Correlation analyses. The first step in these analyses was running correlation
analyses to investigate the strength of the relationships between TDS
and other USEIT scales and to identify relationships among other predictor
variables. To maximize the initial pool of possible predictors, researchers
used a correlation of at least ±0.2 with TDS as the criterion to retain variables
as predictor variables (Fraenkel & Wallen, 2003). To evaluate the relationship
between TDS and school- and district-level USEIT variables, researchers aggregated
the value of TDS to the appropriate hierarchical level. At the school
level, researchers assigned each school the mean TDS score for teachers
within that school. At the district level, researchers assigned each district the
mean TDS score for teachers within that district. Researchers used the same
aggregation procedure for classroom-level predictor variables of TDS that
they used at higher-levels of analysis. Researchers aggregated teachers’ experience
with technology at the school level by calculating the mean scale score
for teachers within the school. Schools’ mean experience with technology
scores were then correlated with the school mean TDS scores and with other
school-level variables, such as the principal’s use of technology.