In this study, we investigated mathematics teacher's noticing of students' thinking in the context of mathematical modeling activities (MEAs) related to statistics. One middle-school mathematics teacher participated in the study, which adopted a case study design. Data were collected through interviews with the teacher based on video recordings of…

The year 2020 saw the outbreak of the COVID-19 pandemic that not only had wide-reaching social and economic consequences but also put healthcare systems under stress. Strategies for coping with the virus depended heavily on the interpretation of data. This article uses information from a UK upper tier local authority to examine how closely the…

We report a study on mathematical literacy with special emphasis on health literacy. In particular, we identify and characterize the mathematical competencies that a citizen needs to interpret the official information on the COVID-19 pandemic as experienced in Mexico. To achieve this, we analyze the daily reports on the pandemic issued by the…

This article explores 6th-grade students' modelling with data in generating models for selecting an Australian swimming team for the (then) forthcoming 2016 Olympics, using data on swimmers' times at various previous events. We propose a modelling framework comprising four components: working in shared problem spaces between mathematics and…

Recent research has shown that young children are capable of engaging in data modeling and making informed judgments, an aspect of the mathematics curriculum not previously considered integral to early numeracy. In an Australian study, a sample of 21 highly able Grade 1 students was engaged in a series of investigations where they developed their…

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

This study examined how 12- and 13-year-old students' mathematics and science background knowledge affected line graph interpretations and how interpretations were affected by graph question levels. A purposive sample of 14 students engaged in think aloud interviews while completing an excerpted Test of Graphing in Science. Data were…

Papini and Pellegrini (Papini, M. R., & Pellegrini, S. "Scaling relative incentive value in consummatory behavior." "Learning and Motivation", in press) observed that, within limits, the level of consummatory responding of rats exposed to incentive downshifts in the concentration of sucrose solutions was similar when the ratio of test/training…

In this article, the authors present the results of a research study in which they used two national datasets to construct and examine a model that estimates relative faculty instructional costs for specific undergraduate degree programs and also identifies differences in these costs by region and institutional type. They conducted this research…