The second research question in my study attempted to analyze the technology integration occurring at 1:1 schools. Each educator had an “integration” score which was generated from 14 questions about the use of various technology tools in the classroom. Teachers responded to the question about integration of the various tools on a 4-point Likert scale that ranged from “Not at all” to “A large extent”. The findings from this question were also quite powerful. On average, teachers at 1:1 schools reported scores that were 0.28 of a standard deviation higher than teachers at non-1:1 schools on the 4-point scale representing how much they integrated technology into their classrooms. In non-statistical terms, this is a large difference. 1:1 educators in the study were integrating technology at much higher levels than their non-1:1 peers. This finding may be of great interest to school leaders who are deciding how and if they should strive to increase technology integration in their school.
There were some additional findings from this question that may be interesting, but they should be interpreted cautiously. The findings I’ll describe below were not related to 1:1 status, but rather teacher age and content area.
For the age variable, teachers were grouped into five age categories that each covered a ten year age span with 20–30 being the youngest age group. The findings from this indicated that when compared with the 20–30 year age group, the technology integration scores from all of the other groups were significantly lower than that youngest group (see note below if you’re interested in why I compared to that youngest group). Interestingly, this same finding was not evident in the variable for time. This may indicate that older teachers are willing to use technology they are comfortable with, but they haven’t been provided the training that allows them to achieve a higher integration score.
Teachers were also placed into one of ten content area variables. The integration scores of teachers from each content area were compared to language arts teachers (see note below if you’re interested in why I compared to Language Arts). Integration scores from teachers in five of the content areas were lower than the scores of language arts teachers. Those areas were Fine Arts, Foreign Language, Math, PE/Health, and Science.
I should again stress that my study was designed to analyze the impact of 1:1 on my research questions. The age and content area findings are not related to 1:1 status.
For those of you familiar with regression models in statistics, you may understand that you need to identify a reference category when using a dummy variable. For those of you less familiar with regression models, it is important to understand what a dummy variable is. A dummy variable is a variable that would hold a value of 0 (no) or 1 (yes) for each item. For example, if I asked a teacher if they taught Fine Arts, they would answer either yes (1) or no (0). Each respondent was coded 0 or 1 for each content area and age category. The next thing I had to do was to identify a reference category to compare to those dummy variables. I selected the youngest age group because of the perception that some have about the younger educators being more comfortable with technology. I selected Language Arts for the content area variable because much of the 1:1 research indicates that some of the largest academic gains have been in that area.