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Taming the Multipliers: Standards C1.03 and C1.02

Taming the Multipliers: Standards C1.03 and C1.02

February 12, 20253 min read

We’re reviewing the ten most cited ARC-PA Standards as of September 2024. Last week, I promised you a deep dive into four often-cited Standards that usually  appear together—my rather unaffectionate name for these is “multipliers.” We’re talking about Standards C1.03, C1.02, A2.09, and A1.02. We have a lot to cover, so let’s begin. I’ll present these in the order they appear on the “Top Ten” List, starting with today’s topic, the C Standards.

C1.03 Language

I feel it’s worth repeating that 106 out of 163 programs were cited in this Standard. That’s two-thirds, an alarming percentage, indicating the Commission’s serious consideration of its exacting requirements regarding Self-Study Reports. 

Standard C1.03 states, “The program must prepare a self-study report as part of the application for accreditation that accurately and succinctly documents the process, application, and results of ongoing program self-assessment. The report must follow the guidelines provided by the ARC-PA.” 

The language we see in the citations looks like this. Note the frequent use of the word “consistent.” 

“Within the submitted self-study report (SSR), the program did not consistently provide documentation of critical data analysis and the ability to link analysis to data-driven conclusions....”

“While the program defined its benchmarks and its process…the discussion with the faculty and review of minutes onsite demonstrated inconsistent inclusion of critical analysis with the SSR.” 

C1.03: Caveats for success

  • Defer to the compliance manual in terms of the level of granularity that they’re looking for in this document. 

  • Even if your SSR is in great shape, the committee will see it as a missing link if your onsite minutes do not corroborate what your report says.

  • Area Needing Improvement / Strength / Modifications MUST result from benchmark-driven triangulation of data points (at least three). This needs to be redundant in the narrative, or it will be misinterpreted. 

  • Critical analysis must be crystal clear!

  • Do not present areas needing improvement that include only one data source or one year of data.

  • Do not define areas needing improvement and strengths without explicit language about what drives the conclusion.

  • You must include conclusion/summary statements in the analysis narratives that mirror the language used in areas needing improvement / strengths / modifications.

  • Do not document data-driven modifications in the analysis narrative but fail to include them in the “modification” section at the bottom of the template.

  • Benchmarks must define program expectations for each specific data element.

  • Benchmarks must have defined strengths and areas in need of improvement that are measurable.

  • Triangulate data from other Appendix 14 components whenever possible.

  • For further information, see my blogs published November 1 and 7, 2023.

C1.02 Language

C1.02 is about benchmarks, critical analysis documentation, and those components in the SSR. You’ll note that these observations reference a lack of critical analysis.

Observation:  “At the time of the site visit, the program stated that areas needing improvement were identified as two years below the program’s benchmark. The program did not consistently conduct critical data analysis that met the program’s benchmarks.”

Observation: “The program did not provide evidence that its identified strengths were the result of performing a critical analysis of the data in its ongoing self-assessment process. In the submitted self-study report and at the time of the site visit, the program did not identify any program strengths.”

C1.02 Caveats for Success:

  • Areas Needing Improvement / Strengths / Modifications MUST result from benchmark-driven triangulation of data points (at least three). 

  • Programs must have explicit benchmarks for all data points, rationales for the benchmarks, and strength benchmarks. In addition, the data plan must be clearly triangulated.

  • Cross-reference data, describe each data point that directly triangulates (all must be commensurate), and summarize the critical analysis clearly. 

  • Ensure the language is aligned in the charts at the bottom of the document. 

  • For more information, see my blogs published November 14 and 28 and December 5, 2023.

In our next blog…

Now that we’ve examined the C Standard multipliers, we need to examine the two A Standards that seem inextricably linked. So, next week, we’ll examine Standards A1.02 and A2.09 because when these appear, today’s C Standards are likely to follow.


C1.03Self-Study ReportCritical AnalysisBenchmarksData Triangulation
blog author image

Scott Massey

With over three decades of experience in PA education, Dr. Scott Massey is a recognized authority in the field. He has demonstrated his expertise as a program director at esteemed institutions such as Central Michigan University and as the research chair in the Department of PA Studies at the University of Pittsburgh. Dr. Massey's influence spans beyond practical experience, as he has significantly contributed to accreditation, assessment, and student success. His innovative methodologies have guided numerous PA programs to ARC-PA accreditation and improved program outcomes. His predictive statistical risk modeling has enabled schools to anticipate student results. Dr Massey has published articles related to predictive modeling and educational outcomes. Doctor Massey also has conducted longitudinal research in stress among graduate Health Science students. His commitment to advancing the PA field is evident through participation in PAEA committees, councils, and educational initiatives.

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Taming the Multipliers: Standards C1.03 and C1.02

Taming the Multipliers: Standards C1.03 and C1.02

February 12, 20253 min read

We’re reviewing the ten most cited ARC-PA Standards as of September 2024. Last week, I promised you a deep dive into four often-cited Standards that usually  appear together—my rather unaffectionate name for these is “multipliers.” We’re talking about Standards C1.03, C1.02, A2.09, and A1.02. We have a lot to cover, so let’s begin. I’ll present these in the order they appear on the “Top Ten” List, starting with today’s topic, the C Standards.

C1.03 Language

I feel it’s worth repeating that 106 out of 163 programs were cited in this Standard. That’s two-thirds, an alarming percentage, indicating the Commission’s serious consideration of its exacting requirements regarding Self-Study Reports. 

Standard C1.03 states, “The program must prepare a self-study report as part of the application for accreditation that accurately and succinctly documents the process, application, and results of ongoing program self-assessment. The report must follow the guidelines provided by the ARC-PA.” 

The language we see in the citations looks like this. Note the frequent use of the word “consistent.” 

“Within the submitted self-study report (SSR), the program did not consistently provide documentation of critical data analysis and the ability to link analysis to data-driven conclusions....”

“While the program defined its benchmarks and its process…the discussion with the faculty and review of minutes onsite demonstrated inconsistent inclusion of critical analysis with the SSR.” 

C1.03: Caveats for success

  • Defer to the compliance manual in terms of the level of granularity that they’re looking for in this document. 

  • Even if your SSR is in great shape, the committee will see it as a missing link if your onsite minutes do not corroborate what your report says.

  • Area Needing Improvement / Strength / Modifications MUST result from benchmark-driven triangulation of data points (at least three). This needs to be redundant in the narrative, or it will be misinterpreted. 

  • Critical analysis must be crystal clear!

  • Do not present areas needing improvement that include only one data source or one year of data.

  • Do not define areas needing improvement and strengths without explicit language about what drives the conclusion.

  • You must include conclusion/summary statements in the analysis narratives that mirror the language used in areas needing improvement / strengths / modifications.

  • Do not document data-driven modifications in the analysis narrative but fail to include them in the “modification” section at the bottom of the template.

  • Benchmarks must define program expectations for each specific data element.

  • Benchmarks must have defined strengths and areas in need of improvement that are measurable.

  • Triangulate data from other Appendix 14 components whenever possible.

  • For further information, see my blogs published November 1 and 7, 2023.

C1.02 Language

C1.02 is about benchmarks, critical analysis documentation, and those components in the SSR. You’ll note that these observations reference a lack of critical analysis.

Observation:  “At the time of the site visit, the program stated that areas needing improvement were identified as two years below the program’s benchmark. The program did not consistently conduct critical data analysis that met the program’s benchmarks.”

Observation: “The program did not provide evidence that its identified strengths were the result of performing a critical analysis of the data in its ongoing self-assessment process. In the submitted self-study report and at the time of the site visit, the program did not identify any program strengths.”

C1.02 Caveats for Success:

  • Areas Needing Improvement / Strengths / Modifications MUST result from benchmark-driven triangulation of data points (at least three). 

  • Programs must have explicit benchmarks for all data points, rationales for the benchmarks, and strength benchmarks. In addition, the data plan must be clearly triangulated.

  • Cross-reference data, describe each data point that directly triangulates (all must be commensurate), and summarize the critical analysis clearly. 

  • Ensure the language is aligned in the charts at the bottom of the document. 

  • For more information, see my blogs published November 14 and 28 and December 5, 2023.

In our next blog…

Now that we’ve examined the C Standard multipliers, we need to examine the two A Standards that seem inextricably linked. So, next week, we’ll examine Standards A1.02 and A2.09 because when these appear, today’s C Standards are likely to follow.


C1.03Self-Study ReportCritical AnalysisBenchmarksData Triangulation
blog author image

Scott Massey

With over three decades of experience in PA education, Dr. Scott Massey is a recognized authority in the field. He has demonstrated his expertise as a program director at esteemed institutions such as Central Michigan University and as the research chair in the Department of PA Studies at the University of Pittsburgh. Dr. Massey's influence spans beyond practical experience, as he has significantly contributed to accreditation, assessment, and student success. His innovative methodologies have guided numerous PA programs to ARC-PA accreditation and improved program outcomes. His predictive statistical risk modeling has enabled schools to anticipate student results. Dr Massey has published articles related to predictive modeling and educational outcomes. Doctor Massey also has conducted longitudinal research in stress among graduate Health Science students. His commitment to advancing the PA field is evident through participation in PAEA committees, councils, and educational initiatives.

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