v1. Audit and Update your Curriculum - by Z.ai 

Question

Does your program provide the qualities students need to develop to become employable in their field? What will [your program] graduates DO on a daily basis? What Knowledge, Skills, and Abilities are required in their profession?

Project description​

Structure programs to ensure graduates acquire the Knowledge and develop the Skills and Abilities required in their profession. Aligning curriculum with learning outcomes and assessment.

Demo (Beta version)

Use the AI Curriculum Modernizer, a guided workspace that helps academics audit, align, and redesign degree programs for the AI era using structured PTO prompts across three steps: Audit → Skills & Gaps → Redesign.
*Based on Dr Ro's related preprint publication. ​

Prototype Images

Modernize your program

This is what the UI can look like

DESCRIPTION

AI-Ready Curriculum Studio (PTO Playbook)

​Overview
The AI-Ready Curriculum Studio is a comprehensive guided workspace designed to help academic institutions modernize their degree programs for the AI era. It provides a structured approach through three main phases: Audit, Skills & Gaps Mapping, and Redesign.
Key Features
Structured PTO FrameworkThe application uses a consistent PTO (Persona-Task-Output) prompting methodology that ensures reliable, actionable results across all analyses. Each prompt assigns a specific expert persona to perform a defined task, producing standardized outputs.
Three-Step Process

1. Program Audit: Analyzes existing curriculum elements including mission alignment, course mapping, CLO gaps, student feedback, accreditation requirements, and ethical considerations.
2. Skills & Gap Mapping: Identifies labor market trends, maps coverage gaps, and optionally analyzes job posting frequencies.
3. Redesign & Assessment: Generates new CLOs, creates assessment plans, develops activities and labs, and suggests authentic assessments.

User Experience

• Wizard-style interface with progress tracking
• Inline editing capabilities with "Re-run with edits" functionality
• Comprehensive export options (DOCX, CSV, PDF, ZIP packages)
• Version history for all AI-generated content
• Verification toggles for data-driven sections

Target Users

• Program chairs and curriculum committees
• Course coordinators and instructional designers
• Accreditation and QA leads
• Faculty revising or creating courses

Implementation HighlightsThe application emphasizes an evidence-first approach, only analyzing user-provided data without fabrication. Ethics-by-design principles are embedded throughout, with bias checks, licensing considerations, and safety reminders. Local storage with JSON export/import ensures data portability and privacy.
For academic institutions seeking to modernize their curriculum in response to AI advancements, this tool provides a systematic, efficient framework that can identify actionable changes in under 10 minutes while maintaining academic rigor and accreditation compliance.
he code and produce the app

The prompt i used

Title AI-Ready Curriculum Studio (PTO Playbook)
One-line purpose
A guided workspace that helps academics audit, align, and redesign degree programs for the AI era using structured PTO prompts across three steps: Audit → Skills & Gaps → Redesign.
Primary users - Program chairs and curriculum committees - Course coordinators and instructional designers - Accreditation and QA leads - Faculty revising or creating courses
​Foundational principles - PTO prompting (Persona–Task–Output) for consistent, actionable results - Evidence-first: users provide mission, CLOs, accreditation criteria, and market evidence; the app structures and analyzes—never fabricates—data - Ethics-by-design: bias, licensing, and safety checks embedded in every output - Export everything for committee use (DOCX, CSV, PDF) High-level flow (wizard with progress tracker) - Step 1: Program Audit (PTO) - Step 2: Skills & Gap Mapping (PTO) - Step 3: Redesign & Assessment (PTO) - Review & Export (memos, appendices, datasets, workshop pack) Data inputs (user-provided) - Program mission & graduate attributes (text) - Course list (CSV: CourseCode, Title, Description, Level) - CLOs (CSV: CourseCode, CLO_Text, BloomLevel if available) - Accreditation framework & version (dropdown+free text) - Student feedback (optional, anonymized text) - Labor-market evidence (optional CSV or pasted summary) - Discipline tags and region (context for skills/labor) App structure (pages & components) 1) Onboarding - Fields: Program name, Discipline(s), Region, Accreditation framework/version - Actions: Start new project, Load saved project - Help: One-screen overview of the three steps and PTO scaffold 2) Step 1 — Program Audit (PTO) a) Mission alignment (Prompt A) - Inputs: Mission statement, Graduate attributes - PTO Prompt - Persona: Institutional effectiveness analyst - Task: Analyze alignment to AI-era competencies (technical, ethical, data, critical thinking, collaboration) - Output: Bulleted strengths/gaps + 3–5 priority actions - Deliverables: Editable bullets; “Add to Strategic Memo”; Export DOCX b) Course map (Prompt B) - Inputs: Course list CSV (or paste) - PTO Prompt - Persona: Curriculum cartographer - Task: Organize Core/Electives; mark high-impact AI integration points by level and prerequisites - Output: Two-column map with 5–10 integration recommendations - Deliverables: Editable table; Export DOCX/CSV c) CLO gap scan (Prompt C) - Inputs: CLOs CSV - PTO Prompt - Persona: Learning outcomes specialist - Task: Tag Bloom levels; flag AI relevance; identify redundancies and omissions - Output: CSV with columns: CourseCode, CLO, Bloom, AI-Relevance(Yes/No), Notes - Deliverables: Editable grid; Export CSV d) Student experience themes (Prompt D, optional) - Inputs: Anonymized student comments - PTO Prompt - Persona: Educational researcher - Task: Summarize themes on relevance, AI readiness, ethics concerns - Output: 100-word neutral summary (no personal data) - Deliverables: Add as “Voice of Student” to memo e) Accreditation alignment (Prompt E) - Inputs: Framework/version + key criteria text - PTO Prompt - Persona: Accreditation strategist - Task: Compare program elements to standards; list gaps and fixes - Output: Checklist + 5 actionable fixes with ownership and timeline - Deliverables: Accreditation Appendix (DOCX) f) Ethics & bias safeguards (Prompt F) - Inputs: Assessments, datasets, tools used - PTO Prompt - Persona: Responsible AI advisor - Task: Identify risks (bias, opacity, unsafe use, licensing); propose mitigation with sources - Output: Table: Risk, Scenario, Source, Mitigation, Feasibility - Deliverables: Ethics Pack (DOCX/CSV) 3) Step 2 — Skills & Gap Mapping (PTO) a) Labor-market scan (Prompt G) - Inputs: Skills CSV (KSA, Frequency, %Growth, Source, Date) or paste summary; discipline/region filters - PTO Prompt - Persona: Labor-market analyst - Task: Identify top 15 emerging KSAs with % growth since baseline; brief descriptions referencing supplied sources (e.g., WEF Future of Jobs) - Output: CSV: KSA, %Growth, Description, Source - Deliverables: Editable CSV; “Mark citations checked” toggle b) Coverage gap map (Prompt H) - Inputs: KSAs (from G), Course map and CLO grid (from Step 1) - PTO Prompt - Persona: Curriculum alignment specialist - Task: Compare KSAs to program coverage; label Missing/Partial/Full; note suggested course homes - Output: Table: KSA, Coverage, Notes, Suggested Course(s) - Deliverables: Gap Map (CSV) + Heatmap view c) Optional job-bank frequency (Prompt I) - Inputs: Filters (sector, region, keywords) - PTO Prompt - Persona: Job-market curator - Task: Frequency table of AI-related skills in filtered postings - Output: Table: Skill, Frequency, Sample Roles, Source/Date - Deliverables: Evidence panel attachment 4) Step 3 — Redesign & Assessment (PTO) a) Generate CLOs (Prompt J) - Inputs: Selected KSAs; target Bloom level; selected course(s) - PTO Prompt - Persona: Learning architect - Task: Draft 4–6 measurable CLOs aligning KSAs to Bloom levels; include quick assessment hint - Output: CLO list with action verbs and short assessment suggestions - Deliverables: CLO set per course; Export DOCX/CSV b) Align & assess (Prompt K) - Inputs: New CLOs; preferred assessment modalities (e.g., lab, project, oral defense) - PTO Prompt - Persona: Assessment designer - Task: CLO–domain–assessment mapping; add brief ethics note per assessment - Output: Table: CLO, Domain, Assessment, Ethics Note - Deliverables: Assessment Map (CSV/DOCX) c) Activities & labs (Prompts L/M/N) - Buttons: - Prompt L: Bias audit of model outputs (lab plan + materials + risk/mitigation) - Prompt M: Sentiment analysis with open-source model (notebook outline + data license note) - Prompt N: Neuro-AI demo (protocol + device safety checklist) - PTO personas: Lab designer / Data scientist / Safety officer - Deliverables: Each is editable and exportable; add to Course Pack d) Authentic assessment generator - Inputs: Current assessment plan (paste) - PTO Prompt - Persona: Authentic assessment coach - Task: Suggest discipline-relevant, real-world assessments that evidence AI-era competencies - Output: 6–10 assessment ideas with rationale and required resources - Deliverables: Assessment Ideas sheet 5) Evidence & Citations - Panel to store links, PDFs, notes (e.g., WEF Future of Jobs 2023; institutional policies; accreditation criteria) - “Insert methods paragraph” button that explains data sources and PTO workflow for reports - Export bibliography snippet 6) Review & Export - Auto-compiled Strategic Memo (includes Step 1 findings, Step 2 KSAs and gap map, Step 3 redesigned CLOs/assessments, ethics safeguards) - Accreditation Appendix (checklist + fixes) - Faculty Workshop Pack (agenda, slides outline, quiz, evaluation form) - CSV exports (CLO grid, KSA list, Gap Map, Assessment map) UX & guardrails - Version history on all AI-generated sections - “Mark as verified” toggles for data-driven sections - Privacy reminder before analyzing student feedback - Dataset licensing and safety reminders embedded in labs - Accessibility notes (e.g., ALT text prompts for exported docs) Success metrics (in-app) - Time-to-first gap report under 10 minutes post-upload - At least 5 actionable changes identified per program - All outputs exportable without manual reformatting Preload sample/demo data (optional) - Short mission statement and graduate attributes - 8-course map (core/electives) - 25 sample CLOs across 4 courses - A small KSAs CSV with clearly labeled “sample data” watermark - Sample ethics risks table with sources PTO prompt templates (embed exactly; editable by admins) Prompt A — Mission Alignment - Persona: Institutional effectiveness analyst - Task: Analyze the mission statement and graduate attributes for AI-era readiness (technical literacy, data fluency, ethics, critical thinking, collaboration). Identify alignment strengths and clear gaps, and propose 3–5 priority actions tied to mission language. - Output: Bulleted strengths, bulleted gaps, 3–5 priority recommendations with 1-sentence justifications. Prompt B — Course Map - Persona: Curriculum cartographer - Task: Organize courses into Core vs Electives. Mark high-impact AI integration points by level and prerequisites; note quick wins vs deeper redesign. - Output: Two-column table (Core/Electives) with annotations; a second list of 5–10 integration recommendations. Prompt C — CLO Gap Scan - Persona: Learning outcomes specialist - Task: Tag CLOs with Bloom levels; flag AI relevance; detect redundancies/omissions; suggest 2–3 AI-era CLOs per course if needed. - Output: CSV: CourseCode, CLO, Bloom, AI-Relevance(Yes/No), Notes, Suggested New CLO(s). Prompt D — Student Themes - Persona: Educational researcher - Task: Summarize anonymized student feedback on relevance, AI readiness, and ethics concerns in ≤100 words; avoid personal data. - Output: Neutral theme summary. Prompt E — Accreditation Alignment - Persona: Accreditation strategist - Task: Compare program elements with the selected accreditation criteria/version. Identify gaps and propose fixes with ownership and timeline. - Output: Checklist of criteria + “Status” + “Action/Owner/Timeline”. Prompt F — Ethics & Bias Safeguards - Persona: Responsible AI advisor - Task: Identify bias/opacity/licensing/safety risks in assessments/datasets/tools; propose feasible mitigations with short references. - Output: Table: Risk, Scenario, Source, Mitigation, Feasibility. Prompt G — Labor-Market Scan - Persona: Labor-market analyst - Task: From provided evidence, list the top 15 emerging KSAs with % growth since baseline; write brief, discipline-aware descriptions; include source tags (e.g., WEF 2023). - Output: CSV: KSA, %Growth, Description, Source. Prompt H — Coverage Gap Map - Persona: Curriculum alignment specialist - Task: Compare KSAs (Prompt G) to Course Map/CLOs; label Missing/Partial/Full; suggest course homes or micro-credential pathways. - Output: Table: KSA, Coverage, Notes, Suggested Course(s). Prompt I — Job-Bank Frequency (optional) - Persona: Job-market curator - Task: Frequency table of AI-related skills in postings matching filters; cite source and date. - Output: Table: Skill, Frequency, Typical Roles, Source/Date. Prompt J — Generate CLOs - Persona: Learning architect - Task: Draft 4–6 measurable CLOs per course aligned to selected KSAs and target Bloom levels; add a brief assessment hint for each CLO. - Output: CLO list with action verbs + assessment hint. Prompt K — Align & Assess - Persona: Assessment designer - Task: Build a CLO–domain–assessment mapping with a short ethics note per assessment. - Output: Table: CLO, Domain, Assessment, Ethics Note. Prompts L/M/N — Activities & Labs - Persona: Lab designer / Data scientist / Safety officer - Task: Create an activity plan/notebook outline/protocol with materials, steps, risks, safety & licensing notes. - Output: Structured plan with checklists. Notes for code builder - Use a left-side stepper for Steps 1–3 with completion badges - Provide inline editors with “Re-run with edits” button for each output - Add Export panel with one-click pack downloads (ZIP containing DOCX/CSV/PDF) - Store project state locally; allow JSON export/import for portability.

Alternatives

Alternative options:

1. Use related GPTs e.g.,  this one, or 1, 2. ​

An alternative UI

AI

AI-Ready Curriculum Studio

Transform degree programs for the AI era

□ Load Project

1

Onboarding

2

Program Audit

3

Skills & Gaps

4

Redesign

5

Review & Export

Welcome to AI-Ready Curriculum Studio

Transform your degree program for the AI era with structured analysis and redesign tools

How It Works

1

Program Audit

Analyze current curriculum against AI-era competencies

2

Skills & Gaps

Map labor market trends to curriculum coverage

3

Redesign

Create new outcomes and assessments

Start Your Project

Program Audit

Analyze your curriculum for AI readiness using structured prompts

A: Mission Alignment

B: Course Map

C: CLO Gap Scan

D: Student Themes

E: Accreditation

F: Ethics Safeguards

Mission Alignment

Institutional effectiveness analyst

Analyze alignment to AI-era competencies (technical, ethical, data, critical thinking, collaboration)

Required Inputs:

• Mission statement
• Graduate attributes

Mission Statement

Graduate Attributes

□ Run Analysis

Analysis Results

Strengths:

• Mission emphasizes critical thinking and ethical decision-making
• Graduate attributes include digital literacy

Gaps:

• No explicit mention of AI competencies
• Data fluency not addressed in graduate attributes

Priority Actions:

1. Add AI literacy to graduate attributes
2. Incorporate data ethics into mission statement
3. Develop AI-specific program outcomes

Course Map

Curriculum cartographer

Organize courses and identify AI integration points

Required Inputs:

• Course list (CSV)

Upload Course List (CSV) Format: CourseCode, Title, Description, Level

□ Run Analysis

Course Map Results

Core Courses:

Code	Title	Level	AI Integration
CS101	Intro to Programming	100	Low
CS201	Data Structures	200	Medium

Integration Recommendations:

• Add AI ethics module to CS201
• Create new AI fundamentals course at 200-level
• Integrate AI tools into capstone projects

CLO Gap Scan

Learning outcomes specialist

Tag Bloom levels and identify AI relevance

Required Inputs:

• CLOs (CSV)

Upload CLOs (CSV) Format: CourseCode, CLO_Text, BloomLevel

□ Run Analysis

CLO Analysis Results

Course	CLO	Bloom Level	AI Relevance
CS101	Write simple programs	Apply	Partial
CS201	Analyze algorithms	Analyze	High

◀ Back Continue to Skills & Gaps ▶

Skills & Gap Mapping

Identify labor market trends and map coverage gaps in your curriculum

G: Labor-Market Scan

H: Coverage Gap Map

I: Job-Bank Frequency

Labor-Market Scan

Labor-market analyst

Identify top emerging KSAs with growth trends

Required Inputs:

• Skills CSV or summary
• Discipline/region filters

Upload Skills Data (CSV) Format: KSA, Frequency, %Growth, Source, Date

□ Run Analysis

Top Emerging KSAs

KSA	% Growth	Description	Source
Machine Learning	85%	Developing and implementing ML models	WEF 2023
Data Ethics	120%	Ethical considerations in data use	WEF 2023
AI Governance	95%	Managing AI systems and compliance	WEF 2023

Coverage Gap Map

Curriculum alignment specialist

Compare KSAs to program coverage

Required Inputs:

• KSAs from labor scan
• Course map and CLOs

□ Run Analysis

Gap Analysis Results

Full Coverage

Partial Coverage

Missing

CS101

CS201

CS350

Machine Learning

Data Ethics

AI Governance

◀ Back Continue to Redesign ▶

Redesign & Assessment

Create new learning outcomes and assessments for the AI era

J: Generate CLOs

K: Align & Assess

Authentic Assessment

Generate CLOs

Learning architect

Draft measurable CLOs aligned to KSAs

Required Inputs:

• Selected KSAs
• Target Bloom level
• Selected course(s)

Select KSAs: Machine Learning Data Ethics AI Governance

Target Bloom Level: Remember Understand Apply Analyze Evaluate Create

Target Course: CS101 - Intro to Programming CS201 - Data Structures CS350 - Machine Learning

□ Generate CLOs

Generated CLOs

1. Design and implement machine learning models for real-world problems
   Assessment: Capstone project with real dataset
2. Evaluate ethical implications of AI systems in various contexts
   Assessment: Case study analysis with written reflection
3. Apply governance frameworks to ensure responsible AI deployment
   Assessment: Policy development exercise

Lab Activities & Protocols

□

Bias Audit Lab

Lab designer

▼

Audit model outputs for bias and fairness

Lab Plan:

Materials:

• Jupyter Notebook
• Sample datasets
• Bias detection toolkit

Steps:

1. Load and explore dataset
2. Train model with default parameters
3. Analyze outputs for demographic bias
4. Document findings and mitigation strategies

Safety & Licensing Notes:

Use anonymized datasets only. Avoid sensitive attributes in analysis.

□ Generate Full Lab Plan

□

Sentiment Analysis Lab

Data scientist

▼

Analyze sentiment with open-source models

Lab Plan:

Materials:

• Python environment
• NLTK or spaCy libraries
• Social media dataset

Steps:

1. Preprocess text data
2. Apply sentiment analysis model
3. Evaluate model performance
4. Visualize sentiment distribution

Licensing Notes:

Ensure dataset licenses permit educational use. Cite model sources.

□ Generate Full Lab Plan

□

Neuro-AI Demo

Safety officer

▼

Neuro-AI demonstration protocol

Lab Plan:

Materials:

• Neural interface simulator
• AI model for pattern recognition
• Safety monitoring equipment

Steps:

1. Set up neural interface
2. Calibrate AI model
3. Run pattern recognition tasks
4. Monitor for safety issues

Safety Notes:

Follow institutional safety protocols. Have emergency procedures in place.

□ Generate Full Lab Plan

◀ Back Continue to Review ▶

Review & Export

Review your findings and export materials for committee use

Project Summary

Strategic Memo

Accreditation

Workshop Pack

Data Exports

Program Details

Name: Bachelor of Computer Science

Discipline: Computer Science, Data Science

Region: North America

Accreditation: ABET Computing

Curriculum Scope

Total Courses: 12

CLOs Analyzed: 48

Labor Data Points: 15

Key Metrics

Mission Alignment: 75%

AI Coverage: 40%

Gap Severity: Medium

Project Progress

Program Audit

Skills & Gaps

Redesign

Recommended Next Steps

1. Review and finalize new CLOs
2. Schedule faculty workshop for feedback
3. Develop implementation timeline
4. Prepare accreditation documentation

Strategic Memo

Executive Summary

Based on our comprehensive audit of the Bachelor of Computer Science program, we have identified key opportunities to enhance AI readiness while maintaining alignment with institutional mission and accreditation standards.

Key Findings

• Mission alignment gaps in AI competencies
• 5 critical KSAs not covered in current curriculum
• Opportunities for authentic AI-integrated assessments

Recommended Actions

1. Update graduate attributes to include AI literacy
2. Develop new course: AI Fundamentals (200-level)
3. Integrate ethics modules across core courses
4. Create AI-focused capstone projects

Accreditation Compliance

Criterion	Status	Action Required	Owner	Timeline
Curriculum Currency	Partial	Add AI competencies	Program Chair	Fall 2024
Assessment Methods	Full	None	-	-
Industry Alignment	Missing	Conduct industry survey	QA Lead	Spring 2024

Faculty Workshop Pack

Workshop Agenda

• 9:00-9:30: Welcome & AI in Education Overview
• 9:30-10:30: Program Audit Findings
• 10:30-10:45: Break
• 10:45-12:00: Skills Gap Analysis
• 12:00-1:00: Lunch
• 1:00-2:30: Redesign Proposals
• 2:30-3:30: Breakout Sessions
• 3:30-4:00: Action Planning

Workshop Materials

• Slide deck template
• Gap analysis worksheets
• Course redesign templates
• Evaluation form

Select Items to Export:

Strategic Memo Accreditation Appendix Workshop Pack CLO Grid Gap Map Assessment Map

Export Format:

□ DOCX

□ CSV

□ PDF

□ ZIP Package

Export Summary:

Selected 4 items for export. All exports include citations and methodology notes.

◀ Back □ Save Project