students of any skill level data science through Python and directly apply this knowledge to a real problem provided by industry. The event is free and optional to the students. We use self-evaluation surveys…

Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…

This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a…

Training programs for statisticians and data scientists in healthcare should give greater importance to fostering inductive reasoning toward developing a mindset for optimizing Big Data. This can complement the current predominant focus on the hypothetico-deductive reasoning model, and is theoretically supported by the constructivist philosophy…

We present a critical perspective on the current state of research on educational dialogues, within and without Computer-Supported Collaborative Learning environments, in order to propose research perspectives in the intersection of these two domains. Our main proposal is that in order to integrate different types of human or machine analyzed data…

In practical work focussing on conceptual development, students spend valuable in-class time on collecting data rather than making sense out of it. This provides a barrier to learning about the targeted concept. To address this problem, we developed an approach that we coin "collaborative data collection." Using a practical on the topic…

Teacher professional development (PD) that supports the emergence of professional learning communities (PLCs) is effective for teachers' learning and instructional improvement. Our work focuses on supporting the emergence of online PLCs and an emergent issue in this work is how to maintain the quality of teachers' experiences in online PLCs when…

This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis,…

The usefulness of the online Skype system for qualitative data collection has been well documented, but its application in qualitative data analysis has been largely ignored. This article provides insight into the use of Skype in the context of interdisciplinary team research, with a focus on the analytical phase of a qualitative investigation.…

This review explores the integration and effects of the Internet of Things (IoT) in education, highlighting its importance in transforming traditional teaching and learning techniques. It examines the early uses and historical growth of IoT, its development, and the turning points in its adoption. It explores IoT platforms, tools, and technologies…

This book highlights the importance of design in computer-supported collaborative learning (CSCL) by proposing data-driven design and assessment. It addresses data-driven design, which focuses on the processing of data and on improving design quality based on analysis results, in three main sections. The first section explains how to design…

Data literacy is a growing area of focus across multiple disciplines in higher education. The dominant forms of introduction focus on computational toolchains and statistical ways of knowing. As data driven decision-making becomes more central to democratic processes, a larger group of learners must be engaged in order to ensure they have a seat…

In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…

Using assignments drawn from a first-year composition course that centers the Southern Life Histories Collection, part of the New Deal's Federal Writers' Project, this paper argues for a pedagogical approach that teaches students digital literacy through archival rhetorics by converting archival texts into data.