東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

You Only Live Up to the Standards Yo...

Strickman, Scott N.

Linked to FindBook

Google Book

Amazon

博客來

You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting.

Record Type:	Electronic resources : Monograph/item
Title/Author:	You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting./
Author:	Strickman, Scott N.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	179 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
Contained By:	Dissertation Abstracts International78-10A(E).
Subject:	Educational tests & measurements. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10271383
ISBN:	9781369788105

You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting.
Strickman, Scott N.

You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 179 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.

Thesis (Ph.D.)--James Madison University, 2017.

Interpretation of performance in reference to a standard can provide nuanced, finely-tuned information regarding examinee abilities beyond that of just a total score. However, there is a multitude of ways to set performance standards yet little guidance regarding which method operates best and under what circumstances. Traditional methods are the most common approach adopted in practice and heavily involve subject matter experts (SMEs). Two other approaches have been suggested in the literature as alternative ways to set performance standards, although they have yet to be implemented in practice. Data-driven approaches do not involve SMEs but rather rely solely upon statistical techniques to classify examinees into groups. Integrated approaches are a newer standard setting method that combines judgments provided by SMEs with statistical techniques to inform the creation of performance standards. The primary purpose of this dissertation was to describe and illustrate the traditional, data-driven, and integrated approaches used to establish performance standards on tests. A traditional standard setting was conducted using the modified Angoff procedure. Latent class analysis (LCA)---a data-driven classification technique---was performed in which model parameters were first freely estimated to assess the fit of various general LCA models and later constrained to create ordered groups for various ordinal LCA models. The traditional and data-driven standard setting methods were combined to form an "integrated" approach. SMEs' ratings of expected examinee performance (derived from the modified Angoff standard setting) were used as item difficulty constraints in an integrated LCA model, the Angoff LCA. The results were used to compare examinee classifications from all three approaches and model-data fit amongst the statistically-oriented methods. Although classifications were planned for comparison across all three approaches, issues were encountered with the Angoff LCA. Therefore, the comparisons of primary interest were between the modified Angoff and championed LCA model. The results did not offer a clear-cut decision about which approach to champion. Ultimately, the modified Angoff was selected as the most appropriate standard setting approach for the test administered. Important considerations are offered for researchers who wish to use data-driven models to set standards and ideas are proposed for future research.

ISBN: 9781369788105Subjects--Topical Terms:

3168483
Educational tests & measurements.

You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting.
LDR:03412nmm a2200301 4500 001 2124713
005 20171031101047.5
008 180830s2017 ||||||||||||||||| ||eng d
020 $a 9781369788105
035 $a (MiAaPQ)AAI10271383
035 $a AAI10271383
040 $a MiAaPQ $c MiAaPQ
100 1 $a Strickman, Scott N. $3 3286722
245 1 0 $a You Only Live Up to the Standards You Set: An Evaluation of Different Approaches to Standard Setting.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 179 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: A.
500 $a Adviser: Dena A. Pastor.
502 $a Thesis (Ph.D.)--James Madison University, 2017.
520 $a Interpretation of performance in reference to a standard can provide nuanced, finely-tuned information regarding examinee abilities beyond that of just a total score. However, there is a multitude of ways to set performance standards yet little guidance regarding which method operates best and under what circumstances. Traditional methods are the most common approach adopted in practice and heavily involve subject matter experts (SMEs). Two other approaches have been suggested in the literature as alternative ways to set performance standards, although they have yet to be implemented in practice. Data-driven approaches do not involve SMEs but rather rely solely upon statistical techniques to classify examinees into groups. Integrated approaches are a newer standard setting method that combines judgments provided by SMEs with statistical techniques to inform the creation of performance standards. The primary purpose of this dissertation was to describe and illustrate the traditional, data-driven, and integrated approaches used to establish performance standards on tests. A traditional standard setting was conducted using the modified Angoff procedure. Latent class analysis (LCA)---a data-driven classification technique---was performed in which model parameters were first freely estimated to assess the fit of various general LCA models and later constrained to create ordered groups for various ordinal LCA models. The traditional and data-driven standard setting methods were combined to form an "integrated" approach. SMEs' ratings of expected examinee performance (derived from the modified Angoff standard setting) were used as item difficulty constraints in an integrated LCA model, the Angoff LCA. The results were used to compare examinee classifications from all three approaches and model-data fit amongst the statistically-oriented methods. Although classifications were planned for comparison across all three approaches, issues were encountered with the Angoff LCA. Therefore, the comparisons of primary interest were between the modified Angoff and championed LCA model. The results did not offer a clear-cut decision about which approach to champion. Ultimately, the modified Angoff was selected as the most appropriate standard setting approach for the test administered. Important considerations are offered for researchers who wish to use data-driven models to set standards and ideas are proposed for future research.
590 $a School code: 1357.
650 4 $a Educational tests & measurements. $3 3168483
650 4 $a Educational psychology. $3 517650
650 4 $a Quantitative psychology. $3 2144748
690 $a 0288
690 $a 0525
690 $a 0632
710 2 $a James Madison University. $b Graduate Psychology. $3 3286280
773 0 $t Dissertation Abstracts International $g 78-10A(E).
790 $a 1357
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10271383