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Assessing Text-Based Writing of Low-Skilled College Students
- Source :
- International Journal of Artificial Intelligence in Education. 28:56-78
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
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.
- Subjects :
- 060201 languages & linguistics
media_common.quotation_subject
05 social sciences
Educational technology
050301 education
Rubric
06 humanities and the arts
Writing quality
Education
Writing skills
Computational Theory and Mathematics
Quality rating
0602 languages and literature
Quality Score
Mathematics education
Quality (business)
Psychology
0503 education
Low skilled
media_common
Subjects
Details
- ISSN :
- 15604306 and 15604292
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- International Journal of Artificial Intelligence in Education
- Accession number :
- edsair.doi...........71c1fb4d72497a4f8ede4131dc225581