| # of APCS Programs coded | # of APCS Programs with no DEIJ | Model Type | Description | Subjects | # of Subjects |
|---|---|---|---|---|---|
| 6 | 0 | 2-way random effects model | Raters randomly drawn from population, all raters code all subjects | DEIJ variables per institution | 117 |
Model Equation \[ Y_{ij} \sim \mu + s_{i} + r_{j} + (sr)_{ij} + \epsilon_{ij} \\\text{ } \\where\text{ } \mu\text{ is the average rating, } \\s_{i}\text{ is subject } i \text{'s effect, } \\r_{j}\text{ is rater } j \text{'s effect, } \\(sr)_{ij}\text{ is the subject-rater interaction effect associated with subject }i \text{ and rater }j\text{, and } \\ \text{ takes into the account that the effect of bias may not be the same for all subjects,} \\ \epsilon_{ij}\text{ is the error effect} \] Â
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| University | Inter-Rater Reliability | Intra-Rater Reliability | Total # of Coders |
|---|---|---|---|
| Duke University | 0.6103062 | 0.6103062 | 9 |
| University of Arizona | 0.7075858 | 0.7113262 | 9 |
| University of Denver | 0.4455760 | 0.4504906 | 9 |
| University of Kentucky | 0.6662142 | 0.6732197 | 8 |
| University of Massachusetts- Amherst | 0.5848952 | 0.5984738 | 8 |
| University of Virginia | 0.7557958 | 0.7561288 | 9 |
| # of APCS Programs coded | # of APCS Programs with no DEIJ | Model Type | Description | Subjects | # of Subjects |
|---|---|---|---|---|---|
| 6 | 0 | 2-way random effects model | Raters randomly drawn from population, all raters code all subjects | DEIJ variables combined by institution (117 variables x 6 institutions) | 702 |
Model Equation \[ Y_{ij} \sim \mu + s_{i} + r_{j} + (sr)_{ij} + \epsilon_{ij} \\\text{ } \\where\text{ } \mu\text{ is the average rating, } \\s_{i}\text{ is subject } i \text{'s effect, } \\r_{j}\text{ is rater } j \text{'s effect, } \\(sr)_{ij}\text{ is the subject-rater interaction effect associated with subject }i \text{ and rater }j\text{, and } \\ \text{ takes into the account that the effect of bias may not be the same for all subjects,} \\ \epsilon_{ij}\text{ is the error effect} \]
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| Inter-Rater Reliability | Intra-Rater Reliability | Total # of Coders |
|---|---|---|
| 0.669455 | 0.6756377 | 9 |
| # of APCS Programs coded | # of APCS Programs with no DEIJ | Model Type | Description | Subjects | # of Subjects |
|---|---|---|---|---|---|
| 24 | 5 | 2-way random effects model | Raters randomly drawn from population, all raters code all subjects | DEIJ variables per institution | 117 |
Model Equation \[ Y_{ij} \sim \mu + s_{i} + r_{j} + (sr)_{ij} + \epsilon_{ij} \\\text{ } \\where\text{ } \mu\text{ is the average rating, } \\s_{i}\text{ is subject } i \text{'s effect, } \\r_{j}\text{ is rater } j \text{'s effect, } \\(sr)_{ij}\text{ is the subject-rater interaction effect associated with subject }i \text{ and rater }j\text{, and } \\ \text{ takes into the account that the effect of bias may not be the same for all subjects,} \\ \epsilon_{ij}\text{ is the error effect} \] Â
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| University | Inter-Rater Reliability | Intra-Rater Reliability | Total # of Coders |
|---|---|---|---|
| Boston University | 0.9101183 | 0.9101183 | 3 |
| Florida State University | 0.9053165 | 0.9053165 | 3 |
| Michigan State University | 0.8434732 | 0.8470519 | 3 |
| Northwestern University | 0.8994698 | 0.8996737 | 3 |
| Ohio State University | 0.7998931 | 0.8024199 | 3 |
| Pennsylvania State University | 0.7392276 | 0.7392276 | 3 |
| Temple University | 0.7020730 | 0.7108420 | 3 |
| University of Delaware | 0.9290791 | 0.9290791 | 3 |
| University of Hawaii | 0.8505783 | 0.8513343 | 3 |
| University of Illinois- Urbana Champaign | 0.7766073 | 0.7768048 | 3 |
| University of Kansas (adult) | 0.9610869 | 0.9619255 | 3 |
| University of Maryland | 0.7684887 | 0.7705954 | 3 |
| University of Michigan | 1.0000000 | 1.0000000 | 3 |
| University of Pittsburgh | 0.9792746 | 0.9792746 | 3 |
| University of Rochester | 0.8303459 | 0.8303459 | 3 |
| University of Southern California | 0.8465284 | 0.8529848 | 3 |
| University of Utah | 0.9827405 | 0.9827405 | 3 |
| University of Wisconsin- Milwaukee | 0.9385244 | 0.9391680 | 3 |
| Virginia Tech | 0.7089391 | 0.7089391 | 3 |
| # of APCS Programs coded | # of APCS Programs with no DEIJ | Model Type | Description | Subjects | # of Subjects |
|---|---|---|---|---|---|
| 24 | 5 | 1-way random effects model | Not all subjects are rated by the same roster of raters | DEIJ variables combined by institution (117 variables x 24 institutions) | 2808 |
Model Equation \[ Y_{ij} \sim \mu + s_{i} + r_{j} + (sr)_{ij} + \epsilon_{ij} \\\text{ } \\where\text{ } \mu\text{ is the average rating, } \\s_{i}\text{ is subject } i \text{'s effect, } \\ \epsilon_{ij}\text{ is the error effect} \]
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| Inter-Rater Reliability | Error Variance | Total # of Coders |
|---|---|---|
| 0.8667913 | 0.0994777 | 9 |
| University | Inter-Rater Reliability | Intra-Rater Reliability | Total # of Coders |
|---|---|---|---|
| Stony | 0.9198967 | 0.9207535 | 3 |
| MN | 0.9651233 | 0.9652435 | 3 |
| Miami | 0.7335764 | 0.7353263 | 3 |
| UIC | 0.2832246 | 0.2832246 | 3 |
| WUSTL | 0.8352501 | 0.8369821 | 3 |
| OklahomaS | 0.8404088 | 0.8409142 | 3 |
| Oregon | 0.7986111 | 0.7986111 | 3 |
| MarylandIntern | 0.7727835 | 0.7788660 | 3 |
| SDSU | 0.8936447 | 0.8936447 | 3 |
| UT | 0.6439077 | 0.6495750 | 3 |
| UCLA | 0.7498350 | 0.7510233 | 3 |
| Indiana | 0.8998206 | 0.9001528 | 3 |
| UW | 0.7409095 | 0.7420709 | 3 |
| Georgia | 0.8614480 | 0.8654906 | 3 |
| Nevada | 0.7553223 | 0.7580202 | 3 |
| SemelIntern | 0.8833500 | 0.8833500 | 3 |
| MUSCIntern | 0.7217781 | 0.7272146 | 3 |
| GMU | 0.8424809 | 0.8424809 | 3 |
| WPIntern | 0.5901932 | 0.5959394 | 3 |
| FIU | 0.9900561 | 0.9904613 | 3 |
| Inter-Rater Reliability | Error Variance | Total # of Coders |
|---|---|---|
| 0.7771125 | 0.1968186 | 9 |
Rationales supported by intrinsic values or principles (Starck, Sinclair, & Shelton, 2021)