AI Assessment Question Review

AI Assessment Question Review

Primary Category: Learning Systems & Assessment Governance

Secondary Focus: Responsible AI, Validity, Fairness, and Accessibility in Testing

Artifact Profile

AI Assessment Question Review is a governance artifact for evaluating AI-generated or AI-assisted assessment items before they are used in quizzes, tests, or exams. It ensures that questions align to learning objectives, reflect appropriate cognitive demand, and meet standards for fairness, accessibility, and scoring integrity.

Using your learning objectives, standards, cognitive targets, draft items, and review criteria, the artifact produces a structured evaluation of assessment quality. Rather than accepting AI output at face value, it makes validity, bias, accessibility, and answer integrity explicit and reviewable.

This artifact is built for education leaders, instructional designers, assessment teams, and governance bodies who want to leverage AI efficiency without compromising professional judgment, equity, or defensibility in assessment design.

Three Key Questions This Artifact Helps You Answer

• Do AI-generated questions validly measure the intended learning objectives?

• Are there issues with bias, accessibility, clarity, or cultural relevance that must be addressed?

• Can these items be approved for use without compromising fairness, integrity, or scoring accuracy?

What This Framework Supports

This artifact supports organizations seeking:

• Governed review of AI-generated or AI-assisted assessment items before use

• Validation of alignment to learning objectives, standards, and cognitive demand

• Identification of bias, accessibility barriers, and construct-irrelevant difficulty

• Assurance of scoring integrity, answer key validity, and defensibility of assessments

How It Is Used

The artifact provides a structured assessment review framework that guides education leaders and assessment teams through:

• Evaluating AI-generated items against objectives, standards, and cognitive targets

• Reviewing questions for bias, accessibility, cultural relevance, and clarity

• Verifying distractor quality, rubrics, and scoring logic

• Producing explicit recommendations to approve, revise, or reject items

This enables organizations to leverage AI efficiency in assessment development while maintaining professional judgment, equity, and psychometric rigor.

What This Produces

• Evaluation of alignment to objectives and cognitive demand

• Identification of bias, accessibility, or construct-irrelevant difficulty

• Verification of scoring keys, rubrics, and distractor quality

• Recommendations to approve, revise, or reject AI-generated items

Common Use Cases

• Reviewing AI-generated quiz, test, or exam questions before use

• Scaling item banks while maintaining alignment to objectives and standards

• Auditing assessments for bias, accessibility, and cultural relevance

• Validating answer keys, rubrics, and distractor quality

• Establishing policies for responsible AI use in assessment design

How This Artifact Is Different

Unlike informal review or unchecked automation, this artifact treats AI-assisted assessment as a governed decision domain. It embeds professional standards, equity, accessibility, and psychometric discipline into the review process so that AI enhances efficiency without replacing human judgment.

Related Framework Areas

This artifact is commonly used alongside other SolveBoard frameworks focused on:

• Instructional design, learning objective alignment, and curriculum governance

• Compliance, documentation, and defensible assessment practices

• Responsible AI policy and educational technology governance

• Quality assurance in testing, measurement, and evaluation systems

Related Terms

AI in education, assessment governance, test item review, psychometric quality, bias in assessment, accessibility in testing, learning objective alignment, and responsible AI.

Framework Classification

This artifact is part of the SolveBoard library of structured decision and governance frameworks. It is designed as a repeatable AI assessment governance framework rather than an informal review checklist or automated validation script.

AI Assessment Question Review

Governing the use of AI-generated assessment items to ensure validity, alignment, fairness, accessibility, and professional accountability.

Definition

AI Assessment Question Review establishes how automated or AI-assisted item generation is evaluated before use in quizzes, tests, and exams. It governs alignment to objectives, cognitive demand, bias detection, accessibility, scoring integrity, and data protection to ensure AI supports—but does not replace—professional judgment in assessment design. Within SolveBoard, this framework treats AI as a constrained drafting tool operating within explicit psychometric and ethical guardrails.

When to Use

• When adopting AI tools to draft test or quiz questions

• When scaling item banks or refreshing assessments rapidly

• When concerns arise about bias, validity, or misalignment

• When integrating AI into assessment development workflows

• When establishing policies for AI-assisted assessment design

When Not to Use

• When AI tools are prohibited by policy or regulation

• When assessments are entirely manually authored with no AI involvement

• When evaluation is informal and ungraded

Common Mistakes

• Accepting AI items without objective alignment checks

• Allowing construct-irrelevant difficulty or trick wording

• Failing to review for bias, cultural relevance, or accessibility

• Overlooking answer key accuracy or distractor quality

• Using student data or sensitive content in prompts

Purpose of the AI Assessment Question Review

The purpose of AI Assessment Question Review is to leverage efficiency in item drafting while preserving assessment quality, equity, and defensibility. A disciplined review ensures AI-generated items measure intended constructs, reflect appropriate cognitive levels, and meet accessibility and fairness standards.

How to Apply

• Define acceptable and prohibited uses of AI in assessment design

• Require explicit mapping from each item to objectives and standards

• Evaluate cognitive level, difficulty, and clarity

• Screen for bias, cultural relevance, and accessibility

• Verify scoring keys, rubrics, and distractor plausibility

• Protect student and educator data in prompts and uploads

Example Scenario

A department uses an AI tool to draft multiple-choice items for a unit exam. Using the framework, teachers verify alignment to learning targets, check Bloom’s levels, review for accessibility, and correct a flawed answer key. Only reviewed and approved items are added to the item bank.

Boundaries

AI Assessment Question Review does not replace psychometric validation, legal compliance, or formal test development processes. It defines the instructional and ethical guardrails for responsible AI use within those systems.

What This Artifact Does

Defines review criteria, workflows, and accountability for using AI to draft assessment questions without compromising validity, equity, or professional standards.

You Provide

(You may provide some, all, or none of the items below. Partial inputs are valid.)

• AI tool description and intended assessment use

• Learning objectives, standards, and cognitive level targets

• Draft items (stems, options, keys, rubrics)

• Equity, accessibility, and bias criteria

• Data privacy and security policies

• Written descriptions or pasted text

• Files, PDFs, images, and other uploads (always acceptable)

• Optional context notes (testing policies, accommodation requirements)

Core Question

Do AI-generated items validly and fairly measure intended learning outcomes without introducing bias, inaccessibility, or scoring errors?

Decision Logic

• If alignment is weak → Revise or reject the item

• If cognitive level is off-target → Rewrite to match objectives

• If bias or accessibility issues appear → Modify or remove

• If keys/distractors are flawed → Correct before use

• If quality is high with safeguards → Approve for monitored use

What the Output Means

• Evaluation of alignment, validity, and cognitive demand

• Identification of bias, accessibility, or scoring risks

• Analysis of governance and review processes

• Recommendations for approval, revision, or rejection

Do Not Use When

• AI tools are prohibited by policy or regulation

• Assessments are entirely manual with no AI involvement

• Evaluation is informal and ungraded

You do not need to complete every section below. Provide only the information you have available or wish to provide. The AI will generate output using only the inputs you supply and will not assume or infer missing information.

Section 1 — AI Tool and Intended Assessment Use

What This Input Represents

The AI system being used and how it is intended to support assessment development.

If You Have Materials, You May Provide (List file names here in your input document):

• AI tool descriptions

• Vendor documentation

• Internal AI usage policies

Guiding Questions:

• What AI tool or system is being used to generate assessment items?

• What types of assessments will it support (quizzes, exams, practice tests, item banks, etc.)?

• How is AI used in the workflow (drafting, editing, scaling, refreshing items)?

Section 2 — Learning Objectives, Standards, and Cognitive Targets

What This Input Represents

The instructional goals and performance expectations each item must align to.

If You Have Materials, You May Provide (List file names here in your input document):

• Curriculum standards

• Learning objectives

• Bloom’s taxonomy mappings

• Assessment blueprints

Guiding Questions:

• What learning objectives or standards must items measure?

• What cognitive levels are intended (recall, application, analysis, etc.)?

• Are there content coverage or blueprint constraints that must be followed?

Section 3 — Draft Items and Scoring Logic

What This Input Represents

The actual AI-generated or AI-assisted questions to be reviewed.

If You Have Materials, You May Provide (List file names here in your input document):

• Draft question stems

• Answer choices

• Answer keys

• Rubrics or scoring guides

Guiding Questions:

• What draft items are being reviewed?

• Are answer keys and distractors clearly defined and accurate?

• Do any items rely on ambiguous wording, trick structure, or construct-irrelevant difficulty?

Section 4 — Equity, Accessibility, Bias, and Data Protection

What This Input Represents

The ethical, legal, and professional guardrails that govern assessment quality and use of data.

If You Have Materials, You May Provide (List file names here in your input document):

• Bias review criteria

• Accessibility guidelines (e.g., WCAG)

• Data privacy policies

• Institutional testing policies

Guiding Questions:

• What equity, bias, or cultural relevance standards must be applied?

• What accessibility requirements must items meet?

• What data privacy or security constraints govern prompts, uploads, or student information?

Section 5 — Supporting Context, Files, and References

What This Input Represents

Any additional information that would help the AI interpret psychometric expectations, institutional policies, or review workflows accurately.

You May Include (List file names here in your input document):

• Assessment policies or governance documents

• Item bank samples or historical test forms

• Audit, compliance, or accessibility reviews

• Links to LMS, testing platforms, or analytics tools

• Pasted text or excerpts

Additional Instructions (Optional)

You may add extra instructions to further shape the output, including:

Requesting PDF or other output formats
Limiting page length or response size
Layout preferences (section order, headings, structure, templates)
Specifying tone, style, or format (executive, concise, detailed, formal, etc.)
Output consistency preferences (fixed structure, standardized phrasing, strict formatting)
Prioritization or scoring preferences (how gaps, risks, or actions should be ranked)
Desired mode behavior as outlined in the section below
Any other constraints, rules, or priorities relevant to your use case

If included, the AI will follow these instructions when they do not conflict with the bridge’s execution rules. More specific instructions generally produce more consistent, repeatable, and targeted outputs.

Desired Mode Behavior

Strict Mode

• Maximize determinism and repeatability
• Minimize wording variation, structure changes, and interpretive flexibility
• Do not extend beyond explicit user inputs

Balanced Mode (Default)

• Maintain structure and discipline
• Allow limited analytical judgment where inputs are incomplete
• Do not introduce external assumptions

Exploratory Mode

• Expand hypothesis space and analytical angles
• Surface alternative interpretations and scenario paths
• Still grounded only in user-provided inputs

If no mode is specified, default to Balanced Mode.

What This Enables

Based on your prepared inputs, this artifact will evaluate whether AI-generated assessment items are aligned to objectives, appropriate in cognitive demand, free from bias, accessible to all learners, and supported by accurate scoring logic. It will identify risks and provide recommendations for approval, revision, or rejection.

Canonical Input Rule (For All SolveBoard Artifacts)

Documents are optional. Sections may be partially completed or left blank. Structured answers to any subset of guiding questions constitute valid input. The AI will evaluate only provided information and will not infer missing content.

AI Execution Instructions

You are operating in Bridge Execution Mode. Follow these rules exactly. Do not reinterpret, summarize, optimize, or override them. Do not introduce external knowledge, assumptions, or inferred content. Evaluate only user-provided inputs. If required information is missing or ambiguous, flag it rather than guessing. Output must follow the defined Output section exactly.

Users may provide some, all, or none of the input sections. Process only what is explicitly provided. Treat empty sections as intentionally omitted.

Purpose

Generate a structured governance review of AI-generated assessment items to ensure validity, fairness, accessibility, and scoring integrity.

What This Bridge Answers

How can AI-generated assessment questions be reviewed and governed so they improve efficiency while preserving validity, equity, accessibility, and professional accountability?

Inputs (All Optional)

• AI tool description and workflows

• Objectives, standards, and cognitive targets

• Draft items (stems, options, keys, rubrics)

• Equity, accessibility, and bias criteria

• Data privacy and security policies

• Any relevant institutional guidelines

• Files, PDFs, spreadsheets, images, links, or other uploaded material

• Context notes

Note: Output Quality and specificity scale with input completeness. The user has been informed of this via the input sheet.

Processing Rules

A valid AI Assessment Question Review output must satisfy all of the following:

• Each item is mapped to objectives and cognitive level

• Validity, clarity, and construct relevance are evaluated

• Bias, accessibility, and cultural relevance are assessed

• Keys, rubrics, and distractors are verified

• Recommendations balance efficiency with assessment integrity

When inputs are sparse:

• Produce the most complete output possible with available data

• Explicitly flag what's missing and how additional inputs would enhance the analysis

• Do not infer or assume missing information

Execution Steps

• Review AI tool capabilities and intended use

• Check alignment to objectives and standards

• Evaluate cognitive demand, clarity, and difficulty

• Assess bias, accessibility, and data handling

• Generate findings and governance recommendations

Output

• Evaluation of alignment, validity, and cognitive demand

• Identification of bias, accessibility, or scoring risks

• Analysis of governance and review processes

• Recommendations for approval, revision, or rejection

Failure Conditions / Misuse

• Using AI items without human review

• Allowing misalignment with objectives or standards

• Ignoring bias, accessibility, or data privacy risks

• Introducing external assumptions not provided by the user

Mode Behavior (From Input Sheet)

Strict Mode

• Maximize determinism and repeatability
• Minimize wording variation, structure changes, and interpretive flexibility
• Do not extend beyond explicit user inputs

Balanced Mode (Default)

• Maintain structure and discipline
• Allow limited analytical judgment where inputs are incomplete
• Do not introduce external assumptions

Exploratory Mode

• Expand hypothesis space and analytical angles
• Surface alternative interpretations and scenario paths
• Still grounded only in user-provided inputs

If no mode is specified, default to Balanced Mode.

Additional Instruction Governance

User-provided additional instructions must be followed exactly unless they conflict with core Bridge Execution Rules. If a conflict exists, Bridge Execution Rules take priority.

Additional instructions may control format, tone, structure, length, or ordering, but must not introduce inferred content, external knowledge, or speculative assumptions.

If instructions are ambiguous, flag ambiguity rather than guessing.

Additional Instructions Execution Rule

If the user provides instructions in the Additional Instructions field, they are binding execution constraints.

Failure to follow them constitutes a Bridge Execution Failure.

Reminder to AI: If a format is requested (e.g., PDF, DOCX), the final output MUST be delivered in that format.

Artifact Instructions

These instructions explain what information the AI Assessment Question Review artifact requires and how to prepare your inputs.

How to Prepare Your Input Document (Required Format)

Create a new Word (or similar) document.
Copy all text from the Input Sheet tab into the document.
Save it — this is now your Input Document.
Answer the guiding questions directly in the Input Document and reference any supporting files there.
Save the completed Input Document (Word, PDF, etc.).
Copy all text from the Bridge AI Prompt tab and paste it into the prompt field.
Attach the completed Input Document and any referenced files when submitting the prompt.

No Supporting Files? No Problem.

You can proceed without uploading any supporting documents, spreadsheets, dashboards, reports, or other attachments.

The Input Document is still required, but it may contain only plain-text answers to the guiding questions.

Written responses alone are sufficient for the AI to generate output.

Supporting files, links, and pasted materials are always optional.

Missing Inputs Are OK

You do not need to complete every section.
You do not need supporting files.

The AI will still run. It will:

Use only the inputs you provide
Skip or flag missing sections
Never fail due to incomplete information

Output quality scales with input depth — but execution never breaks.

Submitting Files

If you upload files, list each file name under the relevant “If You Have Materials” section in your Input Document. This ensures each file is clearly tied to its intended use.

What to Expect From This AI Bridge

This bridge generates a structured, high-value starting point, not a guaranteed final deliverable. Output quality improves as inputs become clearer, deeper, and more complete.

This artifact supports iteration. Users are encouraged to refine inputs, test variations, and rerun the bridge to improve results.

The AI organizes complexity and accelerates insight — but final judgment and decisions remain with the user.

In Short

Stronger inputs → stronger outputs
Iteration improves results
Cross-artifact testing can reveal new perspectives
This artifact enables progress, not perfection