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Boulden, Danielle Cadieux – Knowledge Quest, 2015
Learning analytics has been defined as the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. The potential use of data and learning analytics in educational contexts has caught the attention of educators and…
Descriptors: Educational Research, Data Collection, Data Analysis, School Libraries
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Yonezawa, Susan – Teachers College Record, 2015
Common Core proponents and detractors debate its merits, but students have voiced their opinion for years. Using a decade's worth of data gathered through design-research on youth voice, this article discusses what high school students have long described as more ideal learning environments for themselves--and how remarkably similar the Common…
Descriptors: Student Attitudes, Student Participation, State Standards, High School Students
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Reich, Justin; Tingley, Dustin; Leder-Luis, Jetson; Roberts, Margaret E.; Stewart, Brandon M. – Journal of Learning Analytics, 2015
Dealing with the vast quantities of text that students generate in Massive Open Online Courses (MOOCs) and other large-scale online learning environments is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as students write in forums, assignments, and surveys. This paper introduces to the…
Descriptors: Large Group Instruction, Online Courses, Data Collection, Data Analysis
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Hewitt, Jim – Journal of Learning Analytics, 2015
The article, "Distributed Revisiting: An Analytic for Retention of Coherent Science Learning" is an interesting study that operates at the intersection of learning theory and learning analytics. The authors observe that the relationship between learning theory and research in the learning analytics field is constrained by several…
Descriptors: Retention (Psychology), Science Education, Educational Research, Data Collection
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Merceron, Agathe; Blikstein, Paulo; Siemens, George – Journal of Learning Analytics, 2015
This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…
Descriptors: Educational Research, Data, Data Collection, Data Analysis
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Knight, Simon; Littleton, Karen – Journal of Learning Analytics, 2015
This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances…
Descriptors: Dialogs (Language), Data Collection, Data Analysis, Artificial Intelligence
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Kastens, Kim; Krumhansl, Ruth; Baker, Irene – Science Teacher, 2015
This article is aimed at teachers already experienced with activities involving small, student-collected data sets and who are now ready to begin working with large, online data sets collected by scientists and engineers. The authors discuss challenges, instructional strategies, and sources of appropriate lesson plans. With guidance, plus online…
Descriptors: Science Instruction, Data Collection, Data Analysis, Data Interpretation
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Bowers, Alex J.; Chen, Jingjing – Journal of Education Finance, 2015
The purpose of this study is to bring together recent innovations in the research literature around school district capital facility finance, municipal bond elections, statistical models of conditional time-varying outcomes, and data mining algorithms for automated text mining of election ballot proposals to examine the factors that influence the…
Descriptors: Educational Finance, School Districts, Financial Support, Bond Issues
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Robinson, Mitchell – Arts Education Policy Review, 2015
The music education profession is faced with two serious problems regarding the (mis)use of data in music teacher evaluation. The first has to do with the quality and kinds of data that music teachers have been forced to use; the second is concerned with how these data are being used in the music teacher evaluation process. The evidence I will use…
Descriptors: Music Education, Music Teachers, Teacher Evaluation, Data Analysis
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Selwyn, Neil; Henderson, Michael; Chao, Shu-Hua – British Educational Research Journal, 2015
The generation, processing and circulation of data in digital form is now an integral aspect of contemporary schooling. Based upon empirical study of two secondary school settings in Australia, this paper considers the different forms of digitally-based "data work" engaged in by school leaders, managers, administrators and teachers. In…
Descriptors: Secondary Schools, Governance, Foreign Countries, School Administration
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Zakocs, Ronda; Hill, Jessica A.; Brown, Pamela; Wheaton, Jocelyn; Freire, Kimberley E. – Health Education & Behavior, 2015
Although health education programs may benefit from quality improvement methods, scant resources exist to help practitioners apply these methods for program improvement. The purpose of this article is to describe the Data-to-Action framework, a process that guides practitioners through rapid-feedback cycles in order to generate actionable data to…
Descriptors: Feedback (Response), Health Education, Educational Quality, Program Improvement
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Williamson, Ben – Journal of Educational Administration and History, 2015
Policy innovation labs are emerging knowledge actors and technical experts in the governing of education. The article offers a historical and conceptual account of the organisational form of the policy innovation lab. Policy innovation labs are characterised by specific methods and techniques of design, data science, and digitisation in public…
Descriptors: Educational Policy, Governance, Innovation, Data Analysis
McCart, Amy; McSheehan, Michael; Sailor, Wayne – National Center on Schoolwide Inclusive School Reform: The SWIFT Center, 2015
Schoolwide Integrated Framework for Transformation (SWIFT) Center's technical assistance process supports states, districts, and schools as they become excellent and equitable teaching and learning environments for "all" students. Each school with support from its district begins this process from its own starting point and travels its…
Descriptors: Technical Assistance, Educational Change, Sustainability, Change Strategies
Bahargam, Sanaz; Erdos, Dóra; Bestavros, Azer; Terzi, Evimaria – International Educational Data Mining Society, 2015
Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1) group students so that they can maximally benefit from peer interaction and (2) find an optimal schedule of the educational…
Descriptors: Grouping (Instructional Purposes), Scheduling, Time Factors (Learning), Individualized Instruction
Data Quality Campaign, 2015
If our destination is improved student achievement, we cannot get there without valuing and effectively using data in education. Central to reaching this goal is building trust among all those who have a stake in education that individual student data, such as attendance, course taking, grades, and test scores, are being collected for meaningful…
Descriptors: Data Collection, Data Analysis, Academic Achievement, State Departments of Education
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