Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatic Assessment of the Design Quality of Python Programs with
  Personalized Feedback   The assessment of program functionality can generally be accomplished with
straight-forward unit tests. However, assessing the design quality of a program
is a much more difficult and nuanced problem. Design quality is an important
consideration since it affects the readability and maintainability of programs.
Assessing design quality and giving personalized feedback is very time
consuming task for instructors and teaching assistants. This limits the scale
of giving personalized feedback to small class settings. Further, design
quality is nuanced and is difficult to concisely express as a set of rules. For
these reasons, we propose a neural network model to both automatically assess
the design of a program and provide personalized feedback to guide students on
how to make corrections. The model's effectiveness is evaluated on a corpus of
student programs written in Python. The model has an accuracy rate from 83.67%
to 94.27%, depending on the dataset, when predicting design scores as compared
to historical instructor assessment. Finally, we present a study where students
tried to improve the design of their programs based on the personalized
feedback produced by the model. Students who participated in the study improved
their program design scores by 19.58%.

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The categories of this paper are: q-alg
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The categories of this paper are: comp-gas
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The categories of this paper are: atom-ph
16
The categories of this paper are: stat
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The categories of this paper are: adap-org
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The categories of this paper are: supr-con
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The categories of this paper are: patt-sol
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The categories of this paper are: cmp-lg
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The categories of this paper are: solv-int
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The categories of this paper are: nlin
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The categories of this paper are: plasm-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-ex
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The categories of this paper are: econ
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The categories of this paper are: q-bio
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The categories of this paper are: ao-sci