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Ferguson, Rebecca – Journal of Learning Analytics, 2019
This response to Neil Selwyn's paper, 'What's the problem with learning analytics?', relates his work to the ethical challenges associated with learning analytics and proposes six ethical challenges for the field.
Descriptors: Ethics, Data Analysis, Barriers, Justice
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Hoekstra, R.; Vugteveen, J.; Warrens, M. J.; Kruyen, P. M. – International Journal of Social Research Methodology, 2019
Cronbach's alpha is the most frequently used measure to investigate the reliability of measurement instruments. Despite its frequent use, many warn for misinterpretations of alpha. These claims about regular misunderstandings, however, are not based on empirical data. To understand how common such beliefs are, we conducted a survey study to test…
Descriptors: Statistical Analysis, Researchers, Beliefs, Knowledge Level
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De Raadt, Alexandra; Warrens, Matthijs J.; Bosker, Roel J.; Kiers, Henk A. L. – Educational and Psychological Measurement, 2019
Cohen's kappa coefficient is commonly used for assessing agreement between classifications of two raters on a nominal scale. Three variants of Cohen's kappa that can handle missing data are presented. Data are considered missing if one or both ratings of a unit are missing. We study how well the variants estimate the kappa value for complete data…
Descriptors: Interrater Reliability, Data, Statistical Analysis, Statistical Bias
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Krefeld-Schwalb, Antonia; Donkin, Chris; Newell, Ben R.; Scheibehenne, Benjamin – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…
Descriptors: Models, Cues, Probability, Experiments
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Brochu, Lauren; Burns, Jane – New Review of Academic Librarianship, 2019
In the changing landscape of libraries and the roles of librarians, the area of Research Data Management (RDM) is emerging with new opportunities and challenges. This literature review identifies the current levels of publication that deal with the relationship of the librarian and their role in the research data management process and provides an…
Descriptors: Data, Information Management, Librarians, Role
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Foster, Anita K.; Rinehart, Amanda K.; Springs, Gene R. – portal: Libraries and the Academy, 2019
In fiscal year 2017, The Ohio State University Libraries in Columbus piloted the purchase of research data sets to explore how to integrate this format into the standard workflows of the collections strategist and electronic resources officer. The pilot project had few restrictions except that one-time money must be used and purchases must be…
Descriptors: Data, Library Materials, Library Services, Academic Libraries
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Feng, Luxi; Lindner, Amanda; Ji, Xuejun Ryan; Malatesha Joshi, R. – Reading and Writing: An Interdisciplinary Journal, 2019
According to the simple view of writing (Berninger, Abbott, Abbott, Graham, & Richards, 2002), the two important components of transcription in writing are handwriting and keyboarding, the third one being spelling. The purpose of this paper is to review the contribution of two writing modes--handwriting and keyboarding to writing performance.…
Descriptors: Handwriting, Keyboarding (Data Entry), Correlation, Writing Skills
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Hernández-Leo, Davinia; Martinez-Maldonado, Roberto; Pardo, Abelardo; Muñoz-Cristóbal, Juan A.; Rodríguez-Triana, María J. – British Journal of Educational Technology, 2019
The field of "learning design" studies how to support teachers in devising suitable activities for their students to learn. The field of "learning analytics" explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and…
Descriptors: Instructional Design, Data Analysis, Guidelines, Decision Making
Agarwal, Nikhil; Somaini, Paulo J. – National Bureau of Economic Research, 2019
Preferences for schools are important determinants of equitable access to high-quality education, effects of expanded choice on school improvement and school choice mechanism design. Standard methods for estimating consumer preferences are not applicable in education markets because students do not always get their first choice school. This review…
Descriptors: School Choice, Models, Educational Quality, Data Analysis
Colorado Department of Education, 2019
The Colorado Growth Model (CGM) was developed jointly by the Colorado Department of Education (CDE), the Technical Advisory Panel for Longitudinal Growth (TAP), and the National Center for the Improvement of Educational Assessment (NCIEA). Its development was required by state statute (SB09-163) and assigned to the Technical Advisory Panel. The…
Descriptors: Growth Models, Elementary Secondary Education, Accountability, Academic Achievement
Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil – Grantee Submission, 2016
In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…
Descriptors: Intelligent Tutoring Systems, Data, Randomized Controlled Trials, Electronic Learning
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Wonsavage, F. Paul – Mathematics Teacher: Learning and Teaching PK-12, 2022
Quadratic modeling problems are commonplace in high school mathematics courses; they typically situate quadratic patterns of change and their corresponding parabolic graph within real-world contexts. Traditional approaches to this type of problem lend themselves to making connections across different representations (e.g., Garofalo and Trinter…
Descriptors: Mathematics Instruction, Secondary School Mathematics, Problem Solving, High School Students
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Yong, Binbin; Jiang, Xuetao; Lin, Jiayin; Sun, Geng; Zhou, Qingguo – Educational Technology & Society, 2022
Deep learning (DL), as the core technology of artificial intelligence (AI), has been extensively researched in the past decades. However, practical DL education needs large marked datasets and computing resources, which is generally not easy for students at school. Therefore, due to training datasets and computing resources restrictions, it is…
Descriptors: Electronic Learning, Artificial Intelligence, Shared Resources and Services, Instructional Materials
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Lu, Chang; Macdonald, Rob; Odell, Bryce; Kokhan, Vasyl; Demmans Epp, Carrie; Cutumisu, Maria – Journal of Computing in Higher Education, 2022
The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in…
Descriptors: Computation, Thinking Skills, Higher Education, Educational Trends
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Pellegrini, Mason – Journal of Technical Writing and Communication, 2022
Fierce competition has made innovation increasingly necessary for business success, and this has increased the importance of user-based innovation strategies like design thinking (DT). While many studies in technical and professional communication (TPC) have explored how DT can be used pedagogically, no studies have done this through investigating…
Descriptors: Teaching Methods, Design, Thinking Skills, Web Sites
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