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Scores using four automated and hand-calculated WE-CBM metrics were strongly correlated for word counts and spelled and sequenced word outcomes, though automated scoring overestimated certain complex metrics, limiting some decision errors. Results suggest feasibility for efficient scoring.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/accuracy-of-automated-written-expression-curriculum-based-measurement-scoring-article/598247/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/accuracy-of-automated-written-expression-curriculum-based-measurement-scoring-article/598247.png","ImageObject",300,407,{"name":42,"@type":43},"Mafia Boss","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-10-15",true,{"@type":52,"interactionType":53,"userInteractionCount":33},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What was the study designed to test about aWE-CBM?","Question",{"text":62,"@type":63},"The study examined whether automated written expression curriculum-based measurement could be accurately used to computer-score students’ writing samples for screening and progress monitoring.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"Which outcomes showed the strongest agreement between automated and hand-calculated scores?",{"text":67,"@type":63},"Automated and hand-calculated scores were highly correlated for total words written, correctly spelled words, correct word sequences, and correct minus incorrect word sequences across all assessment timepoints.",{"name":69,"@type":60,"acceptedAnswer":70},"Were there any limitations in the automated scoring accuracy?",{"text":71,"@type":63},"Yes. For correct minus incorrect word sequences, automated scores systematically overestimated hand-calculated scores, producing an unacceptable amount of error for some types of decisions.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},598247,1792211421,{"code":4,"msg":81,"data":82},"success",[83,87,91,95,100,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":81,"data":131},{"doc_id":78,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":33,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145,"preview_page_count":4},962090760730,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","Accuracy of Automated Written Expression Curriculum-Based Measurement Scoring  \nCanadian Journal of School Psychology 2021, Vol. 36(4) 304–317 © The Authors 2021  \nArticle reuse guidelines:  \n[sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/0829573520987753](DOI: 10.1177/0829573520987753)[ ](DOI: 10.1177/0829573520987753)[journals.sagepub.com/home/cjs](journals.sagepub.com/home/cjs)  \nSterett H. Mercer 1, Joanna E. Cannon 1, Bonita Squires 1,2, Yue Guo 1, and Ella Pinco 1  \nAbstract  \nWe examined the extent to which automated written expression curriculum-based measurement (aWE-CBM) can be accurately used to computer score student writing samples for screening and progress monitoring. Students (n = 174) with learning difficulties in Grades 1 to 12 who received 1:1 academic tutoring through a community-based organization completed narrative writing samples in the fall and spring across two academic years. The samples were evaluated using four automated and hand-calculated WE-CBM scoring metrics. Results indicated automated and hand-calculated scores were highly correlated at all four timepoints for counts of total words written (rs = 1.00), words spelled correctly (rs = .99–1.00), correct word sequences (CWS; rs = .96–.97), and correct minus incorrect word sequences (CIWS; rs = .86–.92). For CWS and CIWS, however, automated scores systematically overestimated hand-calculated scores, with an unacceptable amount of error for CIWS for some types of decisions. These findings provide preliminary evidence that aWE-CBM can be used to efficiently score narrative writing samples, potentially improving the feasibility of implementing multi-tiered systems of support in which the written expression skills of large numbers of students are screened and monitored.  \nKeywords  \nwritten expression, curriculum-based measurement, automated text evaluation, screening, progress monitoring  \n1 University of British Columbia, Vancouver, Canada 2Dalhousie University, Halifax, Canada  \nCorresponding Author:  \nSterett H. Mercer, Department of Educational and Counselling Psychology and Special Education, University of British Columbia, 2125 Main Mall, Vancouver, BC, Canada V6T 1Z4.  \nEmail: [sterett.mercer@ubc.ca](sterett.mercer@ubc.ca)  \nTo effectively support students with learning difficulties, measures that can identify which students need additional assistance and that can progress monitor the effectiveness of academic interventions are needed (Jung et al., 2018) . Since the 1970s, researchers in special education have examined curriculum-based measurement (CBM) for these purposes. CBMs are brief and efficient assessments that can be administered frequently during instruction, with evidence of reliability and validity for defensible decisions about student progress during instructional interventions (Deno, 1985) . For example, brief assessments of oral passage reading (i.e., number of words read correctly in 1 minute) work well as a technically adequate indicator of overall reading proficiency (Reschly et al., 2009), are sensitive to reading skill growth during intervention (Morgan & Sideridis, 2006), and improve student outcomes when used by teachers during intervention (Filderman et al., 2018) . Compared to reading CBM, research on written expression CBM (WE-CBM) is less well developed (Tindal, 2013) despite the importance of writing skills for students’ academic and occupational success (National Commission on Writing, 2004) .  \nAdministration of WE-CBM typically includes presentation of a short story starter (e.g.,“One day on the way to school, I. . .”), and then student generation of a 3-to 5-minute writing sample following a 1-minute planning time (Hosp et al., 2016) . Multiple WE-CBM metrics are utilized to score samples, for example, the total number of words written (TWW), counts of words spelled correctly (WSC), counts of correct words sequences (CWS, the number of adjac","cbCaiqXaKffsNZHz","https://ap.wps.com/l/cbCaiqXaKffsNZHz","pdf",494309,14,"English","# Abstract\n# Background and Need for Written Expression CBM\n## Curriculum-Based Measurement Foundations\n## Administration and Scoring Metrics for WE-CBM\n## Limitations in Current Availability and Standards\n# Challenges in Extending WE-CBM Beyond Early Grades\n## Reliability Needs for Longer Samples\n## Validity Differences Across Metrics\n# Feasibility via Automated Text Evaluation\n## Automated Scoring for Universal Screening","[{\"question\":\"What was the study designed to test about aWE-CBM?\",\"answer\":\"The study examined whether automated written expression curriculum-based measurement could be accurately used to computer-score students’ writing samples for screening and progress monitoring.\"},{\"question\":\"Which outcomes showed the strongest agreement between automated and hand-calculated scores?\",\"answer\":\"Automated and hand-calculated scores were highly correlated for total words written, correctly spelled words, correct word sequences, and correct minus incorrect word sequences across all assessment timepoints.\"},{\"question\":\"Were there any limitations in the automated scoring accuracy?\",\"answer\":\"Yes. For correct minus incorrect word sequences, automated scores systematically overestimated hand-calculated scores, producing an unacceptable amount of error for some types of decisions.\"}]","Accuracy of Automated Written Expression Curriculum-Based Measurement Scoring - Article | PDF",1792086565,35]