Khan Lab School
Khan Lab School (KLS) is the innovative laboratory school founded by Sal Khan, the mind that started the revolutionary free online learning platform Khan Academy.
Established in 2014 and located in Mountain View, CA, the school emphasizes a radical way of achieving mastery through practice and project-based learning. In 2021, KLS partnered with Inspirit AI to build a custom, year-long course intended to be taught as a formal class for juniors and seniors looking to expand their coding abilities beyond the Advanced Placement program. As pioneers in the ed-tech space, KLS and Inspirit AI flourished together to deliver a truly novel experience that places students at the center of their own narrative.
KLS’s Experiential Classroom
Khan Lab School believes in second chances.
Distilled into their mission of mastery-based learning is the belief that students deserve to learn at a pace that is appropriate for them.
Blurring the lines between high school and college, KLS views independent learning as a means to advance the collective — to personalize education so that students may build a solid foundation of knowledge for themselves rather than be assessed along one axis and according to a one-time metric.
Borrowing from the ethos that made Khan Academy so popular among millions of students, Sal Khan says of his flagship brick and mortar school,
“The dream has always been that online can unlock the physical experience… We wanted to create a reality where students aren’t just accountable for their own gains or their own progress but also for each other. That they’re invested in each other. That they’re unusually collaborative.”
Naturally, as a laboratory school, there are many experimental tests into how young minds could learn best, but this flexibility also creates a safe space to take risks to incorporate classes traditionally deemed too advanced for the high school level. This competency-based approach makes this all possible for teachers and students to tap into a shared desire to help one another through socially embedded practices of mutual consultation and advisory.
Khan Lab School already had a working relationship with Inspirit AI going into the 2021 school year and were interested in building out a formal course based on a shared interest in pushing the innovative boundary on the learning experience. As one of the most avant-garde schools in the country, the team of curriculum developers at Inspirit AI eagerly created a class worth building a community around.
Customized Instructional Design
Blending traditional classroom learning with KLS’s adaptive mastery system, Kayla Holman, Inspirit AI’s Director of Curriculum, set out to craft a series of courses to encourage students to take on more autonomy in their understanding of modern technology.
The educational experience needed to be one to be delivered in a hybrid format, with students learning remotely for lectures and in-person coding labs with Ms. Holman on an alternating schedule. Taking the best from both formats, Ms. Holman was able to focus on student progress and outcomes both live and asynchronously to offer as many opportunities for feedback as possible.
Emmy Li, Inspirit AI’s Head of Instructional Design, co-taught on regression and decision trees and said of the cohort,
“Teaching this group of young and curious minds was such a pleasure. During the drafting phase of the course, we placed heavy priority on creating highly interactive demonstrations, discussions, and assessments to allow the instructor to pace material to both allow those behind to catch up, offer enrichment to those ahead, and keep the entire class buzzing and talking. The activities we coded for the kids on Desmos ensured that there was a real world application to the theoretical concepts they absorbed during lecture.”
Introduction to Artificial Intelligence
Course Logistics
“Introduction to Artificial Intelligence” runs twice a week, relying on a tech stack of Google Colaboratory, Google Drive, Zoom, and Piazza to integrate technology throughout the experience. Through daily knowledge checks, in-class coding notebooks, weekly coding homework assignments, end-of-class submissions, and exams, mastery is demonstrated and assessed consistently in multiple modalities. KLS evaluates individual assessments using a PEN rubric—short for proficient, emergent, and novice levels of understanding, knowledge, and skills.
First Half
In the first half of the course, students learn AI’s core technologies including applications, foundational concepts, and programming tools through live video lecture and discussion classes and in-person coding labs mini-projects. Students not only learn about different types of machine learning models, but apply those models to real datasets.
Second Half
In the second-half of the course, students complete an instructor-led group project, applying the programming skills developed in the first half. Additionally, the course has a midterm examination in the seventh week, as well as a cumulative final project and presentation. Over six distinct modules (Python Review and Intro to ML, Linear Regression, Classification, Natural Language Processing, Computer Vision and Neural Networks, Convolutional Neural Networks, and Final Project) and a semester of rewarding work, students hone their skill set for college-level research.
Project-Based Learning: For College and Beyond
For a course as innovative at the high school level as “Introduction to Artificial Intelligence,” students are definitely reaping the benefits of the exposure to college level quantitative thinking. These computer science and data science skills are near universal in modern STEM research, and the independent project portfolio they wield can garner access to more advanced courses, internships, and assistantships upon graduating. 21st century skills like coding, data visualization, explainability, scientific communication, project management, and domain research get students’ foot in the door for wider opportunity.
While it may initially seem like this is an ordinary computer science class, this class of students have shown that the intersection of technology and seemingly orthogonal domains like history, economics, art, poetry, and astronomy can produce the most novel solutions to complex problems. The invaluable practice of learning through project based time has proven that students not only have the ability to memorize complex bits of information, but to use it to transform the world for social good.
Student Success Stories
On final presentation day, Ms. Holman’s students smiled as they displayed their machine learning models’ findings in an outdoor venue for classmates, school officials, and friends to listen. With projects ranging in domain and algorithms applied, each individual spoke during their group presentation with micro-subject matter expertise they had cultivated during the cumulative research endeavor.
“Introduction to Artificial Intelligence” is already in its second cohort of students for the spring semester with Kayla Holman once again at the instructional helm. As she reflects on the entire process from inception to execution, Ms. Holman beams with pride at the innovative pedagogical initiative. She exclaims,
“Getting the opportunity to teach at KLS has been the best part about working at Inspirit. Not only are the students extremely intelligent, they're also so passionate about learning and willing to dive deep into coding. Starting from a wide range of coding abilities, these students were able to complete the term with machine learning projects build from scratch which is an incredible accomplishment.”
Looking into the Future
After the success of the first three semesters of “Introduction to Artificial Intelligence,” KLS is once again partnering with Inspirit AI to develop a summer program intended to fit within their philosophy of extended days of independent study. A key distinction from the courses running during the academic year, the summer program offers a broader breadth of subject matters covered, intended to be more accessible to those without formal computer science training. While the more formal course emphasizes mathematical and algorithmic processes underlying machine learning, the summer program presents concepts in artificial intelligence that relate to unexpected areas like photography, song-writing, criminal justice, ecology, and more. As these bespoke programs continue to flourish, all stakeholders hope to bring in as many students from all interests and backgrounds to promote technological fluency for all.
