Table view

Workshop with the team

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Determine the end skills and concepts required for AI and Data Science

A table of core skills and concepts

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Determine the prerequisite technical skills and concepts and build a progression tree

A table with prerequisites and a visualization of the sequences

It is possible that one concept can be learned from more than one angle. E.g. the concept of convolution can be introduced when talking about music and audio or it could be introduced with images.

First pass at connecting the technical skills and concepts with the Common Core, AP, and other core standards

Adding more detail to the existing table / visualization

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Highlight units that your teachers may not be currently teaching but are essential to understanding Data Science / AI

A list of units and concepts with descriptions

E.g. one thing that students will definitely need to learn to truly understand AI is matrices and the idea that multiplying by matrices is literally shifting perspective.

From the connections explore the possibility of reorganizing math courses so that students more easily grasp connections required for Data Science / AI / Future of Work and see the connections between different topics

A document or table with new proposed math sequences and units/topics that they would cover.

E.g. you could teach conic sections from the Geometrical perspective in the same semester as the Algebraic perspective and have students do a project related to that.

This might be an ongoing experimentation.

From the connections, enumerate potential real-world projects and a few possible sequences

A document or table with a list of project ideas, up to a paragraph of description for each and an optional image or screenshot of a possible final product

E.g. Data Visualization - students create a data story in English using a pre-curated dataset and create a website with an essay that uses data visualizations as evidence.

Signal Processing - In Algebra 2, students use an AI technique to create a software that can take in audio input from a person wearing a mask and modify it so it sounds as clear as if the person was not wearing a mask.

Set up meetings with local companies for sponsorship

Meetings set up with local companies’ leaders

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Prepare a pitch slideshow (and making some possible iterations), putting together a clear ask and value proposition

A slideshow or video for the pitches

We may offer to develop a project where students develop a product relevant to that company, or that company gives us datasets for students to analyze.

We may ask for direct funding, equipment donations, allocations of interns, etc

Pitch with you to companies/foundations for sponsorship

Pitch presentations

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Co-design a rough lesson plan with teachers

A lesson plan outline document with descriptions of the activities and stages of each project, what technical skills are addressed, and what scholastic standards are addressed

This would include the list of units/topics that students would cover through this project, and a sequence diagram of how student teams might progress through the project. This can still be tweaked as we add more detail to the project and revise it for future years.

Code / build a technical demo as an example of what students could produce

A technical demo (piece of software) that is an example of what students could produce

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Develop the instructional content, videos, diagrams, quizzes, etc. for students and teachers to be able to follow along and build their own projects

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Collect and clean a variety of datasets for students to choose from

A list of datasets (approximately 1,000 to 10,000 entries) in each dataset

Cleaning means to put each entry of the data in a standard format.

We want to make available enough data that there is at least 1 topic that is meaningful to students.

inventXYZ trains teachers - teachers do the project as if they are the students and then reflect as educators

A teacher training session

Note: we can either have the teachers do the entire project or have them just do a few critical sections for a shorter training time (8-10 hours).

If done in a contiguous block of time, the training session could be done in 4 days.

Revise project materials from teachers’ feedback

Since we have been working collaboratively with the teachers from the start, any revisions are likely to be fairly minor (e.g wording or diagrams)

Pre-test covering both data science objectives and ELA objectives

Pre-test results

Collecting data about where students are starting from will help us truly measure the impacts on student learning and help improve the content

Students create their data visualizations / write code for their analysis

Students in 9th grade ELA complete the project during class

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Students present their data visualizations / analyses to school leadership, community members, and/or local companies

A student presentation

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Post-test covering both data science objectives and ELA objectives

Post-test results

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Co-design a rough lesson plan with teachers

A lesson plan outline document with descriptions of the activities and stages of each project, what technical skills are addressed, and what scholastic standards are addressed

This would include the list of units/topics that students would cover through this project, and a sequence diagram of how student teams might progress through the project. This can still be tweaked as we add more detail to the project and revise it for future years.

Code / build a technical demo as an example of what students could produce

A technical demo (piece of software) that is an example of what students could produce

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Develop the instructional content, videos, diagrams, quizzes, etc. for students and teachers to be able to follow along and build their own projects.

A fully-developed curriculum project in the inventplatform webapp

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inventXYZ trains teachers - teachers do the project as if they are the students and then reflect as educators

A teacher training session

Note: we can either have the teachers do the entire project or have them just do a few critical sections for a shorter training time (8-10 hours).

If done in a contiguous block of time, the training session could be done in 4 days.

Revise project materials from teachers’ feedback

Since we have been working collaboratively with the teachers from the start, any revisions are likely to be fairly minor (e.g wording or diagrams)

Pre-test covering both data science objectives and ELA objectives

Pre-test results

Collecting data about where students are starting from will help us truly measure the impacts on student learning and help improve the content

Students create their data visualizations / write code for their analysis

Students in 9th grade ELA complete the project during class

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Students present their data visualizations / analyses to school leadership, community members, and/or local companies

A student presentation

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Post-test covering both data science objectives and ELA objectives

Post-test results

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Help you understand IT infrastructure requirements so that you know what tools and permissions students need to be able to code.

A list of software and sites that need to be unblocked, some programs that need to be installed, and some permissions that students will need to be able to do their projects.

Also, some example workflows detailing what technical tools students might need in each project

E.g. to use many tools for machine learning such as specific libraries of code for python, students will need access to the command line, sites like github will need to be unlocked. This will be a bit of an iterative process.

Work with your team and facility planners to highlight a suitable space in the school floorplan

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Identify the physical specifications and potential alterations required for the space

A list of general specifications and potential alterations

E.g. specifications for acoustics reverb time and total loudness, ventilation, overall illumination, and some specific notes on what might need to be improved in the area chosen.

A budget estimate table with line items for equipment, furnishings, lighting, etc, and installation labor.

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Help pitch the overall vision of the AI academy, the space, and curriculum to constitutuents

Presentations at townhalls (or video interviews, etc)

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Wait for bond to pass

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Finalize vendors for equipment, lighting, and other furnishings

A table of final vendors, why that vendor was picked, pricing, and delivery schedule estimates.

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Final architectural plans and a 3D walkthrough

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The construction and installation will be handled by your standard contractors. inventXYZ will simply provide some oversight and quality control to make sure things are set up as intended.

Equipment vendors will install the equipment and test it

The construction and installation will be handled by your standard contractors. inventXYZ will simply provide some oversight and quality control to make sure things are set up as intended.

An event to which public and funders can be invited

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Reflect on projects #1 and #2 and revise as needed

Workshop presentation with district leaders on learnings and strategy for year 2

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Begin developing the next batch of projects as per our previously identified curriculum progression

Curriculum outlines for the next batch of projects

We’ll add more detail as we create our plan in 2021 fall and see the initial batch of projects in 2022 spring.

Teacher training for new batch of projects

Teacher training sessions

We’ll add more detail as we create our plan in 2021 fall and see the initial batch of projects in 2022 spring.