This article details an exploratory data analysis project using the Common Online Data Analysis Platform (CODAP) based on the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) four-part statistical problem-solving model. The project goal was to answer what similarities and differences exist within the school…

Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Preparing the new generation to be data-literate citizens is a pressing challenge, and some explorations have been made to cultivate K-12 students' data science skills and attitudes. However, there is a lack of instructional models to guide the design of data science programs in K-12 due to its complex and interdisciplinary nature as well as the…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

There are a variety of discrete facility location models that have practical relevance for operations management and management science courses. Integer linear programming (ILP) is the standard technique for solving such problems. An alternative approach that is often conceptually appealing to students is to pose the problem as one of finding the…

Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…

Effective learning outcome modeling is crucial to the success of learning evaluation in education. In the digital age, the movement towards online learning and computerized assessments has resulted in an explosion of structured and unstructured educational data (e.g., learners' problem-solving process data), which offers new opportunities for…

This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize…

This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…

Engaging in culturally responsive practices is considered best practice in classroom instruction, particularly within diverse schools, however, when making data-based decisions, there is little guidance for culturally responsive practitioners on how to engage in this work. This article introduces a model of culturally responsive data-based…

Computer science concepts have an important part in other subjects and thinking computationally is being recognized as an important skill for everyone, which leads to the increasing interest in developing computational thinking (CT) as early as at the comprehensive school level. Therefore, research is needed to have a common understanding of CT…

The present study examines the difficulties novice data modelers face when asked to provide a data model addressing a given problem. In order to map these difficulties and their causes, two short data modeling problems were given to 82 students who had completed an introductory course in database modeling. Both problems involve three entity sets…

In this paper, we describe a framework for data analysis that can be embedded into a base application. Since it is important to analyze the data directly inside the application where the data is entered, a tool that allows the scientists to easily work with their data, supports and motivates the execution of further analysis of their data, which…