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Stephen Downes – International Association for Development of the Information Society, 2023
Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…
Descriptors: Statistics Education, Data Analysis, Ethics, Data Use
Euler, Elias; Gregorcic, Bor – Physical Review Physics Education Research, 2023
Qualitative studies in the domain of physics education research have become more common in the last several decades. Methodologically, this has been marked by an expansion of the types of data collected in physics education research (PER): namely, in the use of individual and group interviews, problem-solving sessions, and classroom…
Descriptors: Physics, Science Instruction, Teaching Methods, Visual Aids
De Veaux, Richard; Hoerl, Roger; Snee, Ron; Velleman, Paul – Statistics Education Research Journal, 2022
Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the data, the deploying of sustainable solutions, and the communication of key findings for addressing the original problem. As such it spends less…
Descriptors: Holistic Approach, Data Analysis, Statistics Education, Teaching Methods
Quadir, Benazir; Chen, Nian-Shing; Isaias, Pedro – Interactive Learning Environments, 2022
The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…
Descriptors: Data, Educational Research, Educational Objectives, Data Analysis
Lewis, Norman P.; McAdams, Mindy; Stalph, Florian – Journalism and Mass Communication Educator, 2020
This syndicate offers four recommendations to help educators adjust curricula to accommodate the rapid integration of data into journalism. First, instruction in numeracy and basic descriptive statistics must be required as either modules in existing courses or as separate offerings. Second, students should be taught to avoid mistakes in…
Descriptors: Journalism, Data Analysis, Numeracy, Teaching Methods
Burian, Alexis N.; Zhao, Wufan; Lo, Te-Wen; Thurtle-Schmidt, Deborah M. – Biochemistry and Molecular Biology Education, 2021
To fully appreciate genetics, one must understand the link between genotype (DNA sequence) and phenotype (observable characteristics). Advances in high-throughput genomic sequencing technologies and applications, so-called "-omics," have made genetic sequencing readily available across fields in biology from applications in…
Descriptors: Genetics, Science Instruction, Teaching Methods, Biology
Stephens, Paul; Young, Jacob – Information Systems Education Journal, 2020
We describe a "Day of Giving" university fundraising event that can be used to introduce data visualization to undergraduate students. The project involves integrating data sources, creating a Tableau data model, and designing a heat map that can be embedded into a front-end website. Our activity provides opportunities to discuss various…
Descriptors: Data Analysis, Visualization, Experiential Learning, Learning Activities
Jones, Valerie K.; Johnson, Kate; Molskness, Hannah; Gandhi, Ronit; Zhou, Lilly – Journal of Advertising Education, 2022
This paper describes an advertising ethics course designed for first-year students of any major, written from the perspectives of both the course creator/instructor and the students who took the course and developed a workshop based around it. As educators, how do we help students learn and care about how their data is collected and used and…
Descriptors: Advertising, Ethics, Introductory Courses, Undergraduate Students
Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
Bozkurt, Aras; Sharma, Ramesh C. – Asian Journal of Distance Education, 2022
Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…
Descriptors: Learning Analytics, Teaching Methods, Learning Processes, Prediction
Blincoe, Sarai; Buchert, Stephanie – Psychology Learning and Teaching, 2020
The preregistration of research plans and hypotheses may prevent publication bias and questionable research practices. We incorporated a modified version of the preregistration process into an undergraduate capstone research course. Students completed a standard preregistration form during the planning stages of their research projects as well as…
Descriptors: Psychology, Teaching Methods, Research Problems, Research Design
Baumer, Benjamin S.; Garcia, Randi L.; Kim, Albert Y.; Kinnaird, Katherine M.; Ott, Miles Q. – Journal of Statistics and Data Science Education, 2022
We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum from top-to-bottom as our majors progress from our introductory courses to our…
Descriptors: Ethics, Statistics Education, Data Analysis, Teaching Methods
Moriña, Anabel – Educational Review, 2020
The aim of this paper is to identify and describe the key traits of research with life histories. Previous studies on disability and my own work conducting research with the life histories and university experiences of students with disabilities help to explain how these key characteristics manifest themselves in practice. There are six traits…
Descriptors: Students with Disabilities, Biographies, Teaching Methods, Research Methodology
National Forum on Education Statistics, 2024
The "Forum Guide to Data Literacy" is designed to help education agencies understand and build data literacy skills among various stakeholder groups such as administrators, teachers, students, parents and other caregivers, school board members, legislators, and community groups. This resource defines and discusses the importance of data…
Descriptors: Public Agencies, Statistics, Data Analysis, Statistics Education
Boenig-Liptsin, Margarita; Tanweer, Anissa; Edmundson, Ari – Journal of Statistics and Data Science Education, 2022
This article presents the Data Science Ethos Lifecycle, a tool for engaging responsible workflow developed by an interdisciplinary team of social scientists and data scientists working with the Academic Data Science Alliance. The tool uses a data science lifecycle framework to engage data science students and practitioners with the ethical…
Descriptors: Ethics, Statistics Education, Feminism, Interdisciplinary Approach