Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables
Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added est...
Gespeichert in:
Veröffentlicht in: | Journal of research on educational effectiveness 2015-01, Vol.8 (1), p.60-83 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 83 |
---|---|
container_issue | 1 |
container_start_page | 60 |
container_title | Journal of research on educational effectiveness |
container_volume | 8 |
creator | Johnson, Matthew T. Lipscomb, Stephen Gill, Brian |
description | Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they include student and peer background characteristics, and a double-lagged achievement score. We also consider two previously unexplored model variations: (a) replacing classroom peer characteristics with teacher-level averages, and (b) allowing demographics to influence the relationship between current and prior achievement. Using data from a northern state, we find that teacher effectiveness estimates are highly correlated across specifications. However, up to 26% of teachers in the bottom quintile using one specification are ranked higher using another specification. Differences between VAMs have direct implications for which estimates change. In particular, teachers in a district with a large fraction of disadvantaged students receive lower ratings when background characteristics are omitted. Other modeling choices have smaller practical consequences, and none are as important as selecting which assessment to use as the outcome measure. |
doi_str_mv | 10.1080/19345747.2014.967898 |
format | Article |
fullrecord | <record><control><sourceid>proquest_eric_</sourceid><recordid>TN_cdi_eric_primary_EJ1049638</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ1049638</ericid><sourcerecordid>3604017831</sourcerecordid><originalsourceid>FETCH-LOGICAL-c403t-22552f698ffe86b7beeed81fab21aa9496380abc87e1dce912a4c968cd01a1af3</originalsourceid><addsrcrecordid>eNp9UE1LAzEQXUTBWv0HCgHPW5PNfiQnkVK_KCi2eg3ZZIIp201Nskr_vVtXe_Q0w7z35s28JDkneEIww1eE07yo8mqSYZJPeFkxzg6S0W6cFhXlh_s-r46TkxBWGJeEUjZKXhbQBhvtp41b5AxaglTv4NGbbDpIb7QGjWYh2rWMEFB0aBE7DW1EstXoGXrm1LXRu6ZXeCvrBsJpcmRkE-Dst46T19vZcnqfzp_uHqY381TlmMY0y4oiMyVnxgAr66oGAM2IkXVGpOQ5LynDslasAqIVcJLJXPGSKY2JJNLQcXI57N1499FBiGLlOt_2loKUBcNFxknZs_KBpbwLwYMRG99_47eCYLFLT_ylJ3bpiSG9XnYxyMBbtZfMHgn-OazHrwfctsb5tfxyvtEiym3jvPGyVTYI-q_DN4azgAk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1658052916</pqid></control><display><type>article</type><title>Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables</title><source>EBSCOhost Education Source</source><creator>Johnson, Matthew T. ; Lipscomb, Stephen ; Gill, Brian</creator><creatorcontrib>Johnson, Matthew T. ; Lipscomb, Stephen ; Gill, Brian</creatorcontrib><description>Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they include student and peer background characteristics, and a double-lagged achievement score. We also consider two previously unexplored model variations: (a) replacing classroom peer characteristics with teacher-level averages, and (b) allowing demographics to influence the relationship between current and prior achievement. Using data from a northern state, we find that teacher effectiveness estimates are highly correlated across specifications. However, up to 26% of teachers in the bottom quintile using one specification are ranked higher using another specification. Differences between VAMs have direct implications for which estimates change. In particular, teachers in a district with a large fraction of disadvantaged students receive lower ratings when background characteristics are omitted. Other modeling choices have smaller practical consequences, and none are as important as selecting which assessment to use as the outcome measure.</description><identifier>ISSN: 1934-5747</identifier><identifier>EISSN: 1934-5739</identifier><identifier>DOI: 10.1080/19345747.2014.967898</identifier><language>eng</language><publisher>Philadelphia: Routledge</publisher><subject>Academic Achievement ; Computation ; Correlation ; Decision making models ; Demography ; Disadvantaged Youth ; education ; Education policy ; Equations (Mathematics) ; Estimating techniques ; Florida ; Grade 5 ; Grade 8 ; Illinois ; Mathematics Achievement ; Outcome Measures ; Peer Influence ; Pennsylvania ; Policy making ; Reading Achievement ; School Districts ; Scores ; Sensitivity ; Student Characteristics ; Teacher Effectiveness ; Teacher Evaluation ; Teacher Influence ; Teachers ; United States (North) ; Value Added Models</subject><ispartof>Journal of research on educational effectiveness, 2015-01, Vol.8 (1), p.60-83</ispartof><rights>Copyright © Taylor & Francis Group, LLC 2015</rights><rights>Copyright Taylor & Francis Ltd. 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c403t-22552f698ffe86b7beeed81fab21aa9496380abc87e1dce912a4c968cd01a1af3</citedby><cites>FETCH-LOGICAL-c403t-22552f698ffe86b7beeed81fab21aa9496380abc87e1dce912a4c968cd01a1af3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1049638$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Johnson, Matthew T.</creatorcontrib><creatorcontrib>Lipscomb, Stephen</creatorcontrib><creatorcontrib>Gill, Brian</creatorcontrib><title>Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables</title><title>Journal of research on educational effectiveness</title><description>Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they include student and peer background characteristics, and a double-lagged achievement score. We also consider two previously unexplored model variations: (a) replacing classroom peer characteristics with teacher-level averages, and (b) allowing demographics to influence the relationship between current and prior achievement. Using data from a northern state, we find that teacher effectiveness estimates are highly correlated across specifications. However, up to 26% of teachers in the bottom quintile using one specification are ranked higher using another specification. Differences between VAMs have direct implications for which estimates change. In particular, teachers in a district with a large fraction of disadvantaged students receive lower ratings when background characteristics are omitted. Other modeling choices have smaller practical consequences, and none are as important as selecting which assessment to use as the outcome measure.</description><subject>Academic Achievement</subject><subject>Computation</subject><subject>Correlation</subject><subject>Decision making models</subject><subject>Demography</subject><subject>Disadvantaged Youth</subject><subject>education</subject><subject>Education policy</subject><subject>Equations (Mathematics)</subject><subject>Estimating techniques</subject><subject>Florida</subject><subject>Grade 5</subject><subject>Grade 8</subject><subject>Illinois</subject><subject>Mathematics Achievement</subject><subject>Outcome Measures</subject><subject>Peer Influence</subject><subject>Pennsylvania</subject><subject>Policy making</subject><subject>Reading Achievement</subject><subject>School Districts</subject><subject>Scores</subject><subject>Sensitivity</subject><subject>Student Characteristics</subject><subject>Teacher Effectiveness</subject><subject>Teacher Evaluation</subject><subject>Teacher Influence</subject><subject>Teachers</subject><subject>United States (North)</subject><subject>Value Added Models</subject><issn>1934-5747</issn><issn>1934-5739</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9UE1LAzEQXUTBWv0HCgHPW5PNfiQnkVK_KCi2eg3ZZIIp201Nskr_vVtXe_Q0w7z35s28JDkneEIww1eE07yo8mqSYZJPeFkxzg6S0W6cFhXlh_s-r46TkxBWGJeEUjZKXhbQBhvtp41b5AxaglTv4NGbbDpIb7QGjWYh2rWMEFB0aBE7DW1EstXoGXrm1LXRu6ZXeCvrBsJpcmRkE-Dst46T19vZcnqfzp_uHqY381TlmMY0y4oiMyVnxgAr66oGAM2IkXVGpOQ5LynDslasAqIVcJLJXPGSKY2JJNLQcXI57N1499FBiGLlOt_2loKUBcNFxknZs_KBpbwLwYMRG99_47eCYLFLT_ylJ3bpiSG9XnYxyMBbtZfMHgn-OazHrwfctsb5tfxyvtEiym3jvPGyVTYI-q_DN4azgAk</recordid><startdate>20150102</startdate><enddate>20150102</enddate><creator>Johnson, Matthew T.</creator><creator>Lipscomb, Stephen</creator><creator>Gill, Brian</creator><general>Routledge</general><general>Taylor & Francis 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></search><sort><creationdate>20150102</creationdate><title>Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables</title><author>Johnson, Matthew T. ; Lipscomb, Stephen ; Gill, Brian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c403t-22552f698ffe86b7beeed81fab21aa9496380abc87e1dce912a4c968cd01a1af3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Academic Achievement</topic><topic>Computation</topic><topic>Correlation</topic><topic>Decision making models</topic><topic>Demography</topic><topic>Disadvantaged Youth</topic><topic>education</topic><topic>Education policy</topic><topic>Equations (Mathematics)</topic><topic>Estimating techniques</topic><topic>Florida</topic><topic>Grade 5</topic><topic>Grade 8</topic><topic>Illinois</topic><topic>Mathematics Achievement</topic><topic>Outcome Measures</topic><topic>Peer Influence</topic><topic>Pennsylvania</topic><topic>Policy making</topic><topic>Reading Achievement</topic><topic>School Districts</topic><topic>Scores</topic><topic>Sensitivity</topic><topic>Student Characteristics</topic><topic>Teacher Effectiveness</topic><topic>Teacher Evaluation</topic><topic>Teacher Influence</topic><topic>Teachers</topic><topic>United States (North)</topic><topic>Value Added Models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Johnson, Matthew T.</creatorcontrib><creatorcontrib>Lipscomb, Stephen</creatorcontrib><creatorcontrib>Gill, Brian</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><jtitle>Journal of research on educational effectiveness</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Johnson, Matthew T.</au><au>Lipscomb, Stephen</au><au>Gill, Brian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1049638</ericid><atitle>Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables</atitle><jtitle>Journal of research on educational effectiveness</jtitle><date>2015-01-02</date><risdate>2015</risdate><volume>8</volume><issue>1</issue><spage>60</spage><epage>83</epage><pages>60-83</pages><issn>1934-5747</issn><eissn>1934-5739</eissn><abstract>Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they include student and peer background characteristics, and a double-lagged achievement score. We also consider two previously unexplored model variations: (a) replacing classroom peer characteristics with teacher-level averages, and (b) allowing demographics to influence the relationship between current and prior achievement. Using data from a northern state, we find that teacher effectiveness estimates are highly correlated across specifications. However, up to 26% of teachers in the bottom quintile using one specification are ranked higher using another specification. Differences between VAMs have direct implications for which estimates change. In particular, teachers in a district with a large fraction of disadvantaged students receive lower ratings when background characteristics are omitted. Other modeling choices have smaller practical consequences, and none are as important as selecting which assessment to use as the outcome measure.</abstract><cop>Philadelphia</cop><pub>Routledge</pub><doi>10.1080/19345747.2014.967898</doi><tpages>24</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1934-5747 |
ispartof | Journal of research on educational effectiveness, 2015-01, Vol.8 (1), p.60-83 |
issn | 1934-5747 1934-5739 |
language | eng |
recordid | cdi_eric_primary_EJ1049638 |
source | EBSCOhost Education Source |
subjects | Academic Achievement Computation Correlation Decision making models Demography Disadvantaged Youth education Education policy Equations (Mathematics) Estimating techniques Florida Grade 5 Grade 8 Illinois Mathematics Achievement Outcome Measures Peer Influence Pennsylvania Policy making Reading Achievement School Districts Scores Sensitivity Student Characteristics Teacher Effectiveness Teacher Evaluation Teacher Influence Teachers United States (North) Value Added Models |
title | Sensitivity of Teacher Value-Added Estimates to Student and Peer Control Variables |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T14%3A54%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_eric_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sensitivity%20of%20Teacher%20Value-Added%20Estimates%20to%20Student%20and%20Peer%20Control%20Variables&rft.jtitle=Journal%20of%20research%20on%20educational%20effectiveness&rft.au=Johnson,%20Matthew%20T.&rft.date=2015-01-02&rft.volume=8&rft.issue=1&rft.spage=60&rft.epage=83&rft.pages=60-83&rft.issn=1934-5747&rft.eissn=1934-5739&rft_id=info:doi/10.1080/19345747.2014.967898&rft_dat=%3Cproquest_eric_%3E3604017831%3C/proquest_eric_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1658052916&rft_id=info:pmid/&rft_ericid=EJ1049638&rfr_iscdi=true |