Product profilesInsights from the tourActions you can take
About the tourAbout Instruction Partners
Khanmigo by Khan Academy
Khanmigo by Khan Academy
<
About
Users' Take
Our Instructional Take
Evidence of Impact
From the Developer
>
←
More products
About icon

Khanmigo by Khan Academy

Khan Academy is an online platform of instructional videos and practice problems covering math, science, and other core subjects. Khanmigo is the AI tutor built into it, where students can ask for help on a problem as they work or work through an essay writing process, and teachers can get help with planning and interpreting student data. In addition, Khan Academy has launched interim assessments in which students interact with AI to explain their thinking about math problems and reading tasks. 

‍

What it looks like in action

What the students do:

Students independently work through Khan Academy's instructional videos and practice problems, submitting answers that the platform marks right or wrong. Where a school system or school has purchased it, students can also use an optional chat panel to ask the AI tutor, Khanmigo, for help on a problem before or after they submit, ask where to start, or bring questions and content from outside Khan's courses. Students can finish their work without ever interacting with Khanmigo. In school systems using Khan's interim assessments, some items in the assessment require students to type out an explanation of their thinking in response to Khanmigo's questions.

What the AI does:

For student tutoring, AI provides support and feedback while students are working on questions. The Khan Academy platform underneath it provides human-written problems, scores them, tracks mastery, and serves videos without AI. While students are working on these problems, they can engage in conversation with Khanmigo, which uses generative AI to respond, rather than pulling from pre-written hints. Behind the scenes, during the conversation, Khan passes the problem, the step-by-step solution, and what the student has already mastered and recently gotten wrong to the AI model, which helps make the AI response more accurate and tailored to the student. The chat also displays suggested questions that students can click if they do not know what to ask. Khanmigo acts differently before a student submits an answer versus after they submit an answer. Before submission, Khanmigo gives hints and strategies but will not provide the answer. After the student submits, Khanmigo gives more step-by-step guidance, and sometimes the answer, so students can find where they went wrong. During interim assessments, for some items, students complete a more traditional multiple choice or fill-in-the-blank assessment item and then engage in a short conversation with the AI in which the AI asks them to explain their answer. Behind the scenes, the students' responses are scored by the AI based on a rubric written by Khan’s content authors.

What the teacher does:

For teachers, Khanmigo works through the teacher dashboard: it summarizes student chat logs, reports how a class is progressing, suggests what to focus on, and proposes student groupings with a recommended assignment for each. There are also numerous teacher tools to help draft lesson plans and complete other administrative tasks. Teachers assign practice aligned to the lesson they are teaching from their own core curriculum, and monitor student progress during class. Teachers can also assign personalized practice to fill gaps from prior years or move students ahead. In the rotation model Khan designs for, teachers lead small-group instruction with one group while another works on Khan. They can read students' chat logs with Khanmigo, accept or override the groupings and assignments it proposes, and use its free planning and administrative tools. Teachers also receive flags from the system if it detects inappropriate conversations with Khanmigo. Teachers can then view the chats and decide whether to discuss the interaction with the student.

What the leaders do:

Leaders can purchase student access to Khanmigo, either through a school system agreement or by school, which determines whether students can use the tutor at all. They set the instructional design Khan sits inside: which core curriculum teachers use, when practice happens in the schedule, and whether Khan serves on-grade-level practice, intervention, enrichment, or all three. Leaders also have access to dashboards that allow them to track usage and learning on the site and receive warnings about inappropriate or concerning conversations with Khanmigo.

Reach

900,000

Students

For school year 2025–26

—

Teachers

—

Schools

~630

School systems

For school year 2025–26

Use

Recommended use

Thirty or more minutes per week, or 18 or more hours across the school year

Actual use

Nine percent of students reached 18 or more hours across the school year. Another 15% reached nine to 18 hours.


Note:
Khan has shifted its framing from minutes spent to the number of skills a student practices until reaching proficiency, focusing on learning outcomes rather than time.

‍

Product dimensions

Subject

Math, science, ELA/literacy, humanities, test prep

Grade span

K–12

Curriculum alignment

Curriculum-connected and standards-aligned for math: Khan provides its own videos and practice problems organized to match scope and sequence from Illustrative Mathematics, Eureka Math, and EngageNY Standards-only for other core subjects

Design scope

Specific instructional job

The way AI interacts with students

  • Both students and AI asks questions
  • Right/wrong signal (most of the time)
  • AI gives feedback directly to students

Teacher guidance

Offers a range of uses (no specific teacher nudges)

Social vs. solo use

Independent use only

Teacher override

Teacher cannot override—auto-scored

Product adoption

Both—teacher-adopted and system-adopted

Dashboard scope

Teacher and leader dashboards available

Dosage recommendations

Provides dosage recommendations

User values icon

Users' take on wins and limitations

There are clear trends in what users (i.e., teachers, students, instructional leaders) see as the wins and limitations of each product. For each trend below, we've included one illustrative quote from our user interviews.

Wins

Khan's practice is tagged to individual skills, so a school can take its own interim assessment results, sort students by the skills they missed, and assign practice on exactly those skills.

"We're able to take a set of data like our interim assessments, disaggregate the data based on what skills are targeted for everybody, which skills are targeted for small groups. And teachers are able to assign assignments based on data."

— Network STEM Director

Khanmigo notices when a student keeps missing problems in a set and points them toward an instructional video or explanation that addresses it, without the student having to ask or the teacher having to catch it.

"If a student has repeated errors with a skill set, Khanmigo will say, ‘looks like you need some help’ or ‘looks like you need to watch this video.’ So Khanmigo redirects them.”

— Teacher, 5th Grade Math

Khanmigo reads a class's usage data on request and proposes which students to group and what to assign each group, in place of a teacher working through the reports to build those groups.

"Teachers can ask Khanmigo to synthesize their data set from class usage and tell them what they should be doing for targeted groups….They’re spending time reviewing groupings rather than building them from the reports themselves."

— Network STEM Director

Limitations

Khan's design is practice questions and immediate feedback, which builds fluency on a skill but does not ask students to reason through, explain, or defend their thinking.

"It's a program that gives you some practice questions. It gives you real-time feedback, but it doesn't support all the cognitive encoding work that kids really need.”

— Network STEM Director

Khan's answer recognition reads for a specific answer format, so a student who understands the math can be marked wrong for how they wrote it.

“The student understood the place value, but Khan didn’t recognize the way he entered the answer. He wrote ‘hundredths,’ and Khan marked it wrong because it wasn’t in the expected format (e.g., decimal).”

— Teacher, 5th Grade Math

Khan’s support can be bypassed. Students can just engage in practice without watching videos or reading articles. As a result, assignment completion may show that students got answers right, but not whether they used or learned from the instructional supports.

“With Khan, kids can skip the video and the teaching part. So they can complete the lesson, but I don’t know if they actually used the support or learned from it.”

— Math Coach, Middle School

Our instructional take

Instructional wins

  • Khanmigo can increase student practice on specific standards by offering support when students get stuck while practicing independently and with immediate feedback on whether the answer is correct or not.
  • For students who may be uncomfortable asking questions out loud of their teacher, Khan allows students a private forum for questions and video answers. The chat also suggests questions that students can click when they do not know what to ask.
  • Khan offers on demand help for students and parents outside of school time, so support isn’t limited to the school day.

Instructional limitations

  • The teacher dashboard requires several clicks to get insights on student work, making it hard for teachers to track student progress at a glance. Khanmigo surfaces suggestions to teachers only when a teacher asks for them, not when a student struggles. 
  • Designed for solo use, Khan does not increase student talk time and does not facilitate students learning from each other. 
  • Students choose whether to interact with Khanmigo, so different students use it in different amounts. 
  • Juggling paper-pencil notes while entering responses into Khanmigo can be clunky. 
  • Khanmigo collects limited information about why students answered questions the way they did, limiting the extent to which it can then help pinpoint misconceptions.

Implementation considerations

  • Khanmigo shares the standard school-based implementation considerations: scheduling (within the class schedule and the scope-and-sequence for instruction), teacher and leader training, tech set up, and expectations for use.
  • Khanmigo is so flexible that leaders need to be clear about where and how it fits into the day and the instructional program and what parts of the curriculum Khan should not replace. 
  • Because Khanmigo does not prompt particular teacher moves, leaders need to define what teachers should do while students use it and make sure all instructional leaders share the same vision. 
  • Leaders should consider how Khan data should be used during PLC and planning time.
Evaluation icon

Evidence of Impact

Available evidence

Published

There is no independent, causal evidence of impact for Khanmigo

.

Khan Academy has independent randomized evidence, concentrated primarily outside US classrooms and testing the platform as a replacement for or supplement to class time rather than as the practice component of a US instructional model.

‍

US studies:

  • RCT in Arlington, Texas: https://www.nber.org/papers/w32388
  • RCT in Hamilton, TN: https://www.nber.org/papers/w35620

‍

A trial in Salvadoran primary schools held added lesson time constant across three arms and found software lessons produced larger math gains than teacher-led lessons. A preregistered trial across 157 Brazilian primary schools, where the platform replaced one weekly math class, found attitudes toward math improved 0.06 standard deviations and math proficiency did not change. 

‍

A randomized trial in India, where every classroom used Khan Academy and the randomized condition was whether a paraprofessional managed use and kept students on task, found substantially larger gains in classrooms with that adult, which isolates the adult rather than the platform as the variable.

‍

‍

 Khan Academy efficacy studies by ESSA tier; Büchel, Jakob, Kühnhanss, Steffen, and Brunetti, Journal of Labor Economics 40(3) (2022); Ferman, Finamor, and Lima (2019), via J-PAL; Oreopoulos, Gibbs, Jensen, & Price (2024); Oreopoulos & Low (2026) AI in Action Evidence Scan (June 2026)

Here is a blog post from Sal about a recent study (RCT) by Phil Oreopoulos and Nina Low on Khan Academy with Khanmigo: https://blog.khanacademy.org/what-i-found-compelling-in-a-new-randomized-trial-of-khan-academy-in-math-intervention/

‍

From the developer icon

From the developer

From

Khanmigo by Khan Academy

The following was written by the team at Khan Academy and has been edited for clarity and tone by Instruction Partners. 

‍

In the first three years of Khanmigo usage in schools, we have learned a lot, as you can read in a blog post from Sal Khan: https://blog.khanacademy.org/khanmigos-first-chapter-changed-how-i-think-about-ai-a-note-from-sal-khan/

‍

This summer, in time for SY 2026–27, we released a redesigned classroom experience that integrates Khanmigo further into the practice experience. We have seen improvements in student performance in answering questions without Khanmigo after interacting with Khanmigo. We write about how we run these experiments in this blog post: https://blog.khanacademy.org/how-khan-academy-is-building-a-better-ai-tutor-our-most-recent-learnings
‍

However, our biggest lesson continues to be that no technology on its own will improve learning outcomes. Technologies’ success only comes with intentional implementation and use, including professional learning for teachers, continued use of data to monitor what is going well and where more attention is needed, and the human high fives that celebrate in ways that prioritize relationships among people.

Learn more about Khan Academy: https://www.khanacademy.org/

Product website icon

Product website: https://www.khanmigo.ai/

Hear from the developer

Instruction Partners' CEO Emily Freitag spoke with Vicki Zubovic and Kristen DiCerbo from Khan Academy to understand what problems they're trying to solve, how the tool works, and what they're still figuring out.

PreviousNext