Problem decomposition into sub-problems or subgoals and recomposition of the solutions to the subgoals into one complete solution is a common strategy to reduce difficulties in structured problem solving. In this study, we use a datadriven graph-mining-based method to decompose historical student solutions of logic-proof problems into Chunks. We…

Real-world data are fundamental to modern teaching methodologies that aim to improve statistical knowledge and reasoning in students. Statistical information is encountered in everyday life, such as media articles and involves real-world contexts. However, information could be biased or (mis)represented and students should be concerned about the…

This research explores the perspectives of marketing students and educators about the Big Data courses in marketing education programs. It also examines drivers that predict interest on the part of marketing students in taking Big Data courses. Data was collected through interviews with 20 marketing educators, and a survey was completed by 480…

Students at all levels of education experience difficulties with the concepts of measurement uncertainties. One task that includes concepts of measurement uncertainties is a data comparison problem where students decide whether two datasets are in agreement or not--an authentic scientific practice. To aid students with these concepts and tasks,…

The contemporary Human activity utilizes huge volumes of digital data to solve efficiently multiple socio-economic, scientific and technical problems. Now the big data analysis is mainly oriented to the socioeconomic sphere with a goal to lift the profit. The science and technology to penetrate deeper in the nature of objects and systems under…

We provide a computational exercise suitable for early introduction in an undergraduate statistics or data science course that allows students to "play the whole game" of data science: performing both data collection and data analysis. While many teaching resources exist for data analysis, such resources are not as abundant for data…

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…

This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…

Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…

Understanding professional development is a key component in ensuring school improvement. This study examines the professional development experiences of 16 school leaders and staff members in the Northeast Region of the United States. This qualitative grounded theory study investigates the type of professional development experiences that result…

Purpose: The goal of this study is to explore how content creators engage in critical data literacies on TikTok, a social media site that encourages the creation and dissemination of user-created, short-form videos. Critical data literacies encompass the ability to reason with, critique, control, and repurpose data for creative uses. Existing work…

This paper describes the role of data and task context in young children's interpretation of and reasoning about data tables. A design-based descriptive study was conducted with fourteen 5-year-old children in their first year of formal schooling. A picture storybook provided the data context for a data modelling activity that focused on…

In Singapore, where primary and secondary students routinely top standardized worldwide mathematics examinations, a paradox emerges: when reaching university, many struggle to apply their skills critically in real-world contexts. This commentary examines the challenges and strategies involved in teaching quantitative reasoning (QR) to…

Many aspects of noticing in the classroom are tacitly understood by experienced educators. In this case study, we pair ecological and cognitive psychology with computer-augmented analysis of video data to try to better understand some of the tacit elements of educator noticing and decision-making. The ecological model of noticing views noticing as…

In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…