The uses of process data in large-scale educational assessments:
The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Paris
OECD Publishing
2023
|
Schriftenreihe: | OECD Education Working Papers
no.286 |
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in assessments. However, it is now being used for multiple purposes across the assessment cycle. Process data is being deliberately captured and used in large-scale, standardized assessments - moving from viewing it as a "by-product" of digital assessment, to its use "by design" to extend understanding of test-taker performance and engagement. While these techniques offer significant benefits, they also require appropriate validation practices to ensure that their use supports reliable inferences and do not introduce unintended negative consequences |
Beschreibung: | 1 Online-Ressource (23 Seiten) |
DOI: | 10.1787/5d9009ff-en |
Internformat
MARC
LEADER | 00000nam a22000001cb4500 | ||
---|---|---|---|
001 | BV049038330 | ||
003 | DE-604 | ||
007 | cr|uuu---uuuuu | ||
008 | 230706s2023 xx o|||| 00||| eng d | ||
024 | 7 | |a 10.1787/5d9009ff-en |2 doi | |
035 | |a (ZDB-13-SOC)09269117X | ||
035 | |a (OCoLC)1390801970 | ||
035 | |a (DE-599)KEP09269117X | ||
040 | |a DE-604 |b ger |e rda | ||
041 | 0 | |a eng | |
049 | |a DE-521 |a DE-1028 |a DE-573 |a DE-92 |a DE-898 |a DE-1049 |a DE-861 |a DE-91 |a DE-384 |a DE-473 |a DE-355 |a DE-20 |a DE-824 |a DE-29 |a DE-739 |a DE-188 | ||
100 | 1 | |a Maddox, Bryan |e Verfasser |4 aut | |
245 | 1 | 0 | |a The uses of process data in large-scale educational assessments |c Bryan, Maddox |
264 | 1 | |a Paris |b OECD Publishing |c 2023 | |
300 | |a 1 Online-Ressource (23 Seiten) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
490 | 0 | |a OECD Education Working Papers |v no.286 | |
520 | 3 | |a The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in assessments. However, it is now being used for multiple purposes across the assessment cycle. Process data is being deliberately captured and used in large-scale, standardized assessments - moving from viewing it as a "by-product" of digital assessment, to its use "by design" to extend understanding of test-taker performance and engagement. While these techniques offer significant benefits, they also require appropriate validation practices to ensure that their use supports reliable inferences and do not introduce unintended negative consequences | |
650 | 4 | |a Education | |
856 | 4 | 0 | |u https://doi.org/10.1787/5d9009ff-en |x Verlag |z kostenfrei |3 Volltext |
912 | |a ZDB-13-SOC | ||
943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034300932 |
Datensatz im Suchindex
_version_ | 1818896670526537728 |
---|---|
adam_text | |
adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
author | Maddox, Bryan |
author_facet | Maddox, Bryan |
author_role | aut |
author_sort | Maddox, Bryan |
author_variant | b m bm |
building | Verbundindex |
bvnumber | BV049038330 |
collection | ZDB-13-SOC |
ctrlnum | (ZDB-13-SOC)09269117X (OCoLC)1390801970 (DE-599)KEP09269117X |
discipline | Wirtschaftswissenschaften |
discipline_str_mv | Wirtschaftswissenschaften |
doi_str_mv | 10.1787/5d9009ff-en |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a22000001cb4500</leader><controlfield tag="001">BV049038330</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230706s2023 xx o|||| 00||| eng d</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1787/5d9009ff-en</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-13-SOC)09269117X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1390801970</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP09269117X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-521</subfield><subfield code="a">DE-1028</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-1049</subfield><subfield code="a">DE-861</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-384</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-188</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Maddox, Bryan</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The uses of process data in large-scale educational assessments</subfield><subfield code="c">Bryan, Maddox</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Paris</subfield><subfield code="b">OECD Publishing</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (23 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">OECD Education Working Papers</subfield><subfield code="v">no.286</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in assessments. However, it is now being used for multiple purposes across the assessment cycle. Process data is being deliberately captured and used in large-scale, standardized assessments - moving from viewing it as a "by-product" of digital assessment, to its use "by design" to extend understanding of test-taker performance and engagement. While these techniques offer significant benefits, they also require appropriate validation practices to ensure that their use supports reliable inferences and do not introduce unintended negative consequences</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Education</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1787/5d9009ff-en</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-13-SOC</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034300932</subfield></datafield></record></collection> |
id | DE-604.BV049038330 |
illustrated | Not Illustrated |
index_date | 2024-07-03T22:18:26Z |
indexdate | 2024-12-19T19:03:58Z |
institution | BVB |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034300932 |
oclc_num | 1390801970 |
open_access_boolean | 1 |
owner | DE-521 DE-1028 DE-573 DE-92 DE-898 DE-BY-UBR DE-1049 DE-861 DE-91 DE-BY-TUM DE-384 DE-473 DE-BY-UBG DE-355 DE-BY-UBR DE-20 DE-824 DE-29 DE-739 DE-188 |
owner_facet | DE-521 DE-1028 DE-573 DE-92 DE-898 DE-BY-UBR DE-1049 DE-861 DE-91 DE-BY-TUM DE-384 DE-473 DE-BY-UBG DE-355 DE-BY-UBR DE-20 DE-824 DE-29 DE-739 DE-188 |
physical | 1 Online-Ressource (23 Seiten) |
psigel | ZDB-13-SOC |
publishDate | 2023 |
publishDateSearch | 2023 |
publishDateSort | 2023 |
publisher | OECD Publishing |
record_format | marc |
series2 | OECD Education Working Papers |
spelling | Maddox, Bryan Verfasser aut The uses of process data in large-scale educational assessments Bryan, Maddox Paris OECD Publishing 2023 1 Online-Ressource (23 Seiten) txt rdacontent c rdamedia cr rdacarrier OECD Education Working Papers no.286 The digital transition in educational testing has introduced many new opportunities for technology to enhance large-scale assessments. These include the potential to collect and use log data on test-taker response processes routinely, and on a large scale. Process data has long been recognised as a valuable source of validation evidence in assessments. However, it is now being used for multiple purposes across the assessment cycle. Process data is being deliberately captured and used in large-scale, standardized assessments - moving from viewing it as a "by-product" of digital assessment, to its use "by design" to extend understanding of test-taker performance and engagement. While these techniques offer significant benefits, they also require appropriate validation practices to ensure that their use supports reliable inferences and do not introduce unintended negative consequences Education https://doi.org/10.1787/5d9009ff-en Verlag kostenfrei Volltext |
spellingShingle | Maddox, Bryan The uses of process data in large-scale educational assessments Education |
title | The uses of process data in large-scale educational assessments |
title_auth | The uses of process data in large-scale educational assessments |
title_exact_search | The uses of process data in large-scale educational assessments |
title_exact_search_txtP | The uses of process data in large-scale educational assessments |
title_full | The uses of process data in large-scale educational assessments Bryan, Maddox |
title_fullStr | The uses of process data in large-scale educational assessments Bryan, Maddox |
title_full_unstemmed | The uses of process data in large-scale educational assessments Bryan, Maddox |
title_short | The uses of process data in large-scale educational assessments |
title_sort | the uses of process data in large scale educational assessments |
topic | Education |
topic_facet | Education |
url | https://doi.org/10.1787/5d9009ff-en |
work_keys_str_mv | AT maddoxbryan theusesofprocessdatainlargescaleeducationalassessments |