PSY416 Neuropsychological Tesis IIIstanbul Okan UniversityDegree Programs Automotive Engineering (English)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Automotive Engineering (English)
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

General course introduction information

Course Code: PSY416
Course Name: Neuropsychological Tesis II
Course Semester: Spring
Course Credits:
Theoretical Practical Credit ECTS
2 2 3 7
Language of instruction: TR-EN
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: University Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Dr.Öğr.Üyesi ZEYNEP HALE AKSUNA
Course Lecturer(s):
Course Assistants:

Course Objective and Content

Course Objectives: The aim of this course; The aim is to introduce neuropsychological tests that reveal the relationship between cognitive/psychological processes and brain structures, to transfer them with materials, instructions, application and scoring forms, and to teach students to apply and score the relevant test.
Course Content: This course includes neuropsychological tests, materials, instructions, forms of administration and scoring, and applying and scoring the relevant test to students.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) To know the general aspects of neuropsychology.
2) To know the basic techniques and approaches of neuropsychology
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
1) To apply and score some neuropsychological tests.
Field Specific Competence
1) To know the neuropsychological profiles in various neuropsychiatric diseases.
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) Beginning of Courses/ Introduction Lecturer's notes and related articles
2) Psychometrics in Neuropsychological Assessment Lecturer's notes and related articles
3) Norms Selection in Neuropsychological Assessment Lecturer's notes and related articles
4) Story Retrieval Lecturer's notes and related articles
5) Story Retrieval Lecturer's notes and related articles
6) To introduce and explain the theoretical framework and application of the Stroop Test Lecturer's notes and related articles
7) Introducing and explaining the Stroop Test's administration and scoring system Lecturer's notes and related articles
8) Midterm NONE
9) To introduce and explain the theoretical framework and application of the Marking Test Lecturer's notes and related articles
10) Introduce and explain the application form and scoring system of the Marking Test Lecturer's notes and related articles
11) Introducing and explaining the theoretical framework and application of the Raven Test Lecturer's notes and related articles
12) Introducing and explaining the Raven Test's administration and scoring system Lecturer's notes and related articles
13) To introduce and explain the theoretical framework and application of the Wisconsin Card Matching Test. Lecturer's notes and related articles
14) Introduce and explain the administration and scoring system of the Wisconsin Card Sorting Test Lecturer's notes and related articles
15) Review Lecturer's notes and related articles

Sources

Course Notes / Textbooks: Kolb, B. & Whishaw, I.Q. (2015). Fundamentals of Human Neuropsychology, sixth Edition. Worth Publishers
References: Kolb, B. & Whishaw, I.Q. (2015). Fundamentals of Human Neuropsychology, sixth Edition. Worth Publishers

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

3

4

Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10) Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11) Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences of engineering solutions.
12) Knowledge on advanced calculus, including differential equations applicable to automotive engineering; familiarity with statistics and linear algebra; knowledge on chemistry, calculus-based physics, dynamics, structural mechanics, structure and properties of materials, fluid dynamics, heat transfer, manufacturing processes, electronics and control, design of vehicle elements, vehicle dynamics, vehicle power train systems, automotive related regulations and vehicle validation/verification tests; ability to integrate and apply this knowledge to solve multidisciplinary automotive problems; ability to apply theoretical, experimental and simulation methods and, computer aided design techniques in the field of automotive engineering; ability to work in the field of vehicle design and manufacturing.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10) Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11) Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences of engineering solutions.
12) Knowledge on advanced calculus, including differential equations applicable to automotive engineering; familiarity with statistics and linear algebra; knowledge on chemistry, calculus-based physics, dynamics, structural mechanics, structure and properties of materials, fluid dynamics, heat transfer, manufacturing processes, electronics and control, design of vehicle elements, vehicle dynamics, vehicle power train systems, automotive related regulations and vehicle validation/verification tests; ability to integrate and apply this knowledge to solve multidisciplinary automotive problems; ability to apply theoretical, experimental and simulation methods and, computer aided design techniques in the field of automotive engineering; ability to work in the field of vehicle design and manufacturing.

Learning Activity and Teaching Methods

Expression
Lesson

Assessment & Grading Methods and Criteria

Homework
Presentation

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Attendance 12 % 10
Midterms 1 % 40
Final 1 % 50
total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 4 56
Study Hours Out of Class 14 3 42
Homework Assignments 4 16 64
Quizzes 3 9 27
Midterms 1 3 3
Final 1 3 3
Total Workload 195