Abstract

Blended learning is the fastest-growing modality in North America and much of the world. However, research and training in blended learning is far outpaced by its usage. To remedy this gap, we developed a competency framework and self-survey instrument to help teachers and researchers evaluate teacher readiness for blended environments. The purpose of this research is to prove that the model and accompanying survey instrument are reliable for use with teacher candidates both before and after going through a blended teaching course. To accomplish this, we sent out a survey instrument to 326 teacher candidates studying in a blended teaching course at a university in the western United States. The teachers took the survey at the beginning of class, and then once again, three months later. Using confirmatory factor analysis, we determined that the pre-class survey results fell within the range of the four fit statistics cutoffs (RMSEA=.056, CFI=.906, TLI=0.900, SRMR=.04). And with slight modification, the post-class survey results did as well (RMSEA=.052, CFI=.914, TLI=.907, and SRMR .058). We also showed that the factor loadings and communalities were statistically significant. By testing the factors in this way, we make a case for the survey to be a valid and reliable instrument in assessing teacher competency, and make a case for thinking of blended teaching competencies in terms of our model. We then tested for measurement invariance, but were unsuccessful in making a case for it. The results of our findings provide teacher educators, teacher candidates, and researchers a new pedagogically-oriented framework and scientifically validated self-survey to use in order to improve and personalize teacher education and professional development for blended settings.

Degree

College and Department

David O. McKay School of Education; Instructional Psychology and Technology

Rights

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