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Goldhaber, Dan; Holden, Kristian L.; Grout, Cyrus – Educational Researcher, 2019
Longitudinal administrative data generated by public education systems in the United States have become increasingly available and have tremendous potential to inform policy research. While it is tempting to take the accuracy of administrative data for granted, there are reasons why researchers should approach these data with a degree of caution.…
Descriptors: Educational Research, Research Utilization, Data Analysis, Error Patterns
Nicholas Raikes – Research Matters, 2019
Big international assessment organisations like Cambridge Assessment have long held considerable amounts of data. When text is produced digitally, we can do more with it. Surprisingly to many, there have been examples of automatic scoring of extended writing for around 20 years, though what works well in one context may not be applicable in all…
Descriptors: Data Collection, Data Analysis, Evaluation, Technology Uses in Education
Renee A. Silliman – ProQuest LLC, 2019
Background: As the state standards increase, along with the instructional rigor within developed curriculum and state accountability, the need to improve ineffective teachers and their practices in the classroom has become a national priority. The need for relevant professional development that meets both the instructional needs of the teacher and…
Descriptors: Teacher Effectiveness, Experienced Teachers, Coaching (Performance), Data Analysis
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Marc T. Braverman – Journal of Human Sciences & Extension, 2019
This article examines the concept of credible evidence in Extension evaluations with specific attention to the measures and measurement strategies used to collect and create data. Credibility depends on multiple factors, including data quality and methodological rigor, characteristics of the stakeholder audience, stakeholder beliefs about the…
Descriptors: Extension Education, Program Evaluation, Evaluation Methods, Planning
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O'Halloran, Kay L.; Tan, Sabine; Pham, Duc-Son; Bateman, John; Vande Moere, Andrew – Journal of Mixed Methods Research, 2018
This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal…
Descriptors: Mixed Methods Research, Research Design, Data Analysis, Visual Aids
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Alexander, Patricia A. – British Journal of Educational Psychology, 2018
Purpose: The primary goal of this commentary was to consider the future directions that researchers dealing with levels and regulation of strategies and with approaches to learning may wish to pursue in the years to come. Procedure: In order to accomplish this goal, the first step was to look for any common ground shared by authors contributing to…
Descriptors: Futures (of Society), Learning Strategies, Cognitive Style, Educational Research
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Cusker, Jeremy – Issues in Science and Technology Librarianship, 2018
In 2012, this author published a paper describing a method for using the raw data from Web of Science to examine the journals cited by any given group of researchers and then compare that list to lists of 'top journals' of similar disciplines. It was not a straightforward method to use and required a great deal of effort and spreadsheet work by a…
Descriptors: Citation Analysis, Citations (References), Bibliometrics, Evaluation Methods
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Ward, Jason K.; Comer, Unoma; Stone, Suki – Interchange: A Quarterly Review of Education, 2018
This article presents the use of the qualitative research method and the challenges that this form of research imposes along with the increasingly systematic reluctance experienced by doctoral students and their chairs. Increasingly, doctoral students are opting for the qualitative approach over that of the traditional quantitative methodology.…
Descriptors: Qualitative Research, Graduate Students, Student Research, Data Collection
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Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay – Education and Information Technologies, 2018
Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…
Descriptors: Data Collection, Data Analysis, Correlation, Academic Achievement
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Chen, Bodong; Knight, Simon; Wise, Alyssa Friend – Journal of Learning Analytics, 2018
The importance of temporality in learning has been long established, but it is only recently that serious attention has begun to be paid to the precise identification, measurement, and analysis of the temporal features of learning. From 2009 to 2016, a series of temporality workshops explored temporal concepts and data types, analysis methods for…
Descriptors: Time Factors (Learning), Data Analysis, Learning, Experience
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Klumpp, Matthias – Education Sciences, 2018
An increasing effort has been put into dealing with the question of time-series analysis regarding institutional efficiency, including in the area of higher education. Universities are important institutions for economies and societies and are expected to provide excellence as well as efficiency in their processes and outputs. This is reflected in…
Descriptors: Efficiency, Universities, Data Analysis, Achievement Rating
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Franz, Nancy K. – Journal of Extension, 2018
Increased focus on data-driven decision making requires Extension professionals to excel at data analysis and interpretation. Data parties have become increasingly popular for involving stakeholders in making sense of data. As these parties become more frequently used by Extension professionals, best practices are emerging from lessons learned to…
Descriptors: Extension Education, Extension Agents, Decision Making, Data
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Steele, George E. – New Directions for Higher Education, 2018
Two of the most important issues facing those in the field of academic advising are the use of technology and data analytics. There is no question that technology and data will shape the delivery and expectations for academic advising in higher education in the years to come. This chapter explores the intersections between advising, technology,…
Descriptors: Academic Achievement, Academic Advising, Data Analysis, Technology Uses in Education
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Schneider, Johannes; Bernstein, Abraham; Brocke, Jan vom; Damevski, Kostadin; Shepherd, David C. – IEEE Transactions on Learning Technologies, 2018
All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…
Descriptors: Plagiarism, Assignments, Programming, Computer Software
Gregg, Andrea; Wilson, Brent G.; Parrish, Patrick – IDEA Center, Inc., 2018
The field of learning analytics holds considerable promise for higher education, with reports of successful uses now emerging in selected institutions. At the same time, critics have expressed concerns regarding privacy, ethics, and intrusions into teachers' pedagogy. Without attentive planning, higher-education professionals applying learning…
Descriptors: Data Analysis, Higher Education, Vendors, Academic Achievement
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