Psychology | |||||
Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
School/Faculty/Institute | Faculty of Engineering | ||||
Course Code | MATH 321 | ||||
Course Title in English | Automata Theory and Formal Language | ||||
Course Title in Turkish | Biçimsel Diller ve Otomatlar Kuramı | ||||
Language of Instruction | EN | ||||
Type of Course | Flipped Classroom | ||||
Level of Course | Introductory | ||||
Semester | Fall | ||||
Contact Hours per Week |
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Estimated Student Workload | 160 hours per semester | ||||
Number of Credits | 6 ECTS | ||||
Grading Mode | Standard Letter Grade | ||||
Pre-requisites | None | ||||
Expected Prior Knowledge | Basic Discrete Mathematics and Data Structures Knowledge | ||||
Co-requisites | None | ||||
Registration Restrictions | Only Undergraduate Students | ||||
Overall Educational Objective | To learn the fundamentals of theory of computation, basic graph theory and introductory discrete mathematics, learn the classification between classes of languages (regular, context-free, and more) and design grammars and machines that will generate/recognize these languages. | ||||
Course Description | This course covers the fundamentals of theory of computation: basic graph theory, introductory discrete mathematics, regular languages, finite state machines, push-down automata, regular expressions, context-free grammars, Turing machines, decidability, reducibility, time complexity | ||||
Course Description in Turkish | Bu derste, biçimsel diller ve otomatlar kuramının temel kavramları şu başlıklar altında işlenmektedir: temel çizge teorisi, sonlu küme matematiğine giriş, düzenli diller, sonlu durum makineleri, ters otomat, düzenli ifadeler, bağlama duyarsız gramerler, Turing makineleri, karar verilebilirlik, indirgenebilirlik, zaman karmaşıklığı |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) know basic discrete mathematics and graph theory 2) identify finite state machines, regular languages, regular expressions, determinism and nondeterminism and their connection 3) know context-free languages, push-down automata and their connection 4) comprehend Turing machines, decidability and reducibility 5) apply new knowledge as needed, using appropriate learning strategies |
Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | |||||
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | |||||
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | |||||
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | |||||
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | |||||
6) Internalization and dissemination of professional ethical standards. | |||||
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | |||||
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | |||||
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | |||||
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | |||||
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | |||||
12) Ability to acquire knowledge independently, and to plan one’s own learning. | |||||
13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
N None | S Supportive | H Highly Related |
Program Outcomes and Competences | Level | Assessed by | |
1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
6) | Internalization and dissemination of professional ethical standards. | N | |
7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
Prepared by and Date | ŞENİZ DEMİR , November 2023 |
Course Coordinator | ŞENİZ DEMİR |
Semester | Fall |
Name of Instructor | Assoc. Prof. Dr. ŞENİZ DEMİR |
Week | Subject |
1) | Basic Discrete Mathematics and Graph Theory |
2) | Basic Discrete Mathematics and Graph Theory |
3) | Finite State Machines and Regular Languages |
4) | Finite State Machines and Regular Languages |
5) | Nondeterminism and Regular Expressions |
6) | Equivalence of Regular Expressions and Finite State Machines |
7) | Nonregular Languages and Pumping Lemma |
8) | Nonregular Languages and Pumping Lemma |
9) | Context-Free Grammars and Ambiguity |
10) | Push-Down Automata |
11) | Non-Context-Free Languages and Pumping Lemma |
12) | Turing Machines |
13) | Turing Machines |
14) | Advanced Topics (Decidability, reducibility, time complexity) |
15) | Final Exam/Project/Presentation |
16) | Final Exam/Project/Presentation |
Required/Recommended Readings | Introduction To The Theory Of Computation – Michael Sipser 3rd ed. | |||||||||||||||
Teaching Methods | Flipped classroom. In-class flipped practices. | |||||||||||||||
Homework and Projects | In-class flipped practices. No Project. | |||||||||||||||
Laboratory Work | None | |||||||||||||||
Computer Use | For in-class practices | |||||||||||||||
Other Activities | None | |||||||||||||||
Assessment Methods |
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Course Administration |
demirse@mef.edu.tr 536 Instructor’s office: Room 535 (5th floor) Office hours: TBA. E-mail address: demirse@mef.edu.tr Rules for attendance: No attendance required. Missing an in-class practice: Provided that proper documents of excuse are presented, a make-up will be given to each missed practice. Missing a midterm: Provided that proper documents of excuse are presented, make-up for missed midterms will be given. Missing a final: No final exam. A reminder of proper classroom behavior, code |
Activity | No/Weeks | Hours | Calculation | ||||
No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
Course Hours | 14 | 3 | 3 | 84 | |||
Quiz(zes) | 8 | 2 | 1 | 24 | |||
Midterm(s) | 2 | 23 | 3 | 52 | |||
Total Workload | 160 | ||||||
Total Workload/25 | 6.4 | ||||||
ECTS | 6 |