Title:	MAKE USE OF SELFIE DATA TO GENERATE TARGETED RECOMMENDATIONS FOR SCHOOL TEAMS: TWO INSTRUMENTS
Author(s):	Irina Dvoretskaya and Alexander Uvarov
ISBN:	978-989-8704-22-1
Editors:	Demetrios G. Sampson, Dirk Ifenthaler and Pedro Isaías
Year:	2020
Edition:	Single
Keywords:	Self-Assessment Data, Cluster Analysis, Digital Capacity of Schools, Shared Vision, Digital Transformation of Education
Type:	Short
First Page:	383
Last Page:	386
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	As SELFIE (Self-reflection tool for digitally capable schools) piloting has shown, self-assessment of the use of digital technologies (DT) in schools provides school teams with a lot of useful information. Nevertheless, as the feedback highlights, school team members are very interested in also getting the specific targeted recommendations for improving work planning in this area. Here we suggest two practical data-driven approaches for preparing such scale-based recommendations. The first tool is based on Kruskal-Wallis non-parametric test of responses and helps to evaluate if the school develops and supports the shared vision on the integration of DT in the school. It allows us to correspond to the dichotomous scale of a shared vision. It was found out that on the sample level the influence of the shared vision formation is not tangible. The second tool helps to classify across the sample schools, the progress in the use of innovative teaching and learning with DT. Each school was attributed based on the variability of teachers' and school leaders' responses. A cluster analysis was implemented to classify results. Ten clusters obtained were assigned to three out of five levels of the RISC (Reinventing School Coalition) metric/scale.
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