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Turrin, Margie – Science Teacher, 2015
Data and data analysis are central to science and the complex world in which people live. Students need to practice working with data--addressed in the "Next Generation Science Standards" (NGSS Lead States 2013)--starting with small, self-collected data sets and moving on to larger, remotely collected data assemblages. Small data sets…
Descriptors: Science Education, Data Collection, Data Analysis, Experiential Learning
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Bainter, Sierra A.; Curran, Patrick J. – Journal of Cognition and Development, 2015
Amid recent progress in cognitive development research, high-quality data resources are accumulating, and data sharing and secondary data analysis are becoming increasingly valuable tools. Integrative data analysis (IDA) is an exciting analytical framework that can enhance secondary data analysis in powerful ways. IDA pools item-level data across…
Descriptors: Data Analysis, Integrated Activities, Inferences, Statistical Analysis
Datnow, Amanda; Park, Vicki – Educational Leadership, 2015
School leaders are often drowning in data but are unsure which forms of data will help them create a portrait of student achievement that will motivate staff to look beyond simple trends and delve deeper into root causes. Teachers often wish for more guidance on the kinds of data analysis and teaching strategies that will help them move the needle…
Descriptors: Evaluation Utilization, Data, Data Analysis, Data Interpretation
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Miškolci, Jozef – Ethnography and Education, 2015
Researchers' "reflexivity" about how they shape the phenomena that they study within the data collection process is often presented as a crucial component of ethnographic research methodology. Nevertheless, academic literature about ethnography is mostly silent around whether researchers' dreams are relevant to the research process and…
Descriptors: Foreign Countries, Ethnography, Research Methodology, Educational Researchers
Soland, Jim – Phi Delta Kappan, 2015
Predictive analytics in education can offer a benefit as long as educators heed the differences between how the tools are used in industry and how they should be used differently in schooling. Perhaps most important, teachers already know a great deal about their students--far more than an investor knows about a stock or a baseball scout about an…
Descriptors: Prediction, Predictive Validity, Teacher Student Relationship, Familiarity
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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
Feild, Jacqueline – International Educational Data Mining Society, 2015
Providing students with continuous and personalized feedback on their performance is an important part of encouraging self regulated learning. As part of our higher education platform, we built a set of data visualizations to provide feedback to students on their assignment performance. These visualizations give students information about how they…
Descriptors: Student Improvement, Performance, Feedback (Response), Assignments
Arrigo, Marco; Fulantelli, Giovanni; Taibi, Davide – International Association for Development of the Information Society, 2015
Evaluation of Mobile Learning remains an open research issue, especially as regards the activities that take place outside the classroom. In this context, Learning Analytics can provide answers, and offer the appropriate tools to enhance Mobile Learning experiences. In this poster we introduce a task-interaction framework, using learning analytics…
Descriptors: Educational Technology, Technology Uses in Education, Electronic Learning, Telecommunications
Custer, Michael – Online Submission, 2015
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Descriptors: Sample Size, Item Response Theory, Computation, Accuracy
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Wang, Yuan; Paquette, Luc; Baker, Ryan – Journal of Learning Analytics, 2014
In this paper, we present progress towards a longitudinal study of the post-course career advancement of MOOC learners. We present initial results and analysis plans for how to link this to in-course behaviour, towards better understanding the goals of all MOOC learners.
Descriptors: Career Development, Longitudinal Studies, Online Courses, Educational Research
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Berland, Matthew; Baker, Ryan S.; Blikstein, Paulo – Technology, Knowledge and Learning, 2014
Constructionism can be a powerful framework for teaching complex content to novices. At the core of constructionism is the suggestion that by enabling learners to build creative artifacts that require complex content to function, those learners will have opportunities to learn this content in contextualized, personally meaningful ways. In this…
Descriptors: Educational Research, Statistical Analysis, Cooperation, Researchers
Dunlap, Mickey; Studstill, Sharyn – Teaching Statistics: An International Journal for Teachers, 2014
The number of increases a particular stock makes over a fixed period follows a Poisson distribution. This article discusses using this easily-found data as an opportunity to let students become involved in the data collection and analysis process.
Descriptors: Experiential Learning, Learning Activities, Statistical Distributions, Probability
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Milliron, Mark David; Malcolm, Laura; Kil, David – Research & Practice in Assessment, 2014
Civitas Learning was conceived as a community of practice, bringing together forward-thinking leaders from diverse higher education institutions to leverage insight and action analytics in their ongoing efforts to help students learn well and finish strong. We define insight and action analytics as drawing, federating, and analyzing data from…
Descriptors: Case Studies, Communities of Practice, Data Analysis, Higher Education
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Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2014
This research note contributes to the discussion of methods that can be used to identify useful auxiliary variables for analyses of incomplete data sets. A latent variable approach is discussed, which is helpful in finding auxiliary variables with the property that if included in subsequent maximum likelihood analyses they may enhance considerably…
Descriptors: Data Analysis, Identification, Maximum Likelihood Statistics, Statistical Analysis
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Pardo, Abelardo; Siemens, George – British Journal of Educational Technology, 2014
The massive adoption of technology in learning processes comes with an equally large capacity to track learners. Learning analytics aims at using the collected information to understand and improve the quality of a learning experience. The privacy and ethical issues that emerge in this context are tightly interconnected with other aspects such as…
Descriptors: Ethics, Privacy, Learning, Data Analysis
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