While my original intent was to collect data every month on New Hire teachers, I quickly learned that this was not feasible for a number of reasons. I wanted to collect data on New Hire teachers once a month because it meant that I would gather the most accurate and recent data on them if the decided to leave the company and to track their thoughts and feelings over time, especially if the company instituted any changes (i.e. some type of intervention that could convince them to continue working for the agency).
Since I had only received a little over half of the first round of data through the inter-office mail and subsequently had to hunt down the remaining questionnaires, I quickly realized that this process would take a lot more time than I had originally imagined. Having said that, this wasn’t a problem. The only concern would be that between time 1 and time 2, many people would quit and the data from time 1 may not be the most accurate data. However, if you collect data on someone the day that they leave, that may not be the most accurate data either, since they may be in an emotional state and provide misleading answers. So the idea of what ‘accurate’ meant then became my next challenge.
I debated if it was beneficial to gather data as teachers left the company or if it was more beneficial to use the data that they had completed while in the classroom. I convinced myself that it would not be logical or beneficial to garner respsonses from employees as they leave the company because although they may speak more honestly and openly, they may say more negative things about the agency than even the day before they leave, letting my research be tainted with last-day emotions rather than everyday emotions. And it’s the everyday emotions that I want to focus on.