Suggested Methods of Effect Size Estimation for Research in Information Technology and Teacher Education

ID: 54076 Type: Full Paper
  1. Li-Ting Chen and Leping Liu, University of Nevada, Reno, United States

Tuesday, March 19 2:15-2:45 PM Location: Sunset 2 View on map

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Abstract: Effect size estimation is import in research in Information Technology and Teacher Education. With several attempts by American Educational Research Association and American Psychology Association to encourage the reporting of effect size, studies still showed that the effect size reporting rate was low in the two research areas. The most popular effect size index, Cohen’s d, is one of the indices that can be used to assess the magnitude of differences between two groups in between-subjects designs. This paper introduces the use and interpretation of 13 effect size indices that can be used to assess the effect size for two group comparison. Each of the 13 effect size indices requires different statistical assumptions and should be interpreted differently. We present the 13 indices and demonstrate them using an empirical dataset. A free and user friendly R program to calculate the 13 effect size indices is provided.


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