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Wook, Muslihah; Ismail, Suhaila; Yusop, Nurhafizah Moziyana Mohd; Ahmad, Siti Rohaidah; Ahmad, Arniyati – Education and Information Technologies, 2019
Previous studies on educational data mining (EDM) acceptance were focused on antecedents that were adopted from various models and theories. However, the ways in which such antecedents became the most important tools for educational improvement have not been researched in detail. This study aims to identify the priority antecedents of EDM…
Descriptors: Data Collection, Data Analysis, Educational Improvement, Undergraduate Students
Lin, Pei-Ying; Lin, Yu-Cheng – Policy Futures in Education, 2019
Over the decades, it is evident that exceptional learners have been excluded from participating in international assessments such as OECD's PISA (Programme for International Student Assessment) due to their disabilities. Drawing on the interdisciplinary theories and perspectives of educational assessment, measurement, and early childhood special…
Descriptors: International Assessment, Early Childhood Education, Disabilities, Educational Assessment
Demchak, MaryAnn; Sutter, Chevonne – Education and Training in Autism and Developmental Disabilities, 2019
Abstract: This study evaluated whether or not teachers of students with severe disabilities reported implementing specific data-based decision guidelines to make instructional decisions (Browder, Liberty, Heller, & D'Huyvetters, 1986; Browder, Demchak, Heller, & King, 1989) following completion of their teacher preparation program. A…
Descriptors: Data Use, Decision Making, Teacher Attitudes, Severe Disabilities
Roegman, Rachel; Samarapungavan, Ala; Maeda, Yukiko; Johns, Gary – Educational Leadership, 2019
The "Every Student Succeeds Act" requires that student's test scores be disaggregated by racial characteristics. Nevertheless, the author's recent study suggests that K-12 school principals may not intentionally think about race when they collect, interpret, analyze, and make decisions about data. By not disaggregating data by race,…
Descriptors: Elementary Secondary Education, Race, Data Collection, Data Analysis
Sattar, Simeen – Journal of Chemical Education, 2019
Pigments, dyes, and transition-metal compounds are made in courses across the undergraduate chemistry curriculum, but student characterization of these compounds' most striking features, their colors, seldom goes beyond verbal descriptions. Affordable, hand-held, fiber-optic reflectance spectrophotometers make it possible to advance students'…
Descriptors: Chemistry, Science Instruction, Undergraduate Students, Color
Hewitt, Rachel – Higher Education Policy Institute, 2019
In this new Policy Note, Rachel Hewitt, HEPI's Director of Policy and Advocacy, highlights the need to distinguish between mental health and well-being and calls for more comprehensive data to be made available on the well-being of all those work and study at universities. Key points: (1) The conflation of mental health and well-being is not…
Descriptors: Well Being, Higher Education, Mental Health, Data Collection
National Centre for Vocational Education Research (NCVER), 2019
This report covers Commonwealth and state/territory government-funded training (Commonwealth or state recurrent funding, Commonwealth specific purpose funding or state specific funding). This publication provides a summary of data relating to estimated students, programs, subjects and training providers in Australia's government-funded vocational…
Descriptors: Foreign Countries, Vocational Education, Federal Aid, Federal Programs
A Learning Progression for Constructing and Interpreting Data Display. Research Report. ETS RR-20-03
Kim, Eun Mi; Oláh, Leslie Nabors; Peters, Stephanie – ETS Research Report Series, 2020
K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…
Descriptors: Mathematics Education, Statistics Education, Teaching Methods, Data Analysis
Schultheis, Elizabeth H.; Kjelvik, Melissa K. – American Biology Teacher, 2020
Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…
Descriptors: Data Analysis, Scientific Research, Science Instruction, Scientific Principles
Percy, Chris; Tomlinson, Michael; Huddleston, Prue – Journal of Education and Work, 2020
This paper identifies a nascent trend in several countries regarding increased collection, public availability and use of destination data for graduates of secondary education, with policy ambitions to support pupil-level decision-making and drive provider-level accountability. This trend mirrors the previous development of such data for higher…
Descriptors: Educational Trends, Data Collection, Secondary Education, Educational Research
Heyman, Megan – Teaching Statistics: An International Journal for Teachers, 2019
Obtaining relevant data and conveying limitations of the results are two integral components to a successful statistical analysis. It is difficult for students to internalize a deep understanding of these components using only curated, textbook-style examples. Through hands-on data collection, this activity provides a channel for students to…
Descriptors: Data Collection, Statistical Inference, Learning Activities, Research Methodology
Yu-Hung Chiang; Yu-Chen Su; Wei-Tsong Wang; Tien-Chi Huang – Journal of Educational Computing Research, 2025
As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model…
Descriptors: Business Education, College Students, Foreign Countries, Data
Jeremy Roschelle; Amanda Wortman; Stefani Pautz Stephenson – Digital Promise, 2025
Digital learning platforms (DLPs) can transform educational research by serving as infrastructure that bridges the gap between practice and research. This white paper examines the progress of DLPs in SEERNet, a multi-year initiative funded by the Institute of Education Sciences (IES), which aims to advance research infrastructure. Through…
Descriptors: Electronic Learning, Educational Research, Influence of Technology, Research
Meeting the Climate Emergency: University Information Infrastructure for Researching Wicked Problems
Donald J. Waters – ITHAKA S+R, 2025
Commissioned by the Coalition for Networked Information, this report examines the role of research universities in addressing complex societal challenges. It focuses on climate change, which is best characterized as a "wicked" problem. Such problems are difficult to define and lack clear solutions in part because they involve multiple…
Descriptors: Climate, Research Universities, Social Problems, College Role
Jelena Andelkovic Labrovic; Nikola Petrovic; Jelena Andelkovic; Marija Meršnik – Journal of Computing in Higher Education, 2025
The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…
Descriptors: Electronic Learning, Online Courses, Behavior Patterns, Student Behavior

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