Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Foundations for NLP-assisted formative assessment feedback for
  short-answer tasks in large-enrollment classes   Research suggests "write-to-learn" tasks improve learning outcomes, yet
constructed-response methods of formative assessment become unwieldy with large
class sizes. This study evaluates natural language processing algorithms to
assist this aim. Six short-answer tasks completed by 1,935 students were scored
by several human raters, using a detailed rubric, and an algorithm. Results
indicate substantial inter-rater agreement using quadratic weighted kappa for
rater pairs (each QWK > 0.74) and group consensus (Fleiss Kappa = 0.68).
Additionally, intra-rater agreement was estimated for one rater who had scored
178 responses seven years prior (QWK = 0.89). With compelling rater agreement,
the study then pilots cluster analysis of response text toward enabling
instructors to ascribe meaning to clusters as a means for scalable formative
assessment.

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The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
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The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
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The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph