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    audit learning design integrity

    by Carl Badenhorst

    1

    Audits structured learning experiences for internal consistency and relational integrity across outcomes and assessments.

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    See it in action

    You say

    Audit the alignment between these three learning outcomes and the final project brief. Check if the project actually elicits the performance levels described in the outcomes.

    Your agent does

    Integrity Summary

    The final project partially aligns with Outcome 1 but fails to elicit the 'evaluation' level required by Outcome 3.

    Priority Finding

    • Component: Outcome 3 vs. Project Task 2
    • Severity: Critical
    • Finding: The outcome requires evaluating competing theories, but the project only asks for a summary.
    • Recommendation: Revise Task 2 to require a comparative critique.

    What you get

    Validate that assessments accurately measure stated learning outcomes.Identify instructional gaps where learners lack preparation for tasks.Trace the ripple effect of curriculum revisions across all course artifacts.Detect orphan outcomes or activities that lack clear pedagogical purpose.

    About this skill

    The problem

    Learning designs often suffer from hidden inconsistencies where assessments fail to measure stated outcomes, or activities don't actually prepare students for the final exam. These "leaky" curricula waste learner time and undermine institutional credibility through invalid assessment data.

    What it does

    • Maps relationships between learning outcomes, content, activities, assessments, and rubrics to find gaps.
    • Identifies orphan outcomes that aren't assessed and assessment tasks that aren't supported by instructional content.
    • Calculates the impact of revising a single artifact on the rest of the curriculum ecosystem.
    • Categorizes integrity failures by severity and confidence levels based on supplied evidence.
    • Recommends the smallest possible intervention to fix misalignments without redesigning unaffected materials.

    Why this beats prompting it yourself

    Generic prompts often focus on surface-level "action verb" matching or mechanical Bloom's Taxonomy application. This skill treats learning design as a relational database, tracing performance evidence and prerequisite logic to find substantive defects that basic keyword audits miss.

    Use cases

    • QAing a new course module before it goes live to ensure assessment validity.
    • Auditing an existing curriculum map to find redundant activities or unassessed outcomes.
    • Evaluating the downstream impact of changing a high-stakes assessment task.
    • Reviewing rubric criteria against assessment instructions to ensure fair grading.

    Known limitations

    Requires at least two connected components to function. It cannot provide psychometric or accreditation validity claims beyond the provided evidence.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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