Year: 2016
Type: article
Abstract: The focus of this dissertation is the development of the NU Data Knowledge Scale: A measure of teachers’ data use skills and knowledge. The psychometric properties of the NU Data Knowledge Scale were thoroughly examined in this dissertation. First, the test items were based off the databasics, and were independently categorized by subject matter experts. The measure was revised based off of the recommendation of the subject matter experts. The survey was sent to 215 rural Nebraskan teachers along with a demographics section and “Comfort with Data Use” questionnaire. The psychometric properties of the measure were discussed that related the internal consistency, item-total correlations, item difficulty, and item discrimination. The dimensionality of the scale was explored using weighted least means squares analysis and the factor solution was determined by computing a parallel analysis. Fourteen predictors of teacher data literacy were then analyzed through an all possible regression procedure and the top model was chosen based off the Mallow’s Cp and adjusted R2. Overall, the NU Data Knowledge Scale was found to be a single factor measure of data literacy. The predictors included in this model, though significant, did not provide practical significance in predicting scores on the measure. The limitations of the study, direction for future search, and implications for future practice are discussed. Advisor: Beth Doll
Source: Lincoln (University of Nebraska)
Author: Jonathon David Sikorski
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2410514733