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Seth Elkin-Frankston; James McIntyre; Tad T. Brunyé; Aaron L. Gardony; Clifford L. Hancock; Meghan P. O'Donovan; Victoria G. Bode; Eric L. Miller – Cognitive Research: Principles and Implications, 2025
Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…
Descriptors: Group Dynamics, Military Personnel, Measures (Individuals), Computer Software
Cassandra Artman Collier; Anne L. Powell – Journal of Information Systems Education, 2024
As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…
Descriptors: Data Analysis, Information Systems, Educational Research, Data Collection
Chang Liu; Charles Downing – Journal of Information Systems Education, 2024
This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their…
Descriptors: Graduate Students, Program Effectiveness, Information Science, Management Information Systems
Leif Sundberg; Jonny Holmström – Journal of Information Systems Education, 2024
With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…
Descriptors: Artificial Intelligence, Conventional Instruction, Data Collection, Models
Ashley Metzger; Addison Duane; Amia Nash; Valerie Shapiro – International Journal of Education Policy and Leadership, 2024
Background: Knowledge brokering by intermediary organizations includes knowledge distillation processes (e.g., synthesis, translation). Aims and objectives: This article explores how an educational intermediary performs research distillation when creating virtual knowledge reservoirs for educators. Methods: The authors use qualitative data from…
Descriptors: Data Collection, Case Studies, Information Dissemination, Information Networks
Juan D’Brot; W. Chris Brandt – Region 5 Comprehensive Center, 2024
In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…
Descriptors: Educational Improvement, Data Collection, State Departments of Education, School Districts