The main purpose of this study is to develop a conceptual understanding of the irrational number of the square root of 2 ([square root]2 ). Participants in the study were 20 ninth-grade male students. Activity Theory was used as a framework to show the development of the conceptual understanding. Since this study was conducted during the COVID-19…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

To be literate in a society where the information shared online is often exploited, learners should be exposed to multiple aspects of contemporary predictive modeling. This article explores an activity in which grade 10 students learned how a famous AI algorithm (the Apriori algorithm) uses conditional probability to automate the process of…

Purpose: This study aims to analyse and evaluate the methodology followed by the Times Higher Education Impact Rankings (THE-IR), as well as the coverage obtained and the data offered by this ranking, to determine if its methodology reflects the degree of sustainability of universities, and whether their results are accurate enough to be used as a…

We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an undergraduate program is an ideal setting for interdisciplinary training in the intersection…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

The current data-centric business environment has seen an increasing demand for business students with knowledge and skills in the area of business analytics. This article presents the design and implementation of a foundation business analytics (BA) course for undergraduate business students who aspire to become data-literate professionals or…

In this comparative study, I examine principal data use in two sets of districts. One set of three districts has a district-wide focus on using data to improve instruction, and the other set, also with three districts, has a district-wide focus on analyzing disaggregated data by student demographic groups. Data sources include interviews with…

In addition to providing a set of techniques to analyze educational data, I claim that data science as a field can provide broader insights to education research. In particular, I show how the bias-variance tradeoff from machine learning can be formally generalized to be applicable to several prominent educational debates, including debates around…

The purpose of study was gain insight into pre-service teachers' experiences in using classroom data to make learning and teaching decisions. The qualitative study is based on the reflections and recommendations of three pre-service teachers' that participated in a data-driven decision-making intervention whilst on an immersive 10-week…

While universities routinely use student data to monitor and predict student performance, there has been limited engagement with student and staff views, social and ethical issues, policy development, and ethical guidance. We reviewed peer-reviewed and grey-literature articles of 2007 to 2018 describing the perspectives of staff and students in…

This article explores how making data playable, i.e. developing exploratory co-creation techniques that use elements of play and games to interpret small to mid-sized datasets beyond the current focus on visual evidence, can help a) promote creative data literacy in higher education, and b) expand existing definitions of data literacy. The article…

The aim of the paper is to diagnose the entrepreneurship competency levels among students to identify differences in competencies and their levels regarding gender, material status, and professional situation. In addition, the goal of the analysis is to indicate the competencies that need to be strengthened among individual groups of students. The…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

A total of 1023 selected articles published in 2016-2019 related to mobile learning were examined and classified according to the categories in this research: 40% of these articles used quantitative approaches, 18% of them used mixed, and 13% of them were literature reviews. The published studies were analyzed according to research model, sample…