The ASCEND-AI Curriculum

Building AI Literacy from Understanding to Stewardship

The ASCEND-AI Curriculum is a structured learning framework designed to help faculty and students develop the knowledge, critical thinking skills, and ethical foundations needed to engage with artificial intelligence responsibly. Through six interconnected modules, participants progress from foundational concepts to discipline-specific application and AI leadership.

Module 0: ASCEND-AI Overview

Getting started with the ASCEND AI learning journey.

Participants are introduced to the ASCEND AI initiative, program goals, and the ASCEND AI Learning Matrix that guides the curriculum experience.

Module 1: AI Literacy & Fundamental Concepts

Phase: Grounding

Core Question: What is AI, what is it not, and where does human thinking begin?

What You’ll Learn:

•  Explain AI concepts in your own words (pattern recognition, training data, probabilistic prediction)

• Distinguish human meaning-making from machine acceleration

• Apply prompt literacy as a professional communication skill

• Ask appropriate questions about AI policies before using tools in new contexts

  
  

Why It Matters: Grounding means understanding AI deeply enough to use it strategically rather than reflexively. You maintain intellectual ownership of your ideas and professional judgment in your field.

Module 2: Responsible AI Use & Ethical Foundations

Phase: Judgment

Core Question: When should AI be used, when should it not, and who decides?

What You’ll Learn:

• Apply ethical reasoning in context - Identify when “looking good” creates harm

• Articulate how trust is built or broken through AI-supported decisions

• Test AI systems for ethical boundaries in real scenarios

  
  

Why It Matters: Ethics is not abstract principles, it’s embedded practice. Professional judgment means understanding that speed and efficiency compete with dignity, fairness, and accountability. You learn to prioritize what matters most.

Module 3: Detecting Misinformation, Bias & Hallucinations

Phase: Verification

Core Question: How do I know when AI is wrong, and what do I do about it?

What You’ll Learn:

• Verify AI outputs using discipline-specific standards

• Identify fabrications, bias, and misleading summaries systematically

• Document uncertainty transparently

• Treat truth as a human responsibility, not a model feature

  
  

Why It Matters: AI generates plausible-sounding content that can be completely fabricated. Your professional credibility depends on what you verify, not what AI generates. Verification is not optional, it’s essential.

Module 4: Discipline-Specific Integration

Phase: Integration
Core Question: How does AI serve my field without replacing its core thinking?

 What You’ll Learn:

• Identify AI uses that make sense within your discipline

• Preserve disciplinary theory, methods, and lived context

• Apply AI to authentic problems while maintaining professional standards

• Design human-AI workflows that enhance rather than flatten disciplinary thinking

  
  

Why It Matters: Different disciplines have different AI opportunities and risks. A tool that accelerates work in one field may undermine rigor in another. Integration means applying stewardship within your specific professional context. 

Module 5: AI, Innovation & Stewardship

Phase: Leadership

Core Question: How do I lead responsibly in a world shaped by AI?

What You’ll Learn:

• Frame innovation problems in real community or institutional contexts

• Evaluate solutions for impact, ethics, and adaptability, not novelty alone

• Exercise influence without formal authority

• Position yourself as a steward, not a passive user

  
  

Why It Matters: You may enter workplaces where you understand AI better than those managing you. This module prepares you to lead responsible AI adoption in organizations still figuring it out. Stewardship is leadership.

Why This Curriculum Matters

Progression: Grounding → Judgment → Verification → Integration → Leadership

Outcome: You move from AI consumer to AI steward, capable of using AI with intention, verifying outputs, maintaining disciplinary integrity, and leading responsibly.

For Faculty: You will engage with these modules through the Faculty Learning Community (FLC), adapt them for your discipline, and integrate AI literacy into your existing courses. You are not expected to become AI experts. You are expected to model intellectual ownership, ethical reasoning, and disciplinary judgment in how you and your students engage with AI.

For Students: You will encounter these modules as part of your coursework. Each module builds on the one before it. By the end, you will not just understand AI. You will be able to use it with intention, verify its outputs, apply it within your field, and take responsibility for the decisions you make with it.

Together, these learning experiences help cultivate AI-competent communities that are equipped not only to use AI, but also to question it, evaluate it, and shape its future responsibly. These modules can be taken independently or integrated into existing courses, providing flexible pathways for learning.