NEF700-04 - SPECIAL SUBJECTS

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
SPECIAL SUBJECTS NEF700-04 8th Semester 5 0 0 30
PrequisitesPhD Eligibility Exam
Course languageTurkish
Course typeMust 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesOther: Research-Investigation-Discussion  
Instructor (s)Associates,lecturers and instructors of the department 
Course objectiveConducting a scientific thesis according to universal scientific principles  
Learning outcomes
  1. ? Reviewing the literature related to the thesis subject
  2. ? Organizing the information obtained from the literatüre
  3. ? Obtaining the data from a scientific research
  4. ? Analyzing the research data
  5. ? Interpreting the research results
  6. ? Evaluating the research findings and making new scientific proposals
  7. ? Reporting and defending a scientific research
Course Content1. Selection of the thesis subject
2. Reviewing the literature related to the thesis subject
3. Planning all aspects of the research
4. Developing the data obtaining method
5. Confirming the validity and reliability of the data obtaining method
6. Application of the scientific method and evaluation of the results
7. Reporting and writing the research results
 
ReferencesLiterature relevant to the thesis subject 

Course outline weekly

WeeksTopics
Week 1Confirming the validity and reliability of the data obtaining method
Week 2Confirming the validity and reliability of the data obtaining method
Week 3Application of the scientific method
Week 4Application of the scientific method
Week 5Application of the scientific method
Week 6Application of the scientific method
Week 7Evaluation of the research results
Week 8Evaluation of the research results
Week 9Evaluation of the research results
Week 10Evaluation of the research results
Week 11Evaluation of the research results
Week 12Evaluation of the research results
Week 13Evaluation of the research results
Week 14Defending the Thesis

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities1450
Specific practical training00
Assignments1450
Presentation00
Project00
Seminar00
Midterms00
Final exam00
Total100
Percentage of semester activities contributing grade succes0100
Percentage of final exam contributing grade succes00
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 5 70
Laboratory 0 0 0
Application000
Specific practical training000
Field activities1020200
Study Hours Out of Class (Preliminary work, reinforcement, ect)1435490
Presentation / Seminar Preparation1410140
Project000
Homework assignment000
Midterms (Study duration)000
Final Exam (Study duration) 000
Total Workload5270900

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Graduates of this program will have knowledge about the clinical neuro-electrophysiology. They will be able to make applications, seminars and courses, follow research and innovations at this scientific field.    X
2. Graduates of this program are capable of developing new projects and they will have theoretical knowledge and skills to evaluate the new projects in the field of neuro-electrophysiology.    X
3. Graduates of this program will learn interpretation of the EEG both at children and adults. They will have theoretical and practical knowledge about the he basic applications of EEG and activation methods and EEG monitoring    X
4. Graduates of this program will have theoretical and practical knowledge about nerve conduction techniques, needle electromyography, single fiber EMG, repetitive nerve stimulation, evoked potentials and autonomic tests. They are capable of performing this techniques and evaluating the results, and take on the responsibility of these applications in a stand-alone laboratory studies     X
5. Graduates of this program will have knowledge about device used in neuro-electrophysiology and indications for the use and can use them.    X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest