AI for Education: Korean
Report for Lesson Study 2.0
KKU Workshop of AI & Data Science for Education
2022.10.18
Hee-chan Lew
hclew@knue.ac.kr

AI in Society 4.0
 AI is a cornerstone of our current
society in that it is a basis ofhighly sophisticated technologies
driving the 4IR.

 AI is a machine system to
implement a variety of recognition,
thinking, and learning that havebeen performed by only human
intelligence.
 Autonomous driving car with AI
can recognize and make a decision
for passenger’s safety.

AI in school
 Many people consider that AI is enough for high-level experts
only and worry that AI education might be too much burden forordinary students.
 However, Korean
government decided in2019 that AI should betaught urgently in school
curriculum as early as2022.
 Nobody knows about
success or not!!

 We need Lesson Study!!

Lesson Study for AI• Lesson study is a study toimprove educational
relationship between teachersand students in classrooms.
• However, it is very complex inthat it has many factors likecurriculum, textbook, teacher
training, classroom
environment, student previousexperience, educational
cultureTeacherss

Studentss

Curriculum

AI Basic• “AI Basic (informatics)”

Key concepts

and “AI Mathematics”
were already developed
as the new chapter ofthe current 2015
national high school
curriculum in 2020.

• Additionally, their newcurriculum is being
developed for the next
national curriculum,
which begins in 2025.

AI and Agent

Recognition
Exploring andReasoning
Leaning
Data

Machine Learning
Model
Impact of AI
Ethics of AI

AI Mathematics
Key concepts
Mathematics
related to AI
Representation of
Text Data
Representation ofImage DataClassification ofData
Tendency andExpectation
Optimization andDecision Making

Textbooks for high school mathematics• 6 kinds of high school
textbooks for “AI Basic”
and “AI Mathematics”
were already developed
for public education in2021.
• These have used fromspring semester of thisyear, 2022 in someschools, as a selective
subject for students
who want it.

Example 1:
Visual Image
Recognition• What isdifferent
between thesetwo pictures?
• Machine with AI
can recognize
the difference
easily thanhuman. How?
• Mathematics
can make itpossible!!

Example 2: Pattern & Rule Recognition• AI can effectively find patterns
and rules inherent in data
through machine learning.

• If the basketball score is x andthe soccer score is y, AI can findthe best trend line y=ax thatpredicts the soccer score fromthe basketball score.
• Mathematics can make itpossible through simple
regression analysis and thegradient descent method

Student

BasketballSoccer

A

44B

57

C

810

Example 3. Spam Mail filtering• AI automatically filters spam mails sprayedindiscriminately on the Internet.
• It is Bayesian estimation that supports this. process.

• This process increases probability offiltering spam mails through adding
information.
Prior
probability

정보1정보2Posterior
Probability 1정보
3Posterior
Probability 2

AI in teacher education
 In 2019 South Korean Government
decided to train 5000 AI teachers forleading high school students in thenew era of the fourth industrial
revolution.
 For 5 years, they have taken master
degree course from the second
semester of 2020.
 KNUE also launched the course for
140 teachers each year in 2020
based on its H-I-G-H-E-R vision.

Humanity

Integrated
Intelligence

Globalization

Renovation
MindHarmony

Experience“HIGHER” Vison of KNUE

KNUE AI Teacher Education
 The program was launched with the goal ofconvergence education related to AI which is todevelop a converging eye through viewing theirsubjects from the AI related perspective.
 Compulsory: 18 credits of 6 courses including AI
programming I, II and AI Education I, II, AI andschool and AI Ethics and Education in School.
 Elective: 9 credits of 2 courses and 1
independent study course (for thesis) in eachdepartment of student’s major subject.
 Two elective courses for mathematics education
major are “AI mathematics education” and“Topics in AI mathematics”.

Lecture Note Cover of AI
Programming I for KNUE AI
Teacher Education

Framework of “AI mathematics Education”
 Based on APEC InMside“AI mathematics education”
chose the following three
thinking as teaching goals:
 Computational thinking
 Statistical thinking
 Programming thinking
 The course discusses
teaching exemplar within
K-12 mathematics
education

AI

Programming Thinking
ElementaryJunior High

Senior HighAI related exemplar

Algeomath: mathematical Block
Coding Platform• Algeomathis the newplatformformathematical block
coding.
“When thearea ofrectangle
becomesmaximum incase that its
perimeter isFinal Remark: InternationalLesson Study• AI and Data Science for educationis on totally new teaching situation.
• We have no enough information ineach country.
• That is why we need international
Lesson Study 2.0 for sharingclassroom information on AI andData Science.

See you again in Lesson Study 2.0