What Teachers Should Know About YAML

In recent years, we have seen an increase in opportunities to encounter the term

YAML

in the worlds of generative AI, cloud services, and programming.

Many teachers may have heard of CSV or JSON, but this might be their first time hearing about YAML.

In fact, YAML is a data format widely used in

generative AI, school system configurations, and cloud service operations.

Teachers may not have many opportunities to write YAML on a daily basis.

However, as AI and school digital transformation (DX) progress,

it is well worth understanding

that "this is how these systems work."

What is YAML?

YAML stands for

YAML Ain't Markup Language

.

It is a somewhat unusual name, but

simply put,

it is a configuration file that is easy for humans to read

.

For example,

学校名: 滝中学校
クラス:
  - 1A
  - 1B
  - 1C

it is written like this.

You can tell what is written just by looking at it.

This is the greatest feature of YAML.

Differences from JSON

In JSON, which I introduced previously,

{
  "学校名":"滝中学校",
  "クラス":["1A","1B","1C"]
}

it looks like this.

JSON is designed for computers.

On the other hand, YAML is

designed for humans.

It has fewer brackets and symbols,

and looks clean.

Therefore,

it is very popular as a configuration file format.

Compatibility with Markdown

If Markdown is

a format for structuring text,

then

YAML

can be called

a format for structuring settings.

In fact,

At the beginning of Markdown,

information is sometimes written in YAML format.

For example,

title: 教員が知っておきたいYAML
author: 松末
date: 2026-06-24

it looks like this.

This is called document metadata.

Why YAML now?

In recent years,

with the spread of generative AI and cloud services,

settings have become important.

For example,

• Discord BOTs

• AI agents

• Web servers

• cloud systems

and so on,

are operated by configuration files.

YAML is often used to describe those settings.

Relationship with the school environment

For teachers,

there may be few opportunities to write YAML directly.

However,

for example,

• Moodle

• GitHub

• Docker

• Open WebUI

and others, you will start to encounter YAML frequently.

In recent years,

some schools have begun operating local LLMs on campus,

or setting up generative AI environments.

In such environments,

YAML plays an active role behind the scenes.

Relationship with AI Agents

The AI agents that have been a hot topic recently also,

have excellent compatibility with YAML.

For example,

you can configure it like this.

役割: 学習アドバイザー
対象: 中学生
目的: 学習支援

In other words,

to the AI,

you can provide instructions.

You can describe "what role to assign."

It can describe that.

In the era of generative AI,

YAML also plays a role like an instruction manual for AI.

Difference from CSV

CSV is in a tabular format.

Name, Class, Attendance Number

It is good at managing data like this.

However,

it is not good at complex structures.

For example,

School
↓
Grade
↓
Class
↓
Student

It becomes difficult to handle when it becomes a hierarchical structure like this.

YAML can naturally express such hierarchical structures.

Compatibility with educational data

In the future,

as student dashboards and learning analytics advance,

we will be handling various educational data.

For example,

• Student Information

• Grades

• Attendance

• Activity History

and so on.

While actual data storage is primarily handled by JSON or databases,

YAML plays a key role in the configuration settings.

School Administration Support in the AI Era

In the future,

AI will likely be integrated into school administration support systems as well.

For example,

extracting students with consecutive absences,

analyzing grade fluctuations,

drafting communications to parents,

are examples of such functions.

YAML may also be used to configure the settings for such AI operations.

Not all teachers need to learn it

Of course,

it is not necessary for all teachers to write YAML.

You can handle daily tasks if you can use Excel.

However,

CSV

JSON

Markdown

YAML

knowing the differences between these data formats

makes it easier to understand how school DX and generative AI work.

Data formats also have a division of roles

To summarize the four introduced so far,

CSV -> tabular data

JSON -> data exchange between systems

Markdown -> document creation

YAML -> configuration management

are their respective roles.

To use teachers as an analogy,

CSV is an attendance register,

JSON is a staff room contact network,

Markdown is a class newsletter,

YAML is a school operation manual

and so on.

Conclusion

YAML is not a flashy technology.

However,

Generative AI

Cloud services

AI agents

Local LLMs

and others are widely used behind the scenes.

In this coming era of school digital transformation,

what is required of teachers is not advanced programming skills.

Rather,

it is to understand

"how data is organized and how it flows."

CSV, JSON, Markdown, and YAML.

Knowing these might be called a new form of information literacy for understanding education in the age of generative AI.