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Subject

Computational Thinking in Education

1. Course Title Computational Thinking in Education
Computational thinking in education
2. Code F23L2S051
3. Study Programme Computer education
4. Organizer of the study programme (unit, institute, department or division) Faculty of Computer Science and Engineering
5. Degree level (first, second, third cycle) First Cycle
6. Academic year / semester 4 / Summer
7. Number of ECTS credits 6
8. Teacher Emil Stankov, Mile Jovanov
9. Prerequisites for enrolling in the course Introduction to Computer Science
10. Objectives of the course programme (competences) In the 21st century, computational thinking is a skill of crucial importance for all citizens of the world. Computing and technology affect our entire lives, and everyone should know how to formulate problems and express solutions for them in a way that a computer can execute. In this course, students will learn various aspects of computational thinking and approaches for teaching them in elementary and secondary education. They will learn a block-based language and modern approaches designed to facilitate learning programming.
11. Course content Lectures:
1. Introduction to Computational Thinking
2. Using abstractions and pattern recognition to present problems in new and different ways
3. Logical organization and analysis of data
4. Decomposition of problems into smaller parts
5. Online and offline tools for developing computational thinking
6. Tackling the problem using algorithmic thinking techniques
7. Informatics Thinking in Software Development
8. Elements of a Block-based (Visual) Programming Language
9. Elements of a Block-based (Visual) Programming Language 2
10. Implementation of solutions in a block-based (visual) programming language
11. Computational Thinking in Educational Digital Games

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12. Learning methods Lectures using presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lectures, independent preparation and defense of a project assignment and a seminar paper.
13. Total available time 6 ECTS x 30 hours = 180 hours
14. Distribution of available time 30 + 45 + 15 + 15 + 75 = 180 hours
15. Forms of teaching activities
15.1. Lectures - theoretical instruction 30 hours
15.2. Exercises (laboratory, auditory), seminars, teamwork 45 hours
16. Other forms of activities
16.1. Project assignments 15 hours
16.2. Independent assignments 15 hours
16.3. Home study 75 hours
17. Assessment method
17.1. Tests 0 points
17.2. Seminar paper / project (presentation: written and oral) 15 points
17.3. Activities and learning 30 points
17.4. Final exam 30 points
18. Grading criteria (points / grade)
up to 50 points5 (five) (F)
from 51 to 60 points6 (six) (E)
from 61 to 70 points7 (seven) (D)
from 71 to 80 points8 (eight) (C)
from 81 to 90 points9 (nine) (B)
from 91 to 100 points10 (ten) (A)
19. Requirement for obtaining a signature and taking the final exam Activities 15.2 and 16.1 have been completed.
20. Language of instruction Macedonian and English
21. Method for monitoring the quality of teaching internal evaluation and survey mechanism
22. Literature
22.1. Required literature
1. Karl Beecher | Computational Thinking: A Beginner's Guide to Problem Solving and Programming | BCS Learning & Development Ltd | 2017
2. Jane Krauss, Kiki Prottsman | Computational Thinking and Coding for Every Student: The Teacher's Getting-Started Guide | Corwin Press | 2016
3. Peter J. Rich, Charles B. Hodges | Emerging Research, Practice, and Policy on Computational Thinking | Springer | 2017
4. Paolo Ferragina, Fabrizio Luccio | Computational Thinking: First Algorithms, Then Code | Springer Nature Switzerland AG | 2018
22.2. Additional literature
No. Author Title Publisher Year
Деканат Dean’s Office Студии Studies Акти Acts Проекти Projects