This document records notes on work of the Measuring qualification effects project, and Refining a framework project, to apply the classification process to student assignments.
The workflow begins with manually downloading the TMAs and EMAs as a zip file. I downloaded them into a folder called zipped_assignments
, which is the default, but you can specify a different folder in the scripts.
This is specified in the source_folder parameter to the extract_assignments
script.
These are manually prepared zip files containing a presentation’s EMAs and TMAs. By default the script uses a zipped_assignments
folder,
If this folder does not exist, the extract_assignments
script creates it. You can specify a different folder in the script.
The assignment zip files are unzipped into this folder.
After unzipping there is one folder for each student. Each folder has a sub-folders for each assignment. This sub-folder will contain all of the student submitted files. This means there may be further sub-folders if the student has structured their submission that way, for example, to include supporting data.
Two scripts extract raw text files from the associated document type. 1 Both scripts write the text output into the source sub-folder.
Other document types can be supported too if the appropriate script is written.
Applies the selected classification scheme to the extracted text files.
The individual classification results for each document are written back into the text file’s sub-folder.
The presentation’s summary results are written to the root assignments
folder in two formats, json
and tsv
.
The classifiers are set using the standard workflow.
See prepare taxonomy documentation for more information.
1 | Text Extraction Methods |
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