*As you read this post, you may realize that it is very similar to the previous post. Although findings are similar, this post relates to a different variable.
The final research question in my dissertation focused on teacher’s reported competency with technology. Teachers were asked two questions on the survey to address this question. The findings from this question indicate that 1:1 teachers reported higher competency scores than their non-1:1 peers on this study. On average, teachers at 1:1 schools reported scores that were .29 of a standard deviation higher than their non-1:1 peers. This may be one of the more interesting findings from my study. Teachers at 1:1 schools reported that they are much more competent with technology than their non-1:1 peers. This finding may lead to many more questions. Do 1:1 teachers report higher competency because of better/more professional development? Are 1:1 teachers forced to increase competency because they have a classroom full of students with a computing device? I hope to analyze the professional development component in more detail within the next year. My survey does include some information that may help me address that question.
Like in my previous post, 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 with 20–30 being the youngest age group. The other teachers fell into groups that each covered ten years. The findings from this indicated that when compared with the 20–30 year age group, the technology competency 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).
Teachers were also placed into one of ten content area variables. The competency 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). Competency scores from teachers in three of the content areas were lower than the scores of language arts teachers. Those areas were Foreign Language, Math, and PE/Health.
I should again stress that my study was designed to analyzed 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 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.