As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Data-driven marketing analytics courses are integral to modern business management degrees in universities, yet many graduates focus solely on single, separated data analysis techniques during their learning process, hindering effective integration and practical performance. This study proposes that employing the Fishbowl method, which divides…

The practice of statistics has the power to motivate and support learning across the STEM (Science, Technology, Engineering, and Mathematics) disciplines. When connected with meaningful science contexts, statistical problem solving through the collection of data and subsequent data analysis, supported by contemporary graphing technology, presents…

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…

Solving problems in educational settings, as in daily-life scenarios, involves constantly assessing one's own confidence in each considered solution. Metacognitive research has exposed cues that may bias confidence judgments (e.g., familiarity with question terms). Typically, metacognitive research methodologies require examining misleading cues…

The advancement of technology has led to a growing interest in assessing scientific inquiry within digital platforms. This shift towards dynamic and interactive inquiry assessments enables researchers to investigate not only the accuracy of student responses ("product data") but also their steps and actions leading to those responses…

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…

Interactive tasks designed to elicit real-life problem-solving behavior are rapidly becoming more widely used in educational assessment. Incorrect responses to such tasks can occur for a variety of different reasons such as low proficiency levels, low metacognitive strategies, or motivational issues. We demonstrate how behavioral patterns…

This study investigated how one's problem-solving style impacts his/her problem-solving performance in technology-rich environments. Drawing upon experiential learning theory, we extracted two behavioral indicators (i.e., planning duration for problem solving and human-computer interaction frequency) to model problem-solving styles in…

In this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

In 2020, the COVID-19 pandemic urged authorities to share quantitative information such as infection and death rates. One way of disseminating was through graphs, maps, and diagrams. Such data visualizations communicate numeric data in compact ways, but also require a particular mathematical literacy from readers. We conceptualized this particular…

Although culturally responsive mathematics teaching is important, post-secondary education for preservice teachers (PTs) does not typically lead to learning opportunities for them to use mathematics to recognize the roles of social agents. To address this issue, we created a culturally responsive mathematical modeling task in which we invited PTs…

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…

This is the first of four columns by Tim Erikson which introduces us to the Common Online Data Analysis Platform (CODAP). CODAP is a free, web-based software tool that your students can use for many types of tasks. This first column shows how CODAP can be used for mathematical modelling and where it might fit with the "Australian Curriculum:…

In this paper, we investigate an interesting question that came up when reading a problem in a school textbook: What happens to the variance of a dataset in the case of changing one single data point, and why? Some of the answers are not surprising but here we find the full answer and demonstrate the understanding of it suitable for school…