1About CAI1001C — AI Thinking for Educators¶
CAI1001C: AI Thinking for Educators is a professional development course offered at Miami Dade College, designed to equip K–12 teachers with the AI literacy, pedagogical adaptability, and practical tool fluency they need to thrive in an AI-integrated educational landscape. The course is structured around eight chapters — each one pairing conceptual depth with hands-on application — and is anchored in the understanding that technology adoption without pedagogical intention does more harm than good.
This addendum provides a transparent map of the course: how each chapter aligns to program competencies, what learning theories ground the work, which hands-on labs develop practical skills, and how the course’s eight measurable learning outcomes connect to the full arc of the book.
2CAI1001C Course Competencies¶
The following seven competencies define what a successful CAI1001C graduate can do. Each chapter targets one or more of these competencies, building toward a comprehensive professional AI skillset.
CAI1001C Competency Framework
No. | Domain | Competency Statement |
|---|---|---|
C1 | AI Literacy | Demonstrate foundational understanding of how large language models and AI systems work, including their capabilities, limitations, and the mechanisms behind AI-generated output. |
C2 | Pedagogical Adaptation | Redesign learning experiences and instructional strategies to account for AI’s impact on lower-order thinking skills, repositioning teaching toward higher-order cognition, creativity, and human connection. |
C3 | Tool Fluency | Apply Google AI tools — including Gemini, NotebookLM, AI Studio, and Google Antigravity — purposefully and proficiently in professional education contexts. |
C4 | Ethical Practice | Articulate and apply ethical frameworks for AI use in K–12 settings, including issues of equity, academic integrity, data privacy, and age-appropriate deployment. |
C5 | Assessment Design | Design authentic assessments that remain valid and meaningful in an AI-enabled environment, emphasizing process, reasoning, and real-world performance over rote output. |
C6 | Learner Support | Use AI tools to support differentiated instruction, including students with IEP/504 accommodations, English Language Learners (ELL), and learners who benefit from personalized pacing and scaffolding. |
C7 | Professional Growth | Develop a personal AI professional development roadmap aligned with evolving best practices, institutional expectations, and the long-term trajectory of AI in education. |
3Chapter-to-Competency Alignment¶
The table below maps each of the eight chapters to the competencies it primarily addresses, the learning theory anchoring the instructional design, the hands-on lab included in each chapter, and the point value toward the course total.
Chapter Alignment to CAI1001C Competencies
Ch. | Title | Competencies | Learning Theory | Hands-On Lab | Points |
|---|---|---|---|---|---|
1 | The Classroom Has Already Changed (Whether You Notice or Not) | C1, C2, C4 | Constructivism (Piaget); Bloom’s Revised Taxonomy; Sociocultural Theory (Vygotsky) | Bloom’s Audit: Classify your existing lesson objectives and identify where AI displaces student thinking | 30 |
2 | Inside the Machine: What AI Actually Is | C1, C4 | Cognitive Load Theory (Sweller); Technological Pedagogical Content Knowledge (TPACK) | Prompt Autopsy: Dissect AI responses to identify hallucinations, biases, and confidence gaps | 30 |
3 | Gemini and the Art of the Gem | C3, C6 | Differentiated Instruction (Tomlinson); Universal Design for Learning (UDL) | Gem Builder: Create a custom Gemini Gem configured for a specific student population or instructional need | 30 |
4 | NotebookLM: When Your Sources Talk Back | C3, C5, C6 | Inquiry-Based Learning; Information Processing Theory | Source Studio: Upload course materials and use NotebookLM’s Audio Overview and Q&A to build a student-facing study resource | 30 |
5 | AI Studio: Behind the Curtain | C1, C3, C5 | Metacognition; Constructionism (Papert); Systems Thinking | System Prompt Lab: Configure an AI Studio agent with a role, persona, and constraints designed for a real classroom use case | 30 |
6 | Your Synthetic Educational Team: Agents with Google Antigravity | C3, C6, C7 | Distributed Cognition; Project-Based Learning (PBL) | Agent Assembly: Build a multi-agent Antigravity workflow that handles a recurring teacher task (grading rubric generation, differentiation, parent communication) | 30 |
7 | Pedagogy First: Putting AI in Its Place | C2, C4, C5, C6 | Humanistic Education (Rogers); Critical Pedagogy (Freire); Ethical Reasoning Frameworks | Integrity Redesign: Take an existing assignment, identify AI vulnerabilities, and redesign it using authentic assessment principles | 30 |
8 | The Long View: Education’s Next Decade | C4, C7 | Futures Thinking; Reflective Practice (Schön); Professional Learning Communities (DuFour) | PD Roadmap: Draft a 12-month personal AI professional development plan with specific milestones, tools to explore, and a commitment to peer knowledge-sharing | 30 |
4Course-Level Learning Outcomes¶
Upon successful completion of CAI1001C, students will have demonstrated all eight learning outcomes listed below. Each outcome corresponds to one chapter of the course and is written as a measurable, observable performance standard.
Addendum A — CAI1001C: AI Thinking for Educators | Miami Dade College | Dr. Ernesto Lee