In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…

Statistical data is used in the media and on online platforms, often with an interpretation that serves some commercial or political purpose. Primary preservice teachers must be able to understand statistical data and analyze it critically. Only in this way will they be able to contribute as future teachers to the development of a critical spirit…

The current paper investigates the structural validity of the Children's Concentration and Empathy Scale (CCES), which was designed based on Montessori's developmental theory to assess, using teacher ratings, the coherence of attention-related characteristics (concentration, empathy, and normalization) in children from 1.5 to 12 years old. The…

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…

All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…

Understanding and analyzing data is a crucial aspect of quantitative literacy in the 21st century, leading scholars and policy makers to push for more rigorous instruction in this area rooted in statistical investigation. In this study, we examine 144 upper-elementary mathematics lessons on data and statistics topics to assess the extent to which…

Understanding and analyzing data is a crucial aspect of quantitative literacy in the 21st century, leading scholars and policy makers to push for more rigorous instruction in this area rooted in statistical investigation. In this study, we examine 144 upper-elementary mathematics lessons on data and statistics topics to assess the extent to which…

Statistical literacy refers to two interrelated components: people's ability to interpret and critically evaluate statistical information, and their ability to discuss or communicate their reactions to statistical information. The ability to read and interpret graphical displays is part of statistical literacy because much of the statistical…

Topological data analysis (TDA) is a collection of powerful tools that can quantify shape and structure in data in order to answer questions from the data's domain. This is done by representing some aspect of the structure of the data in a simplified topological signature. In this article, we introduce two of the most commonly used topological…

For the least-squares analysis of data having multiple uncertain variables, the generally accepted best solution comes from minimizing the sum of weighted squared residuals over all uncertain variables, with, for example, weights in x[subscript i] taken as inversely proportional to the variance [delta][subscript xi][superscript 2]. A complication…

This paper describes two classes of advanced data mining methods that can obtain actionable insight from cooperative education data: text mining of job descriptions and graph mining of job interview data. While these methods are not new in general, they have not been widely used in co-operative education research. A technical overview of each…

This paper proposes a novel application of knowledge space theory for identifying discrepancies between the knowledge structure that experts expect students to have and the real knowledge structure that students demonstrate on tests. The proposed approach combines two methods of constructing knowledge spaces. The expected knowledge space is…

To learn with data, students need "data" to explore. This can be deceptive--data-rich experiences typically involve much more than a straightforward science lab. Solving real problems with data means identifying authentic questions that are meaningful to students and provide a foundation for deep inquiry. Such situations often lend…

Nitrogen- or phosphorus-based fertilizers, used in agriculture, can run off into nearby waterways during periods of heavy rain or high flow and cause harmful blooms (Paerl et al. 2016), low oxygen (Joyce 2000), and decreased biodiversity (Sebens 1994). Studies of the effects wetlands can have on water and habitat quality (Verhoeven and Meuleman…

These pages aim to explain and interpret why the late Mika Seppälä, a conformal geometer, proposed to model student study behaviour using concepts from conformal geometry, such as Riemann surfaces and Strebel differentials. Over many years Mika Seppälä taught online calculus courses to students at Florida State University in the United States, as…