Academic Catalog

LINC 51F: ARTIFICIAL INTELLIGENCE LEADERSHIP & EMERGING EDUCATIONAL TRENDS

Foothill College Course Outline of Record

Foothill College Course Outline of Record
Heading Value
Effective Term: Spring 2026
Units: 3
Hours: 3 lecture per week (36 total per quarter)
Degree & Credit Status: Degree-Applicable Credit Course
Foothill GE: Non-GE
Transferable: CSU
Grade Type: Letter Grade (Request for Pass/No Pass)
Repeatability: Not Repeatable

Student Learning Outcomes

  • Design a strategic plan for responsible AI adoption that aligns with institutional goals and centers equity and accessibility.
  • Critically evaluate emerging AI technologies and implementation frameworks, providing evidence-based recommendations that address ethics and inclusion.

Description

This course prepares educators to lead responsible artificial intelligence (AI) adoption at the school or district level by combining innovative thinking with practical change management strategies. Participants will study emerging AI technologies, analyze implementation frameworks for privacy, bias mitigation, and accessibility, and develop professional learning experiences that build educator capacity. Topics include program design, stakeholder communication, metrics for evaluating impact, and equity-centered decision-making. Students will develop a comprehensive plan to champion ethical, future-ready AI initiatives that align with institutional goals and community values.

Course Objectives

The student will be able to:

  1. Investigate and compare emerging artificial intelligence (AI) technologies and trends, evaluating their systemic potential and readiness for K-12 contexts.
  2. Analyze legal, ethical, and policy frameworks—including privacy, bias mitigation, and accessibility mandates—to inform institution-wide AI decisions.
  3. Develop stakeholder-aligned communication strategies that build a shared vision and foster buy-in for responsible AI initiatives.
  4. Design professional learning and change management plans that equip educators and staff to implement AI tools effectively and equitably.
  5. Establish metrics and evaluation methods to measure the impact of AI initiatives on learning outcomes, equity goals, and organizational objectives.

Course Content

  1. Emerging artificial intelligence (AI) technologies and trends
    1. Overview of systems and models for K-12 contexts
      1. Large-language
      2. Multimodal
      3. Agentic
      4. Emerging
    2. Horizon-scanning methods
    3. Adoption-curve analysis
    4. Readiness factors
      1. Infrastructure
      2. Policy alignment
      3. Pedagogical fit
  2. Legal, ethical, and policy frameworks
    1. Privacy statutes and district policies
      1. FERPA
      2. COPPA
      3. GDPR
    2. Bias-mitigation frameworks
    3. DEIA alignment
    4. Accessibility standards
  3. Stakeholder communication and vision building
    1. Identifying and mapping stakeholder groups
    2. Crafting value propositions and shared-vision narratives
    3. Feedback loops and transparency
  4. Professional learning and change management
    1. Designing PD pathways
      1. Workshops
      2. Coaching
      3. Micro-credentialing
    2. Cultivating communities of practice to support culture shift
    3. Sustaining momentum through iterative support and resource curation
  5. ​Metrics and impact evaluation
    1. Defining success indicators
      1. Learning outcomes
      2. Equity metrics
      3. Operational efficiency
    2. Data-collection strategies
    3. Iterative improvement cycles
    4. Reporting structures for stakeholders

Lab Content

Not applicable.

Special Facilities and/or Equipment

When taught via the internet: Students must have current email accounts and/or ongoing access to internet capable computers or tablets.

Method(s) of Evaluation

Methods of Evaluation may include but are not limited to the following:

Development and presentation of a responsible AI strategic plan that aligns with institutional goals and centers equity and accessibility
Constructive contributions to class discussions and peer-review sessions that advance collective understanding and refine individual projects
All major assignments will be evaluated against detailed rubrics, with opportunities to revise and resubmit work based on instructor and peer feedback

Method(s) of Instruction

Methods of Instruction may include but are not limited to the following:

The student will engage with course concepts through multimodal instructional materials offered in accessible formats, supplying multiple means of representation
The student will observe instructor-guided demonstrations and then apply skills using a modality of their choice (e.g., digital, visual, or written), providing multiple means of action and expression
The student will co-construct knowledge by participating in synchronous or asynchronous discussions, peer feedback, and collaborative activities that honor diverse cultural and linguistic assets, ensuring multiple means of engagement

Representative Text(s) and Other Materials

Khan, Salman. Brave New Words: How AI Will Revolutionize Education (and Why That's a Good Thing). 2024.

Instructor-assigned notes, materials, and resources, including instructional materials, open education resources, multimedia, and websites.

Types and/or Examples of Required Reading, Writing, and Outside of Class Assignments

  1. Reading assignments include analysis of texts, selected examples, and student projects.
  2. Writing assignments include multiple developmental projects, reflections, discussion responses, and peer feedback on projects.
  3. Outside assignments include project planning and development, participation in online peer collaboration activities, and project development through an iterative process.

When taught online, these methods may take the form of multimedia and web-based presentations. Assignments will be submitted online as well.

Discipline(s)

Instructional Design/Technology