RESEARCH METHODS
- Course
- BASC501 - RESEARCH METHODS
- Department
- Electronics and Communication Engineering - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Prof. Dr. HALUK BALKAN
- Prerequisite
- -
- Keywords
- -
Course Description
This course introduces students to research methods and contemporary issues related to research in a university setting. Students will be introduced to research proposal development, scientific literature reviews, measurement analysis, statistical data analysis, and research planning techniques, good research practice, and oral and written research communication. Ethics and intellectual property topics related to research will also be covered. During this course, students will evaluate the broad impact of their engineering research and relevant constraints and data analysis skills. Also students will research, plan, execute and evaluate a self-defined research project. Research will focus on the Engineering Themes of Energy, Water, Health or Security.
RESEARCH METHODS
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm Paper (Project Proposal) | Assignment | 30 |
| Final Paper (Literature Review paper publisha | Assignment | 50 |
| Powerpoint presentation of the final paper | Presentation | 20 |
| Total | 100 | |
Course outcomes
- 01 Assess suitable types of research
- 02 Plan and write an effective research proposal
- 03 Design and conduct a proper scientific research
- 04 Perform ethical research
- 05 Perform an effective literature survey
- 06 Assess data collection methods
- 07 Perform experiments and evaluate data
- 08 Report and present research results
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction to course, processes |
| Week 2 | Research Methodology andesarch Process |
| Week 3 | Research Problem |
| Week 4 | Model Building & Variables and Their Types- |
| Week 5 | Research Proposal &Formulation of Hypothesis |
| Week 6 | Literature Survey & Plagiarism |
| Week 7 | Data Collection & Sampling |
| Week 8 | MIDTERM EXAMINATION |
| Week 9 | Writing a paper in Scientific Format |
| Week 10 | Presentations of results |
| Week 11 | Effective Technical Writing |
| Week 12 | Ethical issues in research & Collaboration in research |
| Week 13 | Student Presentations |
| Week 14 | Student Presentations |
| Week 15 | Not Scheduled inAcademic calender |
Reference Books & Course Materials
- 01 Dr. Pandey, Prabhat and Dr. Meenu Mishra Pandey, “ RESEARCH METHODOLOGY: TOOLS AND TECHNIQUES”, ISBN 978-606-93502-7-0, © Bridge Center, 2015
- 02 John W. CRESWELL, "Research Design", 4th Ed., Sage Publications Ltd.,2014.
- 03 Patrick DUNLEAVY, "Authoring a PhD:How to Plan, Draft, Write and Finish a Doctoral thesis or Dissertation", Palgrave Study Guides, 2003.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- Demonstrate a thorough understanding of the theories, frameworks, and models in order to assess and comprehend the state of the art in data science.
- Review the literature and apply data science theories and methodology in new research and experiments.
- Analyze datasets using supervised and unsupervised machine learning techniques.
- Design, develop and test statistics and informatics software systems for data management, analysis and problem solving.
- Conceptualize and develop efficient visuals for a range of data types and analytical tasks, and carry out independent research on a range of theoretical and applied subjects in visualization and visual analytics.
- Obtain a high level of proficiency in communication, problem solving, research or project-related activities and function effectively as a team member or a leader to accomplish a common goal in a multidisciplinary team.
- Develop and implement optimal solutions to overcome challenges associated with managing large datasets by utilizing parallel methods, cloud computing, and non-relational data storage and retrieval (NoSQL).
- Demonstrate an understanding of the interdisciplinary of data, information, and communications, as well as the ability to evaluate the leading research methods for data collection and analysis.
- Demonstrate a deep understanding of the ethical issues surrounding the use of data and apply ethical decision making in real-world data-related applications.
- Demonstrate capability of analyzing, synthesizing, and evaluating knowledge from a wide range of fields and be capable of lifelong self-directed learning.
Po-Lo Matrix
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