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Rankin, Jenny Grant – Online Submission, 2015
Data is critical, but data has not always lead to success. If data is not communicated clearly, the results can be disastrous. Design lets us communicate data so it can be understood. Dr. Rankin believes that "when we're fluent in visualizing our ideas, we can communicate them across global boundaries, across spoken language barriers, and…
Descriptors: Data, Information Utilization, Relevance (Education), Data Interpretation
Rankin, Jenny Grant – Universal Journal of Educational Research, 2016
Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…
Descriptors: Evidence Based Practice, Data Interpretation, Information Utilization, Standards
Goedert, Kelly M.; Ellefson, Michelle R.; Rehder, Bob – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Individuals have difficulty changing their causal beliefs in light of contradictory evidence. We hypothesized that this difficulty arises because people facing implausible causes give greater consideration to causal alternatives, which, because of their use of a positive test strategy, leads to differential weighting of contingency evidence.…
Descriptors: Causal Models, Inferences, Beliefs, Attitude Change
Reporting Data with "Over-the-Counter" Data Analysis Supports Increases Educators' Analysis Accuracy
Rankin, Jenny Grant – Online Submission, 2013
There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts…
Descriptors: Statistical Data, Data Interpretation, Data Analysis, Error of Measurement
Frederick, Karen; Barnard-Brak, Lucy; Sulak, Tracey – International Journal of Research & Method in Education, 2012
There has been a significant increase in the use of secondary data sets. Many such data sets purport to be nationally representative. Secondary data sets include research commissioned by the National Center for Education Statistics, the Centers for Disease Control, and other public entities. Research increasingly utilizes these secondary data in…
Descriptors: Autism, Statistical Analysis, Pervasive Developmental Disorders, Disproportionate Representation

Carter, Greg Lee – Teaching Sociology, 1989
Presents a classroom technique for demonstrating the post-factum interpretation problem. Describes the various ways that students interpreted data concerning the percentage of men and women in traditionally female occupations. Discusses the various uses of this technique in both introductory and research classes. (KO)
Descriptors: Classroom Techniques, Data Interpretation, Information Utilization, Learning Strategies

Hinkle, Dennis E.; And Others – New Directions for Institutional Research, 1988
The data collected in higher education research are not always quantitative or continuous. Statistical methods using the log-linear model provide the institutional researcher with a powerful set of tools for addressing research questions when data are categorical. (Author/MSE)
Descriptors: Data Interpretation, Higher Education, Information Utilization, Institutional Research
Hiroto, Nagato – 1997
Designed for language teachers who find reading statistical research difficult but necessary, this article focuses on the minimal knowledge needed about statistical techniques for interpreting research findings. It first examines the statistical reasoning underlying quantitative, empirical studies, including normal distribution, standard…
Descriptors: Classroom Research, Classroom Techniques, Comparative Analysis, Data Interpretation