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Bartholomew, Scott R.; McGraw, Tim; Fauber, Daphne; Charlesworth, Jon; Weitlauf, John – Technology and Engineering Teacher, 2020
Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields…
Descriptors: Sanitation, Water, Agriculture, High School Students
Taub, Michelle; Azevedo, Roger – New Directions for Teaching and Learning, 2023
The goal of this chapter is to propose a cyclical process of how teachers can use multimodal multichannel data of cognitive, affective, metacognitive, motivational, and social processes to assist with the understanding of their own and their students' self-regulated learning (SRL), and their subsequent instructional decision making. What…
Descriptors: Independent Study, Learning Processes, Instructional Design, Decision Making
Kahn, Jennifer; Jiang, Shiyan – Learning, Media and Technology, 2021
We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using…
Descriptors: Visualization, Data Use, Data Interpretation, Decision Making
Blair, Morgan; Zanidean, Alex – Strategic Enrollment Management Quarterly, 2020
Data interpretation can be difficult. Data visualization techniques from the manufacturing industry make interpretation easier. Control charts display trends in context, so it is clear when performance is truly changing and when it is not. Decision makers know when to act, when to maintain, and when to celebrate. This article discusses the use of…
Descriptors: Enrollment Management, Decision Making, Data Interpretation, Visualization
Jason Robert Murphy – ProQuest LLC, 2018
Implemented in 2013, the Local Control Funding Formula (LCFF) requires Local Education Agencies (LEA's) to engage in a continuous improvement process that identifies actions that extend and improve services for targeted student groups. The vision of the LCFF is that all stakeholder groups including Staff (certificated, classified, management and…
Descriptors: Data, Visualization, Stakeholders, Access to Information
Jeyaraj, Anand – Journal of Information Systems Education, 2019
Responding to the industry need for professionals to employ data-driven decision-making, educational institutions offer courses in business analytics (BA). Since BA professionals require a unique set of skills different from those found in specific business disciplines, a pedagogical framework to impart such knowledge and skills was developed. The…
Descriptors: Decision Making, Data Analysis, Visualization, Data Interpretation
Bowers, Alex J.; Krumm, Andrew E. – Information and Learning Sciences, 2021
Purpose: Currently, in the education data use literature, there is a lack of research and examples that consider the early steps of filtering, organizing and visualizing data to inform decision-making. The purpose of this study is to describe how school leaders and researchers visualized and jointly made sense of data from a common learning…
Descriptors: Evidence Based Practice, Data Use, Decision Making, Visualization
Albo, Laia; Hernandez-Leo, Davinia – IEEE Transactions on Learning Technologies, 2021
This article presents an evaluation of edCrumble, a blended learning authoring tool for teachers. The tool visually represents learning designs and integrates data analytics to scaffold teacher design decisions. In addition to assessing the usability of edCrumble using Usability Metric for User Experience questionnaire, analyses of participant…
Descriptors: Programming, Blended Learning, Teaching Methods, Instructional Design
Kennedy-Clark, Shannon; Galstaun, Vilma; Reimann, Peter; Martyn, Taylor; Williamson, Kiatin; Weight, Jessica – Australian Journal of Teacher Education, 2020
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…
Descriptors: Data Analysis, Preservice Teachers, Student Attitudes, Decision Making
Barneva, Reneta P.; Brimkov, Valentin E.; Walters, Lisa M. – Journal of Educational Technology Systems, 2018
In all areas of human activity, decision-making based on data analysis is very important. As the availability of data grows, it becomes critical to educate not only traditional students but also those individuals who are now in the workforce, as many of them are expected to manage the complex data streams and to provide evidence and guidance for…
Descriptors: Decision Making, Data Analysis, Visualization, Measurement Techniques
Alhadad, Sakinah S. J. – Journal of Learning Analytics, 2018
Understanding human judgement and decision making during visual inspection of data is of both practical and theoretical interest. While visualizing data is a commonly employed mechanism to support complex cognitive processes such as inference, judgement, and decision making, the process of supporting and scaffolding cognition through effective…
Descriptors: Visualization, Data Analysis, Evaluative Thinking, Statistical Inference
Cunningham-Nelson, Samuel; Baktashmotlagh, Mahsa; Boles, Wageeh – IEEE Transactions on Education, 2019
Contribution: An automated methodology that provides visualizations of students' free text comments from course satisfaction surveys. Focusing on sentiment, these visualizations reveal learning and teaching aspects of the course that either may require improvement or are performing well. They provide educators with a simple, systematic way to…
Descriptors: Student Attitudes, Visualization, Course Evaluation, Teaching Methods
Crick, Ruth Deakin; Knight, Simon; Barr, Steven – Journal of Learning Analytics, 2017
Central to the mission of most educational institutions is the task of preparing the next generation of citizens to contribute to society. Schools, colleges, and universities value a range of outcomes--e.g., problem solving, creativity, collaboration, citizenship, service to community--as well as academic outcomes in traditional subjects. Often…
Descriptors: Educational Improvement, Holistic Approach, Data Collection, Data Analysis
Killen, Catherine P. – European Journal of Engineering Education, 2015
This paper outlines a novel approach to engineering education research that provides three dimensions of learning through an experiential class activity. A simulated decision activity brought current research into the classroom, explored the effect of experiential activity on learning outcomes and contributed to the research on innovation decision…
Descriptors: Engineering Education, Educational Innovation, Educational Research, Experiential Learning
Hillaire, Garron; Rappolt-Schlichtmann, Gabrielle; Ducharme, Kim – Journal of Learning Analytics, 2016
Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise…
Descriptors: Visual Learning, Educational Theories, Visualization, Computer Graphics
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