A data entry form with failsafes
I’m currently working on a large longitudinal project as a programmer/analyst. Most of the data are collected using paper/pencil tasks and questionnaires and need to be entered into the database by student assistants. In previous projects, this led to some minor irritations since some assistants occasionally entered some words with capitalisation and others without, or they inadvertently added a trailing space to the entry, or used participant IDs that didn’t exist – all small things that cause difficulties during the analysis.
To reduce the chances of such mishaps in the current project, I created an on-line platform that uses HTML, JavaScript and PHP to homogenise how research assistants can enter data and that throws errors and warnings when they enter impossible data. Nothing that will my name pop up at Google board meetings, but useful enough.
Anyway, you can download a slimmed-down version of this platform here. The comments in the PHP files should tell you what I try to accomplish; if something’s not clear, there’s a comment section at the bottom of this page. You’ll need a webserver that supports PHP, and you’ll need to change the permissions of the Data directory to 777.
Update (2023-08-06): The links below no longer work.
You can also check out the demo. To log in, use one of the following e-mail addresses: first.assistant@university.ch, second.assistant@university.ch, third.assistant@university.ch. (You can change the accepted e-mail address in index.php). The password is projectpassword.
Then enter some data. You can only enter data for participants you’ve already created an ID for, though. For this project, the participant IDs consist of the number 4 or 5 (= the participant’s grade), followed by a dot, followed by a two digit number between 0 and 39 (= the participant’s class), followed by a dot and another two digit number between 0 and 99. The entry for Grade needs to match the first number in ID.
If you enter task data for a participant for whom someone has already task data at that data collection wave, you’ll receive an error. You can override this error by ticking the Correct existing entry? box at the bottom. This doesn’t overwrite the existing entry, but adds the new entry, which is flagged as the accurate one. During the analysis, you can then filter out data that was later updated.
Hopefully this is of some use to some of you!