Loading…
A Distribution-Free Approach for Comparing Growth of Knowledge
The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indic...
Saved in:
Published in: | Journal of educational measurement 1994-03, Vol.31 (1), p.51-65 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303 |
---|---|
cites | cdi_FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303 |
container_end_page | 65 |
container_issue | 1 |
container_start_page | 51 |
container_title | Journal of educational measurement |
container_volume | 31 |
creator | Tan, E. S. Imbos, Tj Does, R. J. M. M. |
description | The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indicate, that, despite the possession of more knowledge at entrance, students with a low rate of growth of knowledge in the first year demonstrate a lower level of knowledge after the second academic year and continue to do so throughout the academic program when compared to students who show a higher rate of growth of knowledge in the first year. The analysis has been carried out using a distribution-free version of a longitudinal IRT-model suggested by Albers, Does, Imbos, and Janssen (1989). Furthermore, growth of knowledge has been described by means of a general regression model. Statistical inferences are possible using a randomization design extended to the situation where the observations are time-dependent proportions of correct answers. |
doi_str_mv | 10.1111/j.1745-3984.1994.tb00434.x |
format | article |
fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_1295276440</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ482617</ericid><jstor_id>1435097</jstor_id><sourcerecordid>1435097</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303</originalsourceid><addsrcrecordid>eNqVkUtPwkAUhSdGExH9By4aXbfOs9O6ICG8FFBjopi4mbRlBlqhU6clwL93mhJYO5s7yXfPuTfnAnCHoIfse8g8xClzSRhQD4Uh9aoYQkqotzsDrSM6By0IMXahz9gluCrLDELEOEMt0Ok6_bSsTBpvqlTn7tBI6XSLwugoWTpKG6en10Vk0nzhjIzeVktHK2eS6-1KzhfyGlyoaFXKm0Ntg8_h4KP35E7fRs-97tRNKA-Qq2Ag55jSmElilyAoRv4cMuVDjhlWiGH7CySP5yT0CSM4wliyBPsqZiomkLTBfeNrF_vdyLISmd6Y3I4UCIcMc5_Suuux6UqMLksjlShMuo7MXiAo6rxEJupQRB2KqPMSh7zEzopvG7E0aXIUDsY0wD7iFncavE1Xcv8PYzEe9F8YOvlnZaXNyYASBsPa322wvYbcHXFkfoTPCWfi63UkZhTOJu_fWATkD2JqkfI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1295276440</pqid></control><display><type>article</type><title>A Distribution-Free Approach for Comparing Growth of Knowledge</title><source>JSTOR Archival Journals and Primary Sources Collection</source><source>ERIC</source><creator>Tan, E. S. ; Imbos, Tj ; Does, R. J. M. M.</creator><creatorcontrib>Tan, E. S. ; Imbos, Tj ; Does, R. J. M. M.</creatorcontrib><description>The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indicate, that, despite the possession of more knowledge at entrance, students with a low rate of growth of knowledge in the first year demonstrate a lower level of knowledge after the second academic year and continue to do so throughout the academic program when compared to students who show a higher rate of growth of knowledge in the first year. The analysis has been carried out using a distribution-free version of a longitudinal IRT-model suggested by Albers, Does, Imbos, and Janssen (1989). Furthermore, growth of knowledge has been described by means of a general regression model. Statistical inferences are possible using a randomization design extended to the situation where the observations are time-dependent proportions of correct answers.</description><identifier>ISSN: 0022-0655</identifier><identifier>EISSN: 1745-3984</identifier><identifier>DOI: 10.1111/j.1745-3984.1994.tb00434.x</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>Academic Achievement ; Analysis of variance ; Change ; Comparative Analysis ; Educational research ; Foreign Countries ; Item Response Theory ; Knowledge Level ; Longitudinal Studies ; Medical Education ; Medical schools ; Medical Students ; Modeling ; Netherlands ; Nursing students ; P values ; Prediction ; Proportions ; Random allocation ; Regression analysis ; Statistical Distributions ; Stochastic Analysis</subject><ispartof>Journal of educational measurement, 1994-03, Vol.31 (1), p.51-65</ispartof><rights>Copyright 1994 National Council on Measurement in Education</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303</citedby><cites>FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/1435097$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/1435097$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,58238,58471</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ482617$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Tan, E. S.</creatorcontrib><creatorcontrib>Imbos, Tj</creatorcontrib><creatorcontrib>Does, R. J. M. M.</creatorcontrib><title>A Distribution-Free Approach for Comparing Growth of Knowledge</title><title>Journal of educational measurement</title><description>The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indicate, that, despite the possession of more knowledge at entrance, students with a low rate of growth of knowledge in the first year demonstrate a lower level of knowledge after the second academic year and continue to do so throughout the academic program when compared to students who show a higher rate of growth of knowledge in the first year. The analysis has been carried out using a distribution-free version of a longitudinal IRT-model suggested by Albers, Does, Imbos, and Janssen (1989). Furthermore, growth of knowledge has been described by means of a general regression model. Statistical inferences are possible using a randomization design extended to the situation where the observations are time-dependent proportions of correct answers.</description><subject>Academic Achievement</subject><subject>Analysis of variance</subject><subject>Change</subject><subject>Comparative Analysis</subject><subject>Educational research</subject><subject>Foreign Countries</subject><subject>Item Response Theory</subject><subject>Knowledge Level</subject><subject>Longitudinal Studies</subject><subject>Medical Education</subject><subject>Medical schools</subject><subject>Medical Students</subject><subject>Modeling</subject><subject>Netherlands</subject><subject>Nursing students</subject><subject>P values</subject><subject>Prediction</subject><subject>Proportions</subject><subject>Random allocation</subject><subject>Regression analysis</subject><subject>Statistical Distributions</subject><subject>Stochastic Analysis</subject><issn>0022-0655</issn><issn>1745-3984</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1994</creationdate><recordtype>article</recordtype><sourceid>7SW</sourceid><recordid>eNqVkUtPwkAUhSdGExH9By4aXbfOs9O6ICG8FFBjopi4mbRlBlqhU6clwL93mhJYO5s7yXfPuTfnAnCHoIfse8g8xClzSRhQD4Uh9aoYQkqotzsDrSM6By0IMXahz9gluCrLDELEOEMt0Ok6_bSsTBpvqlTn7tBI6XSLwugoWTpKG6en10Vk0nzhjIzeVktHK2eS6-1KzhfyGlyoaFXKm0Ntg8_h4KP35E7fRs-97tRNKA-Qq2Ag55jSmElilyAoRv4cMuVDjhlWiGH7CySP5yT0CSM4wliyBPsqZiomkLTBfeNrF_vdyLISmd6Y3I4UCIcMc5_Suuux6UqMLksjlShMuo7MXiAo6rxEJupQRB2KqPMSh7zEzopvG7E0aXIUDsY0wD7iFncavE1Xcv8PYzEe9F8YOvlnZaXNyYASBsPa322wvYbcHXFkfoTPCWfi63UkZhTOJu_fWATkD2JqkfI</recordid><startdate>199403</startdate><enddate>199403</enddate><creator>Tan, E. S.</creator><creator>Imbos, Tj</creator><creator>Does, R. J. M. M.</creator><general>Blackwell Publishing Ltd</general><general>National Council on Measurement in Education</general><scope>BSCLL</scope><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>JILTI</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope></search><sort><creationdate>199403</creationdate><title>A Distribution-Free Approach for Comparing Growth of Knowledge</title><author>Tan, E. S. ; Imbos, Tj ; Does, R. J. M. M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Academic Achievement</topic><topic>Analysis of variance</topic><topic>Change</topic><topic>Comparative Analysis</topic><topic>Educational research</topic><topic>Foreign Countries</topic><topic>Item Response Theory</topic><topic>Knowledge Level</topic><topic>Longitudinal Studies</topic><topic>Medical Education</topic><topic>Medical schools</topic><topic>Medical Students</topic><topic>Modeling</topic><topic>Netherlands</topic><topic>Nursing students</topic><topic>P values</topic><topic>Prediction</topic><topic>Proportions</topic><topic>Random allocation</topic><topic>Regression analysis</topic><topic>Statistical Distributions</topic><topic>Stochastic Analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tan, E. S.</creatorcontrib><creatorcontrib>Imbos, Tj</creatorcontrib><creatorcontrib>Does, R. J. M. M.</creatorcontrib><collection>Istex</collection><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>Periodicals Index Online Segment 32</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><jtitle>Journal of educational measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tan, E. S.</au><au>Imbos, Tj</au><au>Does, R. J. M. M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ482617</ericid><atitle>A Distribution-Free Approach for Comparing Growth of Knowledge</atitle><jtitle>Journal of educational measurement</jtitle><date>1994-03</date><risdate>1994</risdate><volume>31</volume><issue>1</issue><spage>51</spage><epage>65</epage><pages>51-65</pages><issn>0022-0655</issn><eissn>1745-3984</eissn><abstract>The longitudinal testing of student achievement requires the solution of several new problem areas. In this article, several small groups of medical students at the University of Limburg Medical School in Maastricht, The Netherlands, are compared with respect to their performances. The results indicate, that, despite the possession of more knowledge at entrance, students with a low rate of growth of knowledge in the first year demonstrate a lower level of knowledge after the second academic year and continue to do so throughout the academic program when compared to students who show a higher rate of growth of knowledge in the first year. The analysis has been carried out using a distribution-free version of a longitudinal IRT-model suggested by Albers, Does, Imbos, and Janssen (1989). Furthermore, growth of knowledge has been described by means of a general regression model. Statistical inferences are possible using a randomization design extended to the situation where the observations are time-dependent proportions of correct answers.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/j.1745-3984.1994.tb00434.x</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0022-0655 |
ispartof | Journal of educational measurement, 1994-03, Vol.31 (1), p.51-65 |
issn | 0022-0655 1745-3984 |
language | eng |
recordid | cdi_proquest_journals_1295276440 |
source | JSTOR Archival Journals and Primary Sources Collection; ERIC |
subjects | Academic Achievement Analysis of variance Change Comparative Analysis Educational research Foreign Countries Item Response Theory Knowledge Level Longitudinal Studies Medical Education Medical schools Medical Students Modeling Netherlands Nursing students P values Prediction Proportions Random allocation Regression analysis Statistical Distributions Stochastic Analysis |
title | A Distribution-Free Approach for Comparing Growth of Knowledge |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T23%3A41%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Distribution-Free%20Approach%20for%20Comparing%20Growth%20of%20Knowledge&rft.jtitle=Journal%20of%20educational%20measurement&rft.au=Tan,%20E.%20S.&rft.date=1994-03&rft.volume=31&rft.issue=1&rft.spage=51&rft.epage=65&rft.pages=51-65&rft.issn=0022-0655&rft.eissn=1745-3984&rft_id=info:doi/10.1111/j.1745-3984.1994.tb00434.x&rft_dat=%3Cjstor_proqu%3E1435097%3C/jstor_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4781-f08ed244b5e306531b16d05f607252f1526078e7bd3963532a22e5c26fb5fb303%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1295276440&rft_id=info:pmid/&rft_ericid=EJ482617&rft_jstor_id=1435097&rfr_iscdi=true |