Assessing Text-Based Writing of Low-Skilled College Students

Autor/inn/en	Perin, Dolores; Lauterbach, Mark
Titel	Assessing Text-Based Writing of Low-Skilled College Students
Quelle	In: International Journal of Artificial Intelligence in Education, 28 (2018) 1, S.56-78 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.1007/s40593-016-0122-z
Schlagwörter	College Students; Writing Evaluation; Writing Skills; Developmental Studies Programs; Computer Assisted Testing; Scoring; Automation; Predictor Variables; Scores; Scoring Rubrics; Persuasive Discourse; Essay Tests; Introductory Courses; Writing Achievement; Low Achievement + Suchen Sie Ihr Suchwort? Collegestudent; Writing skill; Schreibfertigkeit; Developmental studies; Developmental psychology; Study; Studies; Entwicklungspsychologie; Studium; Bewertung; Prädiktor; Scoring formulas; Auswertungsbogen; Persuasion; Persuasive Kommunikation; Schriftlicher Sprachgebrauch; Einführungskurs; Unterdurchschnittliche Leistung
Abstract	The problem of poor writing skills at the postsecondary level is a large and troubling one. This study investigated the writing skills of low-skilled adults attending college developmental education courses by determining whether variables from an automated scoring system were predictive of human scores on writing quality rubrics. The human-scored measures were a holistic quality rating for a persuasive essay and an analytic quality score for a written summary. Both writing samples were based on text on psychology and sociology topics related to content taught at the introductory undergraduate level. The study is a modified replication of McNamara et al. ("Written Communication," 27(1), 57-86 2010), who identified several Coh-Metrix variables from five linguistic classes that reliably predicted group membership (high versus low proficiency) using human quality scores on persuasive essays written by average-achieving college students. When discriminant analyses and ANOVAs failed to replicate the McNamara et al. ("Written Communication," 27(1), 57-86 2010) findings, the current study proceeded to analyze all of the variables in the five Coh-Metrix classes. This larger analysis identified 10 variables that predicted human-scored writing proficiency. Essay and summary scores were predicted by different automated variables. Implications for instruction and future use of automated scoring to understand the writing of low-skilled adults are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01