Is Goblins free for teachers?

Yes. Goblins offers a generous free tier that includes 1 live feedback assignment per week, insights on student mastery and replays, and the ability to upload your own content. The Max plan adds unlimited assignments, superadaptive mode, grade exports, standards growth reports, and SSO/LMS integration, with per-student pricing for schools and districts.

How does Goblins work?

Three simple steps: (1) Share an assignment from thousands of standards-aligned topics using a share code. (2) Students speak and draw their thinking naturally, and Goblins responds with Socratic questioning that sounds just like their teacher. (3) Teachers get real-time formative insights showing what students struggle with and suggestions to inform instruction.

Does Goblins prevent cheating?

Yes. Goblins uses a purpose-trained AI model that evaluates cheating signals in real time. It can detect when students are copying answers, using external tools inappropriately, or not genuinely working through problems. Copy-pasting answers is also blocked.

Can I use my own voice with Goblins?

Yes. Teachers can record their voice and take a selfie to create a custom 3D avatar in about 30 seconds. Students then hear help in their own teacher's voice and see a familiar face, making the experience more personal and effective.

What math levels does Goblins cover?

Goblins covers math from Grade 5 through AP Calculus, including thousands of standards-aligned topics. Teachers can also upload their own content for custom assignments at any level.

Is Goblins FERPA compliant?

Yes. Goblins is FERPA and state compliant. Student data privacy and security are a top priority.

Does Goblins support English Language Learners?

Yes. Goblins supports 30+ languages so teachers don't have to translate every worksheet. It is especially helpful for ELL students who need accessible math instruction in their native language.

What grade level is AI.S-ID.A.3 taught?

This standard is part of the AI curriculum in Massachusetts Curriculum Framework for Mathematics.

Are there practice problems for AI.S-ID.A.3?

Yes, there are 3 practice problems available for AI.S-ID.A.3 with worked examples.

What learning resources are available for AI.S-ID.A.3?

There are 2 Khan Academy resources available for AI.S-ID.A.3, including 1 videos, 1 exercises.

AI.S-ID.A.3: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (... | Massachusetts Curriculum Framework for Mathematics

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

Example Problems

A cat gave birth to 3 kittens who each had a different weight between

147

and

159 \text{ g}

147, 153, 159

Then, the cat gave birth to a 4th kitten that weighed

57 \text{ g}

.

How will adding this kitten's weight affect the median; will it increase, decrease, or stay the same?

Nia tracked her step counts for 8 days. The mean step count was exactly 10,000 steps. On the 9th day, she logged 10,000 steps.

How will adding this day's count affect the mean; will it increase, decrease, or stay the same?

Lara is a wildlife researcher.
They were analyzing the mean lengths of 7 fish their team had observed. The fish all had different lengths between

15 \text{ cm}

and

33 \text{ cm}

.
Lara found out that they were misreading the longest length. It was actually

88 \text{ cm}

, not

33 \text{ cm}

.

How will this length increasing affect the mean; will it increase, decrease, or stay the same?

Khan Academy Resources

Use probabilities to make fair decisions Using probabilities to make fair decisions example

1-on-1 AI tutoring aligned to AI.S-ID.A.3. Instant help for students, real-time insights for teachers.

Used in classrooms by 100,000+ students at Baltimore County, Plano ISD, Deer Valley USD, KIPP, and districts nationwide.

Free for teachers, forever →

AI.S-ID.A.3: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).