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Showing 1 to 15 of 58 results Save | Export
Louie, Josephine; Fagan, Emily; Stiles, Jennifer; Roy, Soma; Chance, Beth – Educational Leadership, 2023
Students need "critical data literacy" skills to help make sense of the multitude of information available to them, especially as it relates to high-stakes issues of social justice. The authors describe two curriculum modules they developed--one on income equality, one on immigration--that help students learn to analyze data in order to…
Descriptors: Social Justice, Data, Multiple Literacies, Critical Theory
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Silvia-Jessica Mostacedo-Marasovic; Cory T. Forbes – International Journal of Sustainability in Higher Education, 2024
Purpose: A faculty development program (FDP) introduced postsecondary instructors to a module focused on the food-energy-water (FEW) nexus, a socio-hydrologic issue (SHI) and a sustainability challenge. This study aims to examine factors influencing faculty interest in adopting the instructional resources and faculty experience with the FDP,…
Descriptors: Faculty Development, Learning Modules, Program Evaluation, Program Attitudes
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James J. Pomykalski – Information Systems Education Journal, 2023
Blended learning, which is the "thoughtful fusion of face-to-face and online learning experiences" (Garrison & Vaughan, 2008), is a pedagogical paradigm used in courses across numerous disciplines. In this paper, the use of LinkedIn Learning modules as the primary technological component is described; the focus of this first-time use…
Descriptors: Social Media, Blended Learning, Teaching Methods, Learning Modules
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Md. Yunus Naseri; Caitlin Snyder; Katherine X. Perez-Rivera; Sambridhi Bhandari; Habtamu Alemu Workneh; Niroj Aryal; Gautam Biswas; Erin C. Henrick; Erin R. Hotchkiss; Manoj K. Jha; Steven Jiang; Emily C. Kern; Vinod K. Lohani; Landon T. Marston; Christopher P. Vanags; Kang Xia – IEEE Transactions on Education, 2025
Contribution: This article discusses a research-practice partnership (RPP) where instructors from six undergraduate courses in three universities developed data science modules tailored to the needs of their respective disciplines, academic levels, and pedagogies. Background: STEM disciplines at universities are incorporating data science topics…
Descriptors: Data Science, Courses, Research and Development, Theory Practice Relationship
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Victoria L. Cross; Megan N. Imundo; Courtney M. Clark; Melissa Paquette-Smith – Psychology Learning and Teaching, 2024
Learning to interpret visual representations of data is an important step towards becoming an informed consumer of research. The current study assesses the effectiveness of two versions of a scaffolded online module in improving students' ability to identify main effects and interactions in 2 × 2 factorial designs. Across two experiments (N =…
Descriptors: Undergraduate Students, Cooperative Learning, Statistics Education, Psychology
Hollylynne S. Lee; Emily P. Thrasher; Matt Grossman; Gemma F. Mojica; Bruce Graham; Adrian Kuhlman – Grantee Submission, 2023
This paper presents the design of an innovative platform to support teachers' personalized learning related to teaching statistics and data science in grades 6-12 (http://instepwithdata.org). Through a study of 32 pilot users, the authors describe how teachers utilized supports such as personalization surveys, tracking of progress on a dashboard,…
Descriptors: Secondary School Teachers, Faculty Development, Statistics Education, Data Science
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Holly Golecki; Joe Bradley – Biomedical Engineering Education, 2024
Biomedical engineering capstone design courses provide a salient opportunity to discuss ethical considerations in engineering. As technology and society develop and change, new challenges constantly arise related to how society and technology inform each other. In this space, ethical training for engineering students is critically important for…
Descriptors: Experiential Learning, Decision Making, Ethics, Capstone Experiences
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Ian Thacker; Rebecca Schroeder; Sara Shields-Menard; Nickolas Goforth – International Journal of Science and Mathematics Education, 2025
To create opportunities for meaningful applications of data science for diverse students, we developed and implemented an online learning module focused on engaging students at a Hispanic Serving Institution (HSI) in an analysis of authentic soil data. Development of the module occurred over three design iterations involving interviews with 10…
Descriptors: Hispanic American Students, Minority Serving Institutions, Data Science, Undergraduate Students
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Smeaton, Alan F. – Health Education & Behavior, 2023
Many universities have wellness programs to promote overall health and well-being. Using students' own personal data as part of improving their own wellness would seem to be a natural fit given that most university students are already data and information literate. In this work, we aim to show how the interplay between health literacy and data…
Descriptors: Universities, Health Education, Digital Literacy, Multiple Literacies
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Sickler, Jessica; Bardar, Erin; Kochevar, Randy – Journal of College Science Teaching, 2021
Data literacy, or students' abilities to understand, interpret, and think critically about data, is an increasing need in K-16 science education. Ocean Tracks College Edition (OTCE) sought to address this need by creating a set of learning modules that engage students in using large-scale, professionally collected animal migration and physical…
Descriptors: Information Literacy, Data Analysis, Undergraduate Students, Scoring Rubrics
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Mark Matthew Buckman; Kathleen Lynne Lane; David James Royer; Eric Alan Common; Wendy Peia Oakes; Amy Briesch; Sandra Chafouleas; Rebecca Sherod; Paloma Pérez; Emily Iovino; Grant Allen; Arabiye Artola Bonanno; Nathan Allen Lane – Education and Treatment of Children, 2024
In this article, we present findings from our first iterative design study for Project ENHANCE to share our findings as well as provide an exemplar for others engaged in design inquiry. In particular, we explain how we used a data-informed design process with district partners to determine content and features of three foundational professional…
Descriptors: Design, Data Use, Decision Making, Multi Tiered Systems of Support
National Centre for Vocational Education Research (NCVER), 2017
This publication presents estimates of apprentice and trainee activity in Australia for the September quarter 2016. Highlights include: (1) In-training as at 30 September 2016--There were 278,500 apprentices and trainees in-training as of 30 September 2016, a decrease of 5.7% from 30 September 2015; (2) Quarterly training activity--In the…
Descriptors: Vocational Education, Statistical Data, Apprenticeships, Trainees
National Centre for Vocational Education Research (NCVER), 2017
Apprentice and trainee data are reported by the State and Territory Training Authorities to NCVER on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. NCVER…
Descriptors: Vocational Education, Statistical Data, Apprenticeships, Trainees
National Centre for Vocational Education Research (NCVER), 2017
This document covers the data terms used in publications sourced from the National Apprentice and Trainee Collection and their associated data tables. The primary purpose of this document is to assist users of the publications to understand the specific data terms used within them. Terms are listed in alphabetical order with the following…
Descriptors: Vocational Education, Statistical Data, Apprenticeships, Trainees
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Wilson, Anna; Watson, Cate; Thompson, Terrie Lynn; Drew, Valerie; Doyle, Sarah – Teaching in Higher Education, 2017
Learning analytic implementations are increasingly being included in learning management systems in higher education. We lay out some concerns with the way learning analytics--both data and algorithms--are often presented within an unproblematized Big Data discourse. We describe some potential problems with the often implicit assumptions about…
Descriptors: Educational Research, Data Collection, Data Analysis, Integrated Learning Systems
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