Validating a Blended Teaching Readiness Instrument for Primary/Secondary Preservice Teachers

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  • Source:
    British Journal of Educational Technology, v52 n2 p536-551 Mar 2021. 16 pp.
  • Accession Number:
    http://dx.doi.org/10.1111/bjet.13060
  • Language:
    English
  • Publication Type:
    Journal Articles; Reports - Research
  • Additional Information
    • Author(s):
    • Peer Reviewed:
      Y
    • ISSN:
      0007-1013
    • Subject Terms:
    • Abstract:
      Blended learning is the fastest growing teaching modality in North America and much of the world. However, research and training in blended learning are far outpaced by its usage. To remedy this gap, we developed a competency framework and Blended Teaching Readiness Instrument (BTRI) to help teachers and researchers evaluate teacher readiness for blended environments. The purpose of this research is to show that the blended teaching readiness model and accompanying BTRI are reliable for use with teacher candidates both before and after going through a blended teaching course. This knowledge would allow researchers and practitioners to have greater confidence in using the BTRI for future growth curve modeling for the identified blended teaching competencies. To accomplish this, we collected pre- and post-data from teacher candidates across multiple semesters who were studying in a blended teaching course. Using confirmatory factor analysis, we determined the pre-class survey results fell within the range of the four fit statistics cutoffs (RMSEA = 0.045, CFI = 0.933, TLI = 0.929 and SRMR = 0.043). And, the post-class survey results had good fit as well (RMSEA = 0.044, CFI = 0.911, TLI = 0.905 and SRMR = 0.051). 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 blended teacher competency. Additionally, we tested the model for measurement invariance and found that we could reliably use the BTRI for pre-post growth modeling.
    • Abstract:
      As Provided
    • Number of References:
      -1
    • Physical Description:
      16
    • Education Level:
      Higher Education; Postsecondary Education
    • Journal Code:
      MAY2021
    • Publication Date:
      2021
    • Accession Number:
      EJ1286684