Move message about being based on article to introduction of chapter
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@ -2773,6 +2773,7 @@ Having this new framework at hand immediately raises some follow-up research que
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This chapter discusses the history of manual feedback in the programming course taught at the Faculty of Sciences at Ghent University (as described in the case study in Section\nbsp{}[[#sec:usecasestudy]]) and how it informed the development of evaluation and grading features within Dodona.
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We will then expand on some further experiments using data mining techniques we did to try to further reduce the time spent adding manual feedback.
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Section\nbsp{}[[#sec:feedbackprediction]] is based on an article that is currently being prepared for submission.
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** Phase 0: Paper-based assessment
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:PROPERTIES:
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@ -2906,9 +2907,7 @@ Because feedback is also added to a specific section of code, graders naturally
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Given that we now have a system for reusing earlier feedback, we can ask ourselves if we can do this in a smarter way.
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Instead of teachers having to search for the annotation they want to use, what if we could predict which annotation they want to use?
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This is exactly what we will explore in this section.[fn::
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This section is based on an article that is currently being prepared for submission.
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]
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This is exactly what we will explore in this section.
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*** Introduction
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:PROPERTIES:
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