Automated scoring in context: Rapid assessment for placed students
► Applies a new evaluation framework for automated essay scoring (AES). ► Proposes a new use for AES: rapid assessment of placed students in first-year classes. ► Offers results on relationships between AES and established writing measures. This study investigated the use of automated essay scoring...
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Veröffentlicht in: | Assessing writing 2013-01, Vol.18 (1), p.62-84 |
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creator | Klobucar, Andrew Elliot, Norbert Deess, Perry Rudniy, Oleksandr Joshi, Kamal |
description | ► Applies a new evaluation framework for automated essay scoring (AES). ► Proposes a new use for AES: rapid assessment of placed students in first-year classes. ► Offers results on relationships between AES and established writing measures.
This study investigated the use of automated essay scoring (AES) to identify at-risk students enrolled in a first-year university writing course. An application of AES, the Criterion® Online Writing Evaluation Service was evaluated through a methodology focusing on construct modelling, response processes, disaggregation, extrapolation, generalization, and consequence. Based on the results of our two-year study with students (N=1,482) at a public technological research university in the United States, we found that Criterion offered a defined writing construct congruent with established models, achieved acceptance among students and instructors, showed no statistically significant differences between ethnicity groups of sufficient sample size, correlated at acceptable levels with other writing measures, performed in a stable fashion, and enabled instructors to identify at-risk students to increase their course success. |
doi_str_mv | 10.1016/j.asw.2012.10.001 |
format | Article |
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This study investigated the use of automated essay scoring (AES) to identify at-risk students enrolled in a first-year university writing course. An application of AES, the Criterion® Online Writing Evaluation Service was evaluated through a methodology focusing on construct modelling, response processes, disaggregation, extrapolation, generalization, and consequence. Based on the results of our two-year study with students (N=1,482) at a public technological research university in the United States, we found that Criterion offered a defined writing construct congruent with established models, achieved acceptance among students and instructors, showed no statistically significant differences between ethnicity groups of sufficient sample size, correlated at acceptable levels with other writing measures, performed in a stable fashion, and enabled instructors to identify at-risk students to increase their course success.</description><identifier>ISSN: 1075-2935</identifier><identifier>EISSN: 1873-5916</identifier><identifier>DOI: 10.1016/j.asw.2012.10.001</identifier><identifier>CODEN: ASWRFM</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>At Risk Students ; Automated essay scoring (AES) ; Automation ; College Freshmen ; Computer Assisted Testing ; Computer Software Evaluation ; Essay Tests ; Essays ; Ethnic Groups ; Research Universities ; Scoring ; Statistical Analysis ; Student Placement ; Validation methods ; Writing assessment ; Writing Evaluation ; Writing Instruction ; Writing placement</subject><ispartof>Assessing writing, 2013-01, Vol.18 (1), p.62-84</ispartof><rights>2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c351t-cfccfac956119789090810ebf3079989256e81043a4f9221b4fd6067b69d388e3</citedby><cites>FETCH-LOGICAL-c351t-cfccfac956119789090810ebf3079989256e81043a4f9221b4fd6067b69d388e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S107529351200044X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ995504$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Klobucar, Andrew</creatorcontrib><creatorcontrib>Elliot, Norbert</creatorcontrib><creatorcontrib>Deess, Perry</creatorcontrib><creatorcontrib>Rudniy, Oleksandr</creatorcontrib><creatorcontrib>Joshi, Kamal</creatorcontrib><title>Automated scoring in context: Rapid assessment for placed students</title><title>Assessing writing</title><description>► Applies a new evaluation framework for automated essay scoring (AES). ► Proposes a new use for AES: rapid assessment of placed students in first-year classes. ► Offers results on relationships between AES and established writing measures.
This study investigated the use of automated essay scoring (AES) to identify at-risk students enrolled in a first-year university writing course. An application of AES, the Criterion® Online Writing Evaluation Service was evaluated through a methodology focusing on construct modelling, response processes, disaggregation, extrapolation, generalization, and consequence. Based on the results of our two-year study with students (N=1,482) at a public technological research university in the United States, we found that Criterion offered a defined writing construct congruent with established models, achieved acceptance among students and instructors, showed no statistically significant differences between ethnicity groups of sufficient sample size, correlated at acceptable levels with other writing measures, performed in a stable fashion, and enabled instructors to identify at-risk students to increase their course success.</description><subject>At Risk Students</subject><subject>Automated essay scoring (AES)</subject><subject>Automation</subject><subject>College Freshmen</subject><subject>Computer Assisted Testing</subject><subject>Computer Software Evaluation</subject><subject>Essay Tests</subject><subject>Essays</subject><subject>Ethnic Groups</subject><subject>Research Universities</subject><subject>Scoring</subject><subject>Statistical Analysis</subject><subject>Student Placement</subject><subject>Validation methods</subject><subject>Writing assessment</subject><subject>Writing Evaluation</subject><subject>Writing Instruction</subject><subject>Writing placement</subject><issn>1075-2935</issn><issn>1873-5916</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp9kE1PxCAURYnRxHH0B5i46NJNK5TSFl2Nk_Erk5gYXROGPgyTtlSgfvx7aWbi0hVw33k34SB0TnBGMCmvtpn0X1mOSR7fGcbkAM1IXdGUcVIexjuuWJpzyo7RiffbCBSY0hm6XYzBdjJAk3hlnenfE9MnyvYBvsN18iIH0yTSe_C-gz4k2rpkaKWa-DA2MfKn6EjL1sPZ_pyjt7vV6_IhXT_fPy4X61RRRkKqtFJaKs5KQnhVc8xxTTBsNMUV5zXPWQkxKKgsNM9zsil0U-Ky2pS8oXUNdI4ud72Dsx8j-CA64xW0rezBjl4QxjDnNKc8omSHKme9d6DF4Ewn3Y8gWEy-xFZEX2LyNUVRR9y52O2AM-qPXz1xHnuLOL7Zj-MXPw044ZWBPoowDlQQjTX_lP8CHNZ7Qw</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Klobucar, Andrew</creator><creator>Elliot, Norbert</creator><creator>Deess, Perry</creator><creator>Rudniy, Oleksandr</creator><creator>Joshi, Kamal</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T9</scope></search><sort><creationdate>201301</creationdate><title>Automated scoring in context: Rapid assessment for placed students</title><author>Klobucar, Andrew ; 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This study investigated the use of automated essay scoring (AES) to identify at-risk students enrolled in a first-year university writing course. An application of AES, the Criterion® Online Writing Evaluation Service was evaluated through a methodology focusing on construct modelling, response processes, disaggregation, extrapolation, generalization, and consequence. Based on the results of our two-year study with students (N=1,482) at a public technological research university in the United States, we found that Criterion offered a defined writing construct congruent with established models, achieved acceptance among students and instructors, showed no statistically significant differences between ethnicity groups of sufficient sample size, correlated at acceptable levels with other writing measures, performed in a stable fashion, and enabled instructors to identify at-risk students to increase their course success.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.asw.2012.10.001</doi><tpages>23</tpages></addata></record> |
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subjects | At Risk Students Automated essay scoring (AES) Automation College Freshmen Computer Assisted Testing Computer Software Evaluation Essay Tests Essays Ethnic Groups Research Universities Scoring Statistical Analysis Student Placement Validation methods Writing assessment Writing Evaluation Writing Instruction Writing placement |
title | Automated scoring in context: Rapid assessment for placed students |
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