2017 Workshop on Group Problem-Solving (ACLS)

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Academic unit or major
Graduate major in Artificial Intelligence
Yamamura Masayuki  Takinoue Masahiro 
Class Format
Lecture / Exercise     
Media-enhanced courses
Day/Period(Room No.)
Intensive ()  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

Life science and computer science students will form small groups that solve practical problems in the field of computational life science.

Student learning outcomes

Biology students learn computer literacy for group works with computer science students. Computer science students learn basic mathematics for modeling and simulation in Computational life science field.


Computational Life Science, Creative Collaborative Works

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

In the first 8 classes, students are separated into biology students and computer science students, receiving instruction in separate classrooms. In each class the instructor lectures using original materials. In each class, through simple individual and group exercises, students' achievements are evaluated while also aiding their acquisition of knowledge. In the final 7 classes, students solve group problems in contest format in small groups of students with different majors.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction: Students will have their knowledge checked with questionnaires, which will determine group organization. mathematical basics, computer literacy, biological basics
Class 2 Bio-1 : networking and security CS-1 : systems modeling with linear differential equations network security, linear differential equations
Class 3 Bio-2 : Programming in Ruby 1 CS-2 : Feedback control 1 data types and operators, Laplace transfer, stability
Class 4 Bio-3 : Programming in Ruby 2 CS-3 : Feedback Control 2 control flow, state representation
Class 5 Bio-4 : Programming in Ruby 3 CS-4 : Non-linear systems 1 commandline arguments, non-linear differential equations
Class 6 Bio-5 : Programming in Ruby 4 CS-4 : Non-linear systems 2 class and objects, phase diagram
Class 7 Bio-6 : Programming in Ruby 5 CS-6 : Non-linear systems 3 class definition, bifurcation
Class 8 Bio-7 : Presentation CS-7 : Topics Ruby program, systems modeling
Class 9 Introduction for creative collaborative works brain storming, KJ method
Class 10 group work 1 group work
Class 11 group work 2 group work
Class 12 group work 3 group work
Class 13 group work 4 group work
Class 14 group work 5 group work
Class 15 competition competition



Reference books, course materials, etc.

For every class, instructors lecture independent topics with original handouts.

Assessment criteria and methods

Every class also includes simple exercises by individual students or by groups. These exercises help understanding the principle and also become materials for final evaluation. Ranking in the final competition will be added.

Related courses

  • none

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Students must belong to the Education Academy of Computational Life Sciences Doctors Education Program (ACLS)



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