The use of artificial intelligence (AI) in higher education has mostly focused on issues associated with teaching and assessment. In this paper I used AI to support the analysis of data which consisted of public comments on a newspaper article. This small, low risk research was chosen to demonstrate the potential use of AI and how it may support…

Purpose: School principals are increasingly responsible for acting as instructional leaders, but research on data teams typically considers principals as secondary players responsible for ensuring that meetings occur but not necessarily for their quality. We investigated how elementary school principals in one district committed to data use…

Those asked to make valid decisions with data don't have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this…

Historic data in analog (or print) format is a valuable resource that is utilized by scientists in many fields. This type of data may be found in various locations on university campuses including offices, labs, storage facilities, and archives. This study investigates whether biological data held in one institutional university archives could be…

Vision classification tasks, a fundamental and transformative aspect of deep learning and computer vision, play a pivotal role in our ability to understand the visual world. Deep learning techniques have revolutionized the field, enabling unprecedented accuracy and efficiency in vision classification. However, deep learning models, especially…

Collecting data for the purpose of decision making has become an integral part of the landscape of education in the United States over the past decade. Many educators are swamped with such an overwhelming amount of information that it can be difficult to sort and analyze, leaving them floundering under wave after wave of data. The SWIS facilitator…

Mixed methods research collects, analyzes, and integrates rigorous qualitative and quantitative methods to gain a deeper understanding of a phenomenon than would be gained by using either method alone. Integration is one of the key features of mixed methods research and consists of mixing qualitative and quantitative research in a systematic way…

School districts have recognized the undeniable power of using data to enhance performance. As a result, teachers are now required to use data to prepare for critical state assessments and to improve district levels. These assessments are crucial in determining the school's rating by the state and can even result in a state takeover if scores are…

Amid the increasing reliance on digital tools and services in education, this article examines the datafication and commodification of student life in Denmark. We analyse the web and app (iOS and Android) versions of 45 tools and services that teachers in Danish public primary schools use as part of their teaching, the types of data generated by…

Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education,…

Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To include all evidence in one coherent analysis, we require methods to "map" the outcomes onto a single…

Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…

As Twitter's (or X's) influence permeates aspects of education, researchers must consider how to ethically and effectively leverage the unique types of data that this social media platform offers. This paper provides recommended methodological practice considerations for working with qualitative Twitter data toward the advancement of education…

The Teaching and Learning International Survey (TALIS) collects data from representative samples of teachers and principals across the world about their practices and work conditions, school and classroom contexts, and attitudes, motivation, and satisfaction with their profession and jobs. Given the growth of participating countries, the number of…

The current study presents a systematic review of teachers' data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various…