Recurrence quantification analysis: A technique for the dynamical analysis of student writing

Laura K. Allen; Aaron D. Likens; Danielle McNamara

Recurrence quantification analysis: A technique for the dynamical analysis of student writing

Laura K. Allen, Aaron D. Likens, Danielle McNamara

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The current study examined the degree to which the quality and characteristics of students' essays could be modeled through dynamic natural language processing analyses. Undergraduate students (n = 131) wrote timed, persuasive essays in response to an argumentative writing prompt. Recurrent patterns of the words in the essays were then analyzed using recurrence quantification analysis (RQA). Results of correlation and regression analyses revealed that the RQA indices were significantly related to the quality of students' essays, at both holistic and sub-scale levels (e.g., organization, cohesion). Additionally, these indices were able to account for between 11% and 43% of the variance in students' holistic and sub-scale essay scores. Overall, our results suggest that dynamic techniques can be used to improve natural language processing assessments of student essays.

Original language	English (US)
Title of host publication	FLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference
Publisher	AAAI Press
Pages	240-245
Number of pages	6
ISBN (Electronic)	9781577357872
State	Published - 2017
Event	30th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017 - Marco Island, United States Duration: May 22 2017 → May 24 2017

Other

Other	30th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017
Country	United States
City	Marco Island
Period	5/22/17 → 5/24/17

ASJC Scopus subject areas

Artificial Intelligence
Software

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Allen, L. K., Likens, A. D., & McNamara, D. (2017). Recurrence quantification analysis: A technique for the dynamical analysis of student writing. In FLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference (pp. 240-245). AAAI Press.

Recurrence quantification analysis : A technique for the dynamical analysis of student writing. / Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle.

FLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference. AAAI Press, 2017. p. 240-245.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Allen, LK, Likens, AD & McNamara, D 2017, Recurrence quantification analysis: A technique for the dynamical analysis of student writing. in FLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference. AAAI Press, pp. 240-245, 30th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017, Marco Island, United States, 5/22/17.

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