Abstract
Likert-type items are commonly used in education and related fields to measure attitudes and opinions. Yet there is no consensus on how to analyze data collected from these items. In this paper, we first synthesized literature on strategies for analyzing Likert-type data and provided computing tools for these strategies. Secondly, to examine the use and analysis of Likert-type data in the field of educational technology, we reviewed 424 articles that were published in the journal Educational Technology Research and Development between 2016 and 2020. Our review showed that about 50% of the articles reported Likert-type data. A total of 139 articles used Likert-type data as a dependent variable, among which 86% employed parametric methods to analyze the data. In addition, less than 1% of the 139 articles used an ordered probit/ logit model, transformation, or strategy for rescaling Likert-type data to interval data to perform statistical analysis. Finally, to empower educational technology researchers to handle Likert-type data effectively, we concluded the paper with our suggestions and insight regarding alternative strategies and methods.
First Page
39
Last Page
60
Ethics Approval
Yes
Declaration Statement
NONE
Recommended Citation
Chen, L., & Liu, L. (2020). Methods to Analyze Likert-Type Data in Educational Technology Research. Journal of Educational Technology Development and Exchange (JETDE), 13(2), 39-60. https://doi.org/10.18785/jetde.1302.04
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
