Can automated item generation be used to develop high quality MCQs that assess application of knowledge?

Abstract The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Pugh, Debra [verfasserIn] De Champlain, André [verfasserIn] Gierl, Mark [verfasserIn] Lai, Hollis [verfasserIn] Touchie, Claire [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Automated item generation Multiple-choice questions

Übergeordnetes Werk:	Enthalten in: Research and practice in technology enhanced learning - London : Springer Nature, 2006, 15(2020), 1 vom: 05. Juni
Übergeordnetes Werk:	volume:15 ; year:2020 ; number:1 ; day:05 ; month:06

Links:	Volltext

DOI / URN:	10.1186/s41039-020-00134-8

Katalog-ID:	SPR039947106

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spelling	10.1186/s41039-020-00134-8 doi (DE-627)SPR039947106 (SPR)s41039-020-00134-8-e DE-627 ger DE-627 rakwb eng 370 ASE 54.80 bkl 81.68 bkl Pugh, Debra verfasserin aut Can automated item generation be used to develop high quality MCQs that assess application of knowledge? 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants rated a total of 102 MCQs using six quality metrics and made a judgment regarding whether or not each item tested recall or application of knowledge. A Wilcoxon two-sample test evaluated differences in each of the six quality metrics rating scales as well as an overall cognitive domain judgment. No significant differences were found in terms of item quality or cognitive domain assessed when comparing the two item development methods. The vast majority of items (> 90%) developed using both methods were deemed to be assessing higher-order skills. When compared to traditionally developed items, MCQs developed using AIG demonstrated comparable quality. Both modalities can produce items that assess higher-order cognitive skills. Automated item generation (dpeaa)DE-He213 Multiple-choice questions (dpeaa)DE-He213 De Champlain, André verfasserin aut Gierl, Mark verfasserin aut Lai, Hollis verfasserin aut Touchie, Claire verfasserin aut Enthalten in Research and practice in technology enhanced learning London : Springer Nature, 2006 15(2020), 1 vom: 05. Juni (DE-627)512880409 (DE-600)2237676-8 1793-7078 nnns volume:15 year:2020 number:1 day:05 month:06 https://dx.doi.org/10.1186/s41039-020-00134-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 54.80 ASE 81.68 ASE AR 15 2020 1 05 06
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source	Enthalten in Research and practice in technology enhanced learning 15(2020), 1 vom: 05. Juni volume:15 year:2020 number:1 day:05 month:06
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title	Can automated item generation be used to develop high quality MCQs that assess application of knowledge?
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title_full	Can automated item generation be used to develop high quality MCQs that assess application of knowledge?
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title_sort	can automated item generation be used to develop high quality mcqs that assess application of knowledge?
title_auth	Can automated item generation be used to develop high quality MCQs that assess application of knowledge?
abstract	Abstract The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants rated a total of 102 MCQs using six quality metrics and made a judgment regarding whether or not each item tested recall or application of knowledge. A Wilcoxon two-sample test evaluated differences in each of the six quality metrics rating scales as well as an overall cognitive domain judgment. No significant differences were found in terms of item quality or cognitive domain assessed when comparing the two item development methods. The vast majority of items (> 90%) developed using both methods were deemed to be assessing higher-order skills. When compared to traditionally developed items, MCQs developed using AIG demonstrated comparable quality. Both modalities can produce items that assess higher-order cognitive skills.
abstractGer	Abstract The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants rated a total of 102 MCQs using six quality metrics and made a judgment regarding whether or not each item tested recall or application of knowledge. A Wilcoxon two-sample test evaluated differences in each of the six quality metrics rating scales as well as an overall cognitive domain judgment. No significant differences were found in terms of item quality or cognitive domain assessed when comparing the two item development methods. The vast majority of items (> 90%) developed using both methods were deemed to be assessing higher-order skills. When compared to traditionally developed items, MCQs developed using AIG demonstrated comparable quality. Both modalities can produce items that assess higher-order cognitive skills.
abstract_unstemmed	Abstract The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants rated a total of 102 MCQs using six quality metrics and made a judgment regarding whether or not each item tested recall or application of knowledge. A Wilcoxon two-sample test evaluated differences in each of the six quality metrics rating scales as well as an overall cognitive domain judgment. No significant differences were found in terms of item quality or cognitive domain assessed when comparing the two item development methods. The vast majority of items (> 90%) developed using both methods were deemed to be assessing higher-order skills. When compared to traditionally developed items, MCQs developed using AIG demonstrated comparable quality. Both modalities can produce items that assess higher-order cognitive skills.
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title_short	Can automated item generation be used to develop high quality MCQs that assess application of knowledge?
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The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants rated a total of 102 MCQs using six quality metrics and made a judgment regarding whether or not each item tested recall or application of knowledge. A Wilcoxon two-sample test evaluated differences in each of the six quality metrics rating scales as well as an overall cognitive domain judgment. No significant differences were found in terms of item quality or cognitive domain assessed when comparing the two item development methods. The vast majority of items (> 90%) developed using both methods were deemed to be assessing higher-order skills. When compared to traditionally developed items, MCQs developed using AIG demonstrated comparable quality. 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Can automated item generation be used to develop high quality MCQs that assess application of knowledge?

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