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Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
McGee, Monnie – Journal of Statistics Education, 2019
In several sporting events, the winner is chosen on the basis of a subjective score. These sports include gymnastics, ice skating, and diving. Unlike for other subjectively judged sports, diving competitions consist of multiple rounds in quick succession on the same apparatus. These multiple rounds lead to an extra layer of complexity in the data,…
Descriptors: Data Use, Visualization, Interrater Reliability, Introductory Courses
Haymes, Tom – Current Issues in Education, 2021
The standards of educational information exchange are still firmly rooted in a Newtonian paradigm that emphasizes strict rules of information exchange. With the explosion of information since World War II, and especially its accessibility through the mechanism of the internet, this paradigm has become a barrier to effective exchanges of…
Descriptors: Social Networks, Information Dissemination, Information Systems, Access to Information
Decuypere, Mathias; Landri, Paolo – Critical Studies in Education, 2021
University rankings have become commonplace in higher education. Traditional quantified rankings do not merely measure educational performance: they equally grant status, enforce competition between institutions, and are emblematic for the ongoing capitalization of higher education. Drawing on the field of Science and Technology Studies, this…
Descriptors: Universities, Institutional Evaluation, Educational Quality, Institutional Characteristics
Yu, Chong Ho; Douglas, Samantha; Lee, Anna; An, Min – Practical Assessment, Research & Evaluation, 2016
This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…
Descriptors: Visualization, Item Response Theory, Sample Size, Correlation
Atapattu, Thushari; Falkner, Katrina; Tarmazdi, Hamid – International Educational Data Mining Society, 2016
With a goal of better understanding the online discourse within the Massive Open Online Course (MOOC) context, this paper presents an open source visualisation dashboard developed to identify and classify emergent discussion topics (or themes). As an extension to the authors' previous work in identifying key topics from MOOC discussion contents,…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
Killion, Patrick J.; Page, Ian B.; Yu, Victoria – Scholarship and Practice of Undergraduate Research, 2019
The University of Maryland--College Park initiated the First-Year Innovation & Research Experience (FIRE) in 2014 to provide authentic faculty-led research experiences, mentorship, and accelerated opportunity for first-year students from a wide range of academic backgrounds. To annually provide more than 600 new FIRE students with an authentic…
Descriptors: College Freshmen, Student Research, Data Analysis, Visualization
Emery, Mary; Higgins, Lorie; Chazdon, Scott; Hansen, Debra – Journal of Extension, 2015
A mind mapping approach to evaluation called Ripple Effects Mapping (REM) has been developed and used by a number of Extension faculty across the country recently. This article describes three approaches to REM, as well as key differences and similarities. The authors, each from different land-grant institutions, believe REM is an effective way to…
Descriptors: Program Evaluation, Evaluation Methods, Program Effectiveness, Extension Education
Henshaw, Alexis Leanna; Meinke, Scott R. – Journal of Political Science Education, 2018
While data analysis and the related skills of data management and data visualization are important skills for undergraduates in the field of political science, the process of learning these skills can also be used to develop critical thinking, encourage active and collaborative learning, and to apply knowledge gained in the classroom. Drawing on…
Descriptors: Undergraduate Students, Data Analysis, Visualization, Active Learning
Gee, Kevin A. – American Journal of Evaluation, 2014
The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…
Descriptors: Longitudinal Studies, Data Analysis, Statistical Studies, Program Evaluation
Greatorex, Jackie; Rushton, Nicky; Coleman, Tori; Darlington, Ellie; Elliott, Gill – Cambridge Assessment, 2019
A curriculum map is a visualisation of relationships within and between a curriculum or curricula. Curriculum mapping refers to the method for creating and using the curriculum map, however this term is used broadly and encompasses a variety of methodological approaches. Often, researchers in the field of curriculum studies conduct curriculum…
Descriptors: Comparative Analysis, Visualization, Curriculum, Maps
Ochoa, Xavier; Suthers, Dan; Verbert, Katrien; Duval, Erik – Journal of Learning Analytics, 2014
Analyzing a conference, especially one as young and focused as LAK, provides the opportunity to observe the structure and contributions of the scientific community around it. This work will perform a Scientometric analysis, coupled with a more in-depth manual content analysis, to extract this insight from the proceedings and program of LAK 2013.…
Descriptors: Data Analysis, Data Collection, Conferences (Gatherings), Content Analysis
Mills, Robert J.; Chudoba, Katherine M.; Olsen, David H. – Journal of Information Systems Education, 2016
The term data scientist has only been in common use since 2008, but in 2016 it is considered one of the top careers in the United States. The purpose of this paper is to explore the growth of data science content areas such as analytics, business intelligence, and big data in AACSB Information Systems (IS) programs between 2011 and 2016. A…
Descriptors: Information Systems, Information Science Education, Statistical Analysis, Data Analysis
Adkins, Joni K. – Information Systems Education Journal, 2016
The growing popularity of data visualization due to increased amounts of data and easier-to-use software tools creates an information literacy skill gap for students. Students in an Information Technology Management graduate course were exposed to data visualization not only through their textbook reading but also through a data visualization…
Descriptors: Data, Visualization, Assignments, Computer Software
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