This study probed the conceptualization of (in)authenticity in teaching and the way it could be enacted in pedagogical practices. The participants were a purposive sample of 20 Iranian university teachers. Data were collected using in-depth interviews, field notes, and observation. The collected data were analyzed through the lens of hermeneutic…

The constructs that currently animate today's dispositions movement are grit and growth mindset. However, the evidence for the reliability and instructional uses of such noncognitive factors in K-12 schools--and of the surveys and tools that attempt to measure them--is thin. After a look at the "logic of assessment" with its focus on…

This paper presents a class case study of an assignment that asked students to use a Twitter follower report to design a Twitter advertising campaign. The purpose of this case study is to immerse students in a real social media environment and help them become familiar with analyzing social media data to develop advertising campaigns. Students'…

We still know relatively little about how researchers use qualitative data analysis software (QDAS) such as ATLAS.ti and NVivo. We conducted a discourse analysis of 763 empirical articles published from 1994 to 2013 that explored the language used by researchers when reporting QDAS use. We found that most researchers provided few details of their…

A prominent goal of colleges and universities today is to enact data-driven teaching and learning. Faculty clearly play a key role, and yet they tend to have limited time, a lack of training in assessment or education research, and few incentives for engaging in this work. We describe a framework designed to address the practical and cultural…

The growing use of machine learning for the data-driven study of social issues and the implementation of data-driven decision processes has required researchers to re-examine the often implicit assumption that datadriven models are neutral and free of biases. The careful examination of machine-learned models has identified examples of how existing…

A driving factor in designing interactive museum exhibits to support simultaneous users is that visitors learn from one another via observation and conversation. Researchers typically analyze such collaborative interactions among museumgoers through manual coding of live- or video-recorded exhibit use. We sought to determine how log data from an…

According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the…

Members of the Data Science Program at George Washington University (GWU) designed and implemented a tuition-free two-week summer camp at GWU for high-school students from the Washington Metro Area. The United States Department of Agriculture (USDA) Office of the Chief Information Officer and his staff were our main partners in the project. The…

Peter Dunn and Margaret Marshman present the second of their data files articles in which they discuss the statistical investigation cycle which describes the whole process of conducting a statistical research study. [For "The Data Files: A Series of Articles to Support Mathematics Teachers to Teach Statistics," see EJ1259108.]

The use of open textbooks in universities is according to some organisations changing the higher education landscape and is promising for the mainstream adoption of OER. The aim of this paper is to analyse authors' views of agency and empowerment when they plan, create and reflect on their open textbooks, their teaching and students' learning.…

The Canvas Learning Management System (LMS) is used in thousands of universities across the United States and internationally, with a strong and growing presence in K-12 and higher education markets. Analyzing the development of the Canvas LMS, we examine 1) 'frictionless' data transitions that bridge K12, higher education, and workforce data 2)…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

Large-scale assessment programs, such as the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS), employ item response theory (IRT) and marginal estimation methods to estimate student proficiency in specific subjects such as mathematics, science, or reading. Each of these…

This study aims to explore the extent of intergenerational social mobility in the United States for the population as a whole, as well as differentiated by gender and race/ethnicity. Study of intergenerational social mobility is important because it shows whether individuals can prosper in a society regardless of their socioeconomic background, as…