Reflective Writing about the Utility Value of Science as a Tool for Increasing STEM Motivation and Retention -- Can AI Help Scale Up?

Autor/inn/en	Beigman Klebanov, Beata; Burstein, Jill; Harackiewicz, Judith M.; Priniski, Stacy J.; Mulholland, Matthew
Titel	Reflective Writing about the Utility Value of Science as a Tool for Increasing STEM Motivation and Retention -- Can AI Help Scale Up?
Quelle	In: International Journal of Artificial Intelligence in Education, 27 (2017) 4, S.791-818 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.1007/s40593-017-0141-4
Schlagwörter	STEM Education; Content Area Writing; Writing Instruction; Intervention; Student Interests; Academic Persistence; Natural Language Processing; Technology Uses in Education; Writing Evaluation; Scoring; Automation; Biology; Essays; Artificial Intelligence; Student Motivation + Suchen Sie Ihr Suchwort? STEM; Schriftliche Übung; Schreibunterricht; Studieninteresse; Natürliche Sprache; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Bewertung; Biologie; Essay; Aufsatzunterricht; Künstliche Intelligenz; Schulische Motivation
Abstract	The integration of subject matter learning with reading and writing skills takes place in multiple ways. Students learn to read, interpret, and write texts in the discipline-relevant genres. However, writing can be used not only for the purposes of practice in professional communication, but also as an opportunity to reflect on the learned material. In this paper, we address a writing intervention--Utility Value (UV) intervention--that has been shown to be effective for promoting interest and retention in STEM subjects in laboratory studies and field experiments. We conduct a detailed investigation into the potential of natural language processing technology to support evaluation of such writing at scale: We devise a set of features that characterize UV writing across different genres, present common themes, and evaluate UV scoring models using essays on known and new biology topics. The automated UV scoring results are, we believe, promising, especially for the personal essay genre. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01