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Update Please see my next comment that outlines a better approach for dealing with this.
For normal book reading, we decide if we are using a number or size prompt based on the "mode" (which is in turn based on the "treatment" that is set up at the beginning).
However, for pre- and post-tests there is only one prompt and correct answer per question.
So when choosing a prompt and when grading answers, the logic will need to be updated by passing in the "type" (pre-test, post-test, or regular book) so that we can update the logic.
Effected places:
- Getting the choices
Currently, this based on difficulty. However, for pre- and post-tests, difficulty is not relevant. So we need to detect that we are in a pre- or post-test and simply select the one difficulty level that is present.
src/models/Question.ts#getDifficulty - Getting the prompt:
src/models/Question.ts getPrompt - Grading a selection
src/models/Question.ts#isSelectionCorrectwhich in turn depends onsrc/models/Choice.ts#isSelectionCorrect.
For a regular book, identifying the correct answer depends on themode. However, for pre- and post-tests, we will make the assumption that only one of the fields is specified - either the correct number stimulus or the correct size stimulus. So we will need to pass along information about the book type. If a regular book, use mode as normal. If a pre- or post-test, then ignore themodeand identify which field is not null and use that one.
To identify more places that may be effected, in VS Code do a global search for "mode" - CTRL + SHIFT + F to open up the global search on windows.
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