Preparing data-literate citizens and supporting future generations to effectively work with data is challenging. Engaging students in Knowledge Building (KB) may be a promising way to respond to this challenge because it requires students to reflect on and direct their inquiry with the support of data. Informed by previous studies, this research…

Research data management is essential for high-quality reproducible research, yet relatively little is known about how research data management is practiced by graduate students in Civil and Environmental Engineering (CEE). Prior research suggests that faculty in CEE delegate research data management to graduate students, prompting this…

Despite the growing interest in using multimodal data to analyse students' actions in Computers-Supported Collaborative Learning (CSCL) settings, studying teacher's orchestration load in such settings remains overlooked. The notion of classroom orchestration, and orchestration load, offer a lens to study the implications of increasingly complex…

Computer-mediated social learning contexts have become increasingly popular over the last few years; yet existing models of students' cognitive-affective states have been slower to adopt dyadic interaction data for predictions. Here, we explore the possibility of capitalizing on the inherently social component of collaborative learning by using…

Collaborative staff development in education is the vehicle to student success, and research shows that the closer professional learning is to daily practice, the more meaningful and impactful it will be. Written with deep respect for the work educators do in their classrooms each day, this practical resource illustrates the importance of…

Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…

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…

Actionability is a critical issue in learning analytics for driving impact in learning, bridging the gap between insights and improvement. This dissertation places actionability at the forefront, integrating it throughout the learning analytics process to fully leverage its potential. The study involves designing, developing, and implementing…

Statistical competitions like ASA DataFest and the Women in Data Science (WiDS) Datathon give students valuable experience working with real, challenging data. By participating, students practice important statistics and data science skills including data wrangling, visualization, modeling, communication, and teamwork. However, while advanced…

The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated specific advantages of multiple modalities versus a single modality, especially combined…

Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes.…

Incorporating non-verbal data streams is essential to understanding the dynamics of interaction within collaborative learning environments in which a variety of verbal and non-verbal modes of communication intersect. However, the complexity of non-verbal data -- especially gathered in the wild from collaborative learning contexts -- demands…

Many higher education institutions have responded to the significant shortage of professionals with strong analytical expertise by offering graduate programs in business analytics and data science. These programs are typically designed to be practitioner focused and many of them offer a Capstone course that gives students the opportunity to…

In order to study the manifestation of data sense and identify ways of thinking about variability in authentically realistic problems in a group of Chilean fifth-grade students, a lesson plan was designed and implemented, within the framework of statistical literacy and using the "lesson study" modality, in which students were urged to…

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…