Evaluation 2017: From Learning to Action

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Utilizing Data Visualization to Reduce Complexity and Enhance Understanding

Session Number: DVR1
Track: Data Visualization and Reporting
Session Type: TIG Multipaper
Session Chair: Sheila B. Robinson, Ed. D [Program Evaluator / Professional Developer - Greece Central School District]
Presenter 1: Harold Stanislaw [Professor of Psychology - California State University, Stanislaus]
Presenter 2: Ciara C. Paige [Doctorate Student - Claremont Graduate University]
Presenter 3: Mary Anne Sydlik [Research Emerita - Western Michigan University]
Presentation 2 Additional Author: Dana Linnell Wanzer [Research and Evaluation Associate - Claremont Graduate University]
Presentation 2 Additional Author: Natalie D Jones [Claremont Graduate University ]
Presentation 2 Additional Author: Darrel Skousen [Doctoral Candidate - Claremont Graduate University]
Presentation 3 Additional Author: Cody Williams [Research Associate - Western Michigan University]
Presentation 3 Additional Author: Eva Ngulo
Presentation 3 Additional Author: Heather Kasper
Time: Nov 09, 2017 (03:15 PM - 04:15 PM)
Room: Washington 4

Abstract 1 Title: Dynamic display of before and after data
Presentation Abstract 1: Evaluators often compare data measured before an intervention takes place, with data measured some period of time after the intervention.  Static displays of the data before and after the intervention rarely communicate fully the changes triggered by the intervention.  Important individual differences in responses to the intervention can also be masked.  This paper will describe methods for dynamically illustrating the changes associated with introducing an intervention.  The methods will be illustrated by presenting outcomes for children who received one of two different treatments for autism, and were assessed annually for up to 7 years after the start of treatment.
Abstract 2 Title: How effective are logic models? Testing their understandability, credibility, and more
Presentation Abstract 2: Despite the popularity and use of logic models in evaluation, little is known about how cognitively challenging, and credible they are to stakeholders. Through a study conducted on Amazon’s Mechanical Turk (MTurk) platform, various alterations of a single logic model were explored to determine what components (e.g., data visualization principles, arrows, legends, accompanying narrative descriptions) are most important at affecting users’ accuracy of interpretation, response time, mental effort, and perceptions of credibility. Implications for future development in logic modeling and data visualization will be discussed.
Presentation 2 Other Authors: Nina Sabarre, Claremont Graduate University, Doctorate Student; Tarek Azzam, Claremont Graduate University, Associate Professor
Abstract 3 Title: TRANSLATING COMPLEX DATA ANALYSES INTO USABLE FEEDBACK FOR CLIENTS.
Presentation Abstract 3: The proposed demonstration will provide guidelines for evaluators who face the challenge of translating complex data analyses into useful feedback for their clients.
Presentation 3 Other Authors: Robert Ruhf, robert.ruhf@wmich.edu, Senior Researcher, SAMPI, Western Michigan University, Kalamazoo, MI 49008.
Theme: Select one
Audience Level: None

Session Abstract (150 words):  Utilizing Data Visualization to Reduce Complexity and Enhance Understanding


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