STEAM InnovatedEDUCATION · CONSULTING

COMPUTER SCIENCE + AI LITERACY + EQUITABLE LEARNING

Keep the
thinking human.

Computer science for deeper learning—in every subject.

I help educators connect computer science, AI literacy, and equitable learning to the subjects they already teach—so students can investigate, create, test ideas, and explain their thinking.

Professional learning & consulting with Judianne Ganschow

Teacher judgmentStudent reasoningMeaningful accessClassroom transfer

COMPUTER SCIENCE + AI LITERACY ACROSS THE CURRICULUM

Start with the subject.
Deepen the thinking.

Start with a subject learning goal. Connect computer science and AI literacy to it—with students building, investigating, questioning, and making decisions.

MATHEMATICS

Make a rule.
Put it to the test.

Computer science

Program a rule for a growing pattern, test new inputs, and explain when the rule works.

Thinking to develop: Algorithms, inputs, and testing.

AI literacy

Compare an AI-generated pattern rule with students’ own reasoning. Test new cases, identify any errors, and justify whether to accept, revise, or reject the rule.

Thinking to develop: Checking outputs with mathematical evidence.

SCIENCE

Build a model.
Question what it shows.

Computer science

Build a simple ecosystem simulation, change one variable, and compare its behavior with evidence.

Thinking to develop: Computational models and data.

AI literacy

Create, test, and improve a model. Students develop an AI model to classify leaves, choose its training examples, and test it with unfamiliar leaves. They investigate mistakes, decide what needs to change, and refine the model through ongoing cycles of testing and revision. Students compare results across versions, explain the reasoning behind their changes, and use evidence to judge whether the model improved—and where it still falls short.

Thinking to develop: Training data, classification, iterative testing, and evidence-based decisions.

LANGUAGE ARTS

Make a choice.
Follow the consequences.

Computer science

Create a branching story. Use conditions to connect choices and consequences, then revise for a clear narrative.

Thinking to develop: Sequences, conditions, and interactive design.

AI literacy

Compare an AI-suggested story branch with students’ drafts. Check characterization, stereotypes, and voice; decide what to keep or reject and acknowledge any AI contribution.

Thinking to develop: Human authorship, bias, and responsible use.

SOCIAL STUDIES

Explore the data.
Ask whose story it tells.

Computer science

Use a spreadsheet to sort and visualize community data. Question whose experiences are represented—and whose are missing.

Thinking to develop: Data analysis, representation, and computing’s impacts.

AI literacy

Compare an AI-generated account of a community issue with selected primary sources. Identify unsupported claims, missing perspectives, and evidence needed before sharing.

Thinking to develop: Verification, representation, and responsibility.

Illustrative learning connections—not additional assignments. The subject goal comes first; choose computer science, AI literacy, or both when they serve it.

Explore subject-centered professional learning

THE APPROACH

Every student deserves
a meaningful way in.

The goal is not more technology. It is more opportunity for students to reason, create, and make sense of what they are learning.

We begin with the learning goal, the thinking students need to do, and the people in the room. Then we design supports that widen participation while preserving the challenge.

01

Keep the learning at the center

Start with a subject goal. Choose computer science and AI connections that deepen the thinking rather than replace it.

02

Design for participation

Build in clear language, flexible ways to respond, and access options that help students work toward the same meaningful goal.

03

Make it usable tomorrow

Connect professional learning to a real lesson, test the first version, and use classroom evidence to guide the next step.

WORK WITH ME

Start with the challenge
your team is facing.

Workshops, planning partnerships, and implementation support for schools, districts, county offices, and education organizations.

01 / COMPUTER SCIENCE

Computer science
across the curriculum

Help educators use computer science to deepen learning in mathematics, science, language arts, the arts, and beyond—not only in a separate CS class.

  • Teach the Thinking and Interactive Storytelling
  • Algorithms, models, data, and programming in subject learning
  • Accessible lesson design and visible student reasoning
Explore CS integration
02 / AI LITERACY

AI literacy
with human judgment

Connect AI literacy to subject learning: investigate how AI works, question its outputs, and make informed choices while protecting student reasoning and teacher judgment.

  • AI concepts, training data, and model limitations
  • Evidence-checking, bias, and responsible choices
  • PHACT planning and teacher-created learning tools
Discuss an AI workshop
03 / LEADERSHIP & TRANSFER

From a good idea
to sustained practice

Give leaders and teams a practical way to connect goals, professional learning, classroom implementation, and evidence.

  • Needs assessment and planning
  • Facilitated team learning and coaching
  • Program reflection and improvement
Talk through a partnership

Independent consulting is available to organizations outside Monterey County. Scope and timing are tailored to your team.

FOR AI-SUPPORTED LEARNING · THE PHACT FRAMEWORK

Before the prompt,
there’s PHACT.

Purpose, Human Anchor, Audience, Components, and Tone and constraints (PHACT).

A planning framework for keeping human judgment at the center of AI-supported teaching. Start with what students need to learn and what people must contribute, then shape the resource around those decisions.

Explore the PHACT resource page
P

Purpose

What should students understand or be able to do?

H

Human Anchor

What judgment stays with the teacher? What thinking stays with the student?

A

Audience

Who are the learners, and what supports participation?

C

Components

Which features serve the learning purpose?

T

Tone and constraints

How should it communicate, and what boundaries matter?

RESOURCES FOR EDUCATORS

Something useful.
A place to begin.

Start with the subject-based CS and AI-literacy examples above. For AI-supported lesson design, use these two PHACT downloads. No email required.

PDF · PLANNING TOOL

PHACT Planning Sheet

Clarify the learning purpose, human contribution, audience, features, and constraints before you build.

Download the planning sheet
PDF · REVIEW TOOL

PHACT Testing Checklist

Check a classroom resource for instructional value, accuracy, usability, and access before students use it.

Download the testing checklist

MEET YOUR COLLABORATOR

Judianne
Ganschow

Educator. Consultant.
Creator of PHACT.

I help educators connect computer science and AI literacy with the work that matters most: helping every student learn.

For more than a decade, my work has centered on inclusive learning design and helping schools create meaningful opportunities for students. Through STEAM Innovated, I bring together computer science, AI literacy, and practical professional learning.

My work includes teacher learning experiences, integrated CS resources, classroom tools, and program analysis. Across that work, I return to the same questions: Whose thinking is visible? Who can participate? What evidence will help us decide what to do next?

I created PHACT to make those decisions explicit before AI starts producing. My goal is to help educators develop the judgment and confidence to adapt an idea to their own students and context.

Instructional designComputer science integrationHuman-centered AIEquitable participation

LET’S START WITH YOUR CONTEXT

What do you want
to make possible?

Tell me about your educators, the students they serve, and the challenge you are working through. We can explore a workshop, a planning conversation, or a longer partnership.

Email Judianne