Determining cloze item difficulty from item and passage characteristics across different learner backgrounds

Cloze tests have been the subject of numerous studies regarding their function and use in both first language and second language contexts (e.g., Jonz & Oller, 1994; Watanabe & Koyama, 2008). From a validity standpoint, one area of investigation has been the extent to which cloze tests measu...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Language testing 2017-04, Vol.34 (2), p.151-174
Hauptverfasser: Trace, Jonathan, Brown, James Dean, Janssen, Gerriet, Kozhevnikova, Liudmila
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 174
container_issue 2
container_start_page 151
container_title Language testing
container_volume 34
creator Trace, Jonathan
Brown, James Dean
Janssen, Gerriet
Kozhevnikova, Liudmila
description Cloze tests have been the subject of numerous studies regarding their function and use in both first language and second language contexts (e.g., Jonz & Oller, 1994; Watanabe & Koyama, 2008). From a validity standpoint, one area of investigation has been the extent to which cloze tests measure reading ability beyond the sentence level. Using test data from 50 30-item cloze passages administered to 2,298 Japanese and 5,170 Russian EFL students, this study examined the degree to which linguistic features for cloze passages and items influenced item difficulty. Using a common set of 10 anchor items, all 50 tests were modeled in terms of person ability and item difficulty onto a single scale using many-faceted Rasch measurement (k = 1314). Principle components analysis was then used to categorize 25 linguistic item- and passage-level variables for the 50 cloze tests and their respective items, from which three components for each passage- and item-level variables were identified. These six factors along with item difficulty were then entered into both a hierarchical structural equation model and a linear multiple regression to determine the degree to which difficulty in cloze tests could be explained separately by passage and item features. Comparisons were further made by looking at differences in models by nationality and by proficiency level (e.g., high and low). The analyses revealed noteworthy differences in mean item difficulties and in the variance structures between passage- and item-level features, as well as between different examinee proficiency groups.
doi_str_mv 10.1177/0265532215623581
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1879784991</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ1134734</ericid><sage_id>10.1177_0265532215623581</sage_id><sourcerecordid>1879784991</sourcerecordid><originalsourceid>FETCH-LOGICAL-c331t-aeb15f75153cd9c4ebee2f307067c5295dfb9cce994e7c77c8bb920e80a39a193</originalsourceid><addsrcrecordid>eNp1UEtLxDAQDqLgunr3IgQ8V5OmaZqjrOuLBS96Lul0smbtY03aw_rrbbciIngamO8x832EnHN2xblS1yxOpRRxzGUaC5nxAzLjiVIR00l6SGYjHI34MTkJYcMY01ykM1LdYoe-do1r1hSq9hOp67CmpbPWQV91O2p9W09L05R0a0Iwa6TwZryBQetC5yBQA74NYa9Dj01HKzS-QU8LA-9r3_ZNGU7JkTVVwLPvOSevd8uXxUO0er5_XNysIhCCd5HBgkurJJcCSg0JFoixFUyxVIGMtSxtoQFQ6wQVKAVZUeiYYcaM0IZrMSeXk-_Wtx89hi7ftL1vhpM5z5RWWaKH9HPCJtb-c48233pXG7_LOcvHTvO_nQ6Si0kyxIYf-vKJc5EokQx4NOFjRb-O_uf3BfrjgeA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1879784991</pqid></control><display><type>article</type><title>Determining cloze item difficulty from item and passage characteristics across different learner backgrounds</title><source>SAGE Complete A-Z List</source><creator>Trace, Jonathan ; Brown, James Dean ; Janssen, Gerriet ; Kozhevnikova, Liudmila</creator><creatorcontrib>Trace, Jonathan ; Brown, James Dean ; Janssen, Gerriet ; Kozhevnikova, Liudmila</creatorcontrib><description>Cloze tests have been the subject of numerous studies regarding their function and use in both first language and second language contexts (e.g., Jonz &amp; Oller, 1994; Watanabe &amp; Koyama, 2008). From a validity standpoint, one area of investigation has been the extent to which cloze tests measure reading ability beyond the sentence level. Using test data from 50 30-item cloze passages administered to 2,298 Japanese and 5,170 Russian EFL students, this study examined the degree to which linguistic features for cloze passages and items influenced item difficulty. Using a common set of 10 anchor items, all 50 tests were modeled in terms of person ability and item difficulty onto a single scale using many-faceted Rasch measurement (k = 1314). Principle components analysis was then used to categorize 25 linguistic item- and passage-level variables for the 50 cloze tests and their respective items, from which three components for each passage- and item-level variables were identified. These six factors along with item difficulty were then entered into both a hierarchical structural equation model and a linear multiple regression to determine the degree to which difficulty in cloze tests could be explained separately by passage and item features. Comparisons were further made by looking at differences in models by nationality and by proficiency level (e.g., high and low). The analyses revealed noteworthy differences in mean item difficulties and in the variance structures between passage- and item-level features, as well as between different examinee proficiency groups.</description><identifier>ISSN: 0265-5322</identifier><identifier>EISSN: 1477-0946</identifier><identifier>DOI: 10.1177/0265532215623581</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Cloze Procedure ; College Students ; Comparative Analysis ; Cross Cultural Studies ; Difficulty Level ; Educational psychology ; English (Second Language) ; English as a second language tests ; Factor Analysis ; Foreign Countries ; Item Analysis ; Japanese language ; Language Proficiency ; Language Tests ; Linguistics ; Measurement Techniques ; Multiple Regression Analysis ; Rasch model ; Reading Ability ; Russian language ; Second Language Learning ; Statistical Analysis ; Structural equation modeling ; Structural Equation Models ; Test Items ; Test Validity</subject><ispartof>Language testing, 2017-04, Vol.34 (2), p.151-174</ispartof><rights>The Author(s) 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-aeb15f75153cd9c4ebee2f307067c5295dfb9cce994e7c77c8bb920e80a39a193</citedby><cites>FETCH-LOGICAL-c331t-aeb15f75153cd9c4ebee2f307067c5295dfb9cce994e7c77c8bb920e80a39a193</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0265532215623581$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0265532215623581$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21799,27903,27904,43600,43601</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1134734$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Trace, Jonathan</creatorcontrib><creatorcontrib>Brown, James Dean</creatorcontrib><creatorcontrib>Janssen, Gerriet</creatorcontrib><creatorcontrib>Kozhevnikova, Liudmila</creatorcontrib><title>Determining cloze item difficulty from item and passage characteristics across different learner backgrounds</title><title>Language testing</title><description>Cloze tests have been the subject of numerous studies regarding their function and use in both first language and second language contexts (e.g., Jonz &amp; Oller, 1994; Watanabe &amp; Koyama, 2008). From a validity standpoint, one area of investigation has been the extent to which cloze tests measure reading ability beyond the sentence level. Using test data from 50 30-item cloze passages administered to 2,298 Japanese and 5,170 Russian EFL students, this study examined the degree to which linguistic features for cloze passages and items influenced item difficulty. Using a common set of 10 anchor items, all 50 tests were modeled in terms of person ability and item difficulty onto a single scale using many-faceted Rasch measurement (k = 1314). Principle components analysis was then used to categorize 25 linguistic item- and passage-level variables for the 50 cloze tests and their respective items, from which three components for each passage- and item-level variables were identified. These six factors along with item difficulty were then entered into both a hierarchical structural equation model and a linear multiple regression to determine the degree to which difficulty in cloze tests could be explained separately by passage and item features. Comparisons were further made by looking at differences in models by nationality and by proficiency level (e.g., high and low). The analyses revealed noteworthy differences in mean item difficulties and in the variance structures between passage- and item-level features, as well as between different examinee proficiency groups.</description><subject>Cloze Procedure</subject><subject>College Students</subject><subject>Comparative Analysis</subject><subject>Cross Cultural Studies</subject><subject>Difficulty Level</subject><subject>Educational psychology</subject><subject>English (Second Language)</subject><subject>English as a second language tests</subject><subject>Factor Analysis</subject><subject>Foreign Countries</subject><subject>Item Analysis</subject><subject>Japanese language</subject><subject>Language Proficiency</subject><subject>Language Tests</subject><subject>Linguistics</subject><subject>Measurement Techniques</subject><subject>Multiple Regression Analysis</subject><subject>Rasch model</subject><subject>Reading Ability</subject><subject>Russian language</subject><subject>Second Language Learning</subject><subject>Statistical Analysis</subject><subject>Structural equation modeling</subject><subject>Structural Equation Models</subject><subject>Test Items</subject><subject>Test Validity</subject><issn>0265-5322</issn><issn>1477-0946</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1UEtLxDAQDqLgunr3IgQ8V5OmaZqjrOuLBS96Lul0smbtY03aw_rrbbciIngamO8x832EnHN2xblS1yxOpRRxzGUaC5nxAzLjiVIR00l6SGYjHI34MTkJYcMY01ykM1LdYoe-do1r1hSq9hOp67CmpbPWQV91O2p9W09L05R0a0Iwa6TwZryBQetC5yBQA74NYa9Dj01HKzS-QU8LA-9r3_ZNGU7JkTVVwLPvOSevd8uXxUO0er5_XNysIhCCd5HBgkurJJcCSg0JFoixFUyxVIGMtSxtoQFQ6wQVKAVZUeiYYcaM0IZrMSeXk-_Wtx89hi7ftL1vhpM5z5RWWaKH9HPCJtb-c48233pXG7_LOcvHTvO_nQ6Si0kyxIYf-vKJc5EokQx4NOFjRb-O_uf3BfrjgeA</recordid><startdate>201704</startdate><enddate>201704</enddate><creator>Trace, Jonathan</creator><creator>Brown, James Dean</creator><creator>Janssen, Gerriet</creator><creator>Kozhevnikova, Liudmila</creator><general>SAGE Publications</general><general>Sage Publications Ltd</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>201704</creationdate><title>Determining cloze item difficulty from item and passage characteristics across different learner backgrounds</title><author>Trace, Jonathan ; Brown, James Dean ; Janssen, Gerriet ; Kozhevnikova, Liudmila</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-aeb15f75153cd9c4ebee2f307067c5295dfb9cce994e7c77c8bb920e80a39a193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Cloze Procedure</topic><topic>College Students</topic><topic>Comparative Analysis</topic><topic>Cross Cultural Studies</topic><topic>Difficulty Level</topic><topic>Educational psychology</topic><topic>English (Second Language)</topic><topic>English as a second language tests</topic><topic>Factor Analysis</topic><topic>Foreign Countries</topic><topic>Item Analysis</topic><topic>Japanese language</topic><topic>Language Proficiency</topic><topic>Language Tests</topic><topic>Linguistics</topic><topic>Measurement Techniques</topic><topic>Multiple Regression Analysis</topic><topic>Rasch model</topic><topic>Reading Ability</topic><topic>Russian language</topic><topic>Second Language Learning</topic><topic>Statistical Analysis</topic><topic>Structural equation modeling</topic><topic>Structural Equation Models</topic><topic>Test Items</topic><topic>Test Validity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Trace, Jonathan</creatorcontrib><creatorcontrib>Brown, James Dean</creatorcontrib><creatorcontrib>Janssen, Gerriet</creatorcontrib><creatorcontrib>Kozhevnikova, Liudmila</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>CrossRef</collection><collection>Linguistics and Language Behavior Abstracts (LLBA)</collection><jtitle>Language testing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Trace, Jonathan</au><au>Brown, James Dean</au><au>Janssen, Gerriet</au><au>Kozhevnikova, Liudmila</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1134734</ericid><atitle>Determining cloze item difficulty from item and passage characteristics across different learner backgrounds</atitle><jtitle>Language testing</jtitle><date>2017-04</date><risdate>2017</risdate><volume>34</volume><issue>2</issue><spage>151</spage><epage>174</epage><pages>151-174</pages><issn>0265-5322</issn><eissn>1477-0946</eissn><abstract>Cloze tests have been the subject of numerous studies regarding their function and use in both first language and second language contexts (e.g., Jonz &amp; Oller, 1994; Watanabe &amp; Koyama, 2008). From a validity standpoint, one area of investigation has been the extent to which cloze tests measure reading ability beyond the sentence level. Using test data from 50 30-item cloze passages administered to 2,298 Japanese and 5,170 Russian EFL students, this study examined the degree to which linguistic features for cloze passages and items influenced item difficulty. Using a common set of 10 anchor items, all 50 tests were modeled in terms of person ability and item difficulty onto a single scale using many-faceted Rasch measurement (k = 1314). Principle components analysis was then used to categorize 25 linguistic item- and passage-level variables for the 50 cloze tests and their respective items, from which three components for each passage- and item-level variables were identified. These six factors along with item difficulty were then entered into both a hierarchical structural equation model and a linear multiple regression to determine the degree to which difficulty in cloze tests could be explained separately by passage and item features. Comparisons were further made by looking at differences in models by nationality and by proficiency level (e.g., high and low). The analyses revealed noteworthy differences in mean item difficulties and in the variance structures between passage- and item-level features, as well as between different examinee proficiency groups.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/0265532215623581</doi><tpages>24</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0265-5322
ispartof Language testing, 2017-04, Vol.34 (2), p.151-174
issn 0265-5322
1477-0946
language eng
recordid cdi_proquest_journals_1879784991
source SAGE Complete A-Z List
subjects Cloze Procedure
College Students
Comparative Analysis
Cross Cultural Studies
Difficulty Level
Educational psychology
English (Second Language)
English as a second language tests
Factor Analysis
Foreign Countries
Item Analysis
Japanese language
Language Proficiency
Language Tests
Linguistics
Measurement Techniques
Multiple Regression Analysis
Rasch model
Reading Ability
Russian language
Second Language Learning
Statistical Analysis
Structural equation modeling
Structural Equation Models
Test Items
Test Validity
title Determining cloze item difficulty from item and passage characteristics across different learner backgrounds
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T21%3A05%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Determining%20cloze%20item%20difficulty%20from%20item%20and%20passage%20characteristics%20across%20different%20learner%20backgrounds&rft.jtitle=Language%20testing&rft.au=Trace,%20Jonathan&rft.date=2017-04&rft.volume=34&rft.issue=2&rft.spage=151&rft.epage=174&rft.pages=151-174&rft.issn=0265-5322&rft.eissn=1477-0946&rft_id=info:doi/10.1177/0265532215623581&rft_dat=%3Cproquest_cross%3E1879784991%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1879784991&rft_id=info:pmid/&rft_ericid=EJ1134734&rft_sage_id=10.1177_0265532215623581&rfr_iscdi=true