MSc:ResearchMethods

From IU
Jump to navigation Jump to search

Research Methods

  • Course name: Research Methods
  • Course number: XYZ

Course Characteristics

Key concepts of the class

  • Definition and types of research
  • Review process
  • Scientific fraud
  • Experimental design


What is the purpose of this course?

The main purpose of this course is to present the research methods and concepts to the master students of Innopolis University of Data Science and Robotics programs. On one side the course provides the scientific fundamentals of the research activity and on the other anchors the theoretical concepts on practices coming from the world of software development and engineering. As a result of the course, students demonstrate on practice the acquired skills of formulating the research problem, collecting, analyzing data and presenting results of research.

Course objectives based on Bloom’s taxonomy

- What should a student remember at the end of the course?

By the end of the course, the students should be able to:

  • Remember the steps of research design
  • Remember the sources of information in Software Engineering
  • Remember the concept of measurement
  • Remember the notion of Scientific fraud
  • Explain the difference between 4different experimentation designs

- What should a student be able to understand at the end of the course?

By the end of the course, the students should be able to understand:

  • The difference between Science and Engineering
  • The nature of errors
  • The ethics in research
  • How to choose the papers
  • How to summarize the research paper
  • How to evaluate the research paper


- What should a student be able to apply at the end of the course?

By the end of the course, the students should be able to ...

  • Summarize a research paper
  • Evaluate a research paper
  • Write good papers
  • Present results of the research


Course evaluation

Course grade breakdown
Points
Paper review1 10
Project proposal2 40
Interim performance assessment (class participation) 10
Final presentation3 40

1Students have to perform the review of the selected paper. Use the table to submit your selection and get approval for it.

2Students have to make a half-page proposal on the project in their research domain.

3At the end of the course, students make a 15-min video presentation of their research.

Each component will be assessed on a scale 0-10, where 6 is the minimum passing grade. In case of exceptional work a 10 cum laude will be assigned, with a numeric value from 10 to 13 at the discretion of the instructor.

The grading, though, is not a simple linear combination of the components above. In particular:

  • failing any part of the evaluation will trigger a failure in the entire course,
  • if there are not failing components, the final grade will be computed as a weighted average of the components above approximated at the highest second digit and then rounded to the closest integer.

Retakes

Retakes will be run as comprehensive oral exam, where the student will be assessed the acquired knowledge coming from the textbooks, the lectures, the labs, and the additional required reading material, as supplied by the instructor. During such comprehensive oral the student could be asked to solve exercises and to explain theoretical and practical aspects of the course.

Grades range

Course grading range
Range
A. Excellent 95-100
B. Good 75-94
C. Satisfactory 55-74
D. Poor 0-54

Resources and reference material

  • Donald T. Campbell and Julian C. Stanley. Experimental and Quasi-Experimental Designs for Research. Rand McNally College Publishing, 1963
  • Creswell, John W. Educational research: planning, conducting, and evaluating quantitative and qualitative research / John W. Creswell. — 4th ed.

Course Sections

The main sections of the course and approximate hour distribution between them is as follows:

Course Sections
Section Section Title Teaching Hours
1 Theory of research 16
2 Research domains 12
3 Students' presentations 6

Section 1

Section title

Theory of research

Topics covered in this section:

  • Introduction to the course
  • Scientific and engineering research
  • Experimentation
  • Scientific “productivity”
  • Ethics in Research
  • Writing good papers
  • Being a reviewer
  • Influence and presentations

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Homework and group projects 0
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 1
Oral polls 0
Discussions 1

Typical questions for ongoing performance evaluation within this section

  1. What is research?
  2. What types of computing research do you know?
  3. What are the steps of paper evaluation?
  4. What is the common structure of a research paper?
  5. What discover methods do you know?
  6. What is the internal and external validity?
  7. What is the difference between true experiental and quasi-experimental design?


Typical questions for seminar classes (labs) within this section

  1. List the criteria for the evaluation of the research
  2. Based on the given criteria find the relevant papers in ACM DL, Scopus and IEEE Explore
  3. Give an example of the rule of three
  4. Name a few of the aspects of bad writing. Explain them.
  5. Give examples of scientific fraud.
  6. List 4 types of experimental design
  7. List threats to internal validity

Section 2

Section title

Research domains

Topics covered in this section:

  • SSE research
  • Robotics research

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Homework and group projects 0
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 1
Oral polls 0
Discussions 1

Typical questions for ongoing performance evaluation within this section

  1. What are the key research problems in Data Science?
  2. What are the key research problems in Robotics?

Typical questions for seminar classes (labs) within this section

  1. Present the key challenges in solving an identified research problem in data science.
  2. Outline your possible approach to solve a research problem in data science.
  3. Present the key challenges in solving an identified research problem in robotics.
  4. Outline your possible approach to solve a research problem in robotics.

Test questions for final assessment in the course

  1. Identify a key research problem in data science.
  2. Identify a key research problem in robotics.

Section 3

Section title: Students' presentations

Topics covered in this section:

  • Final project presentations

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 1
Oral polls 0
Discussions 1

Typical questions for ongoing performance evaluation within this section

  1. How is your topic related to data science/robotics research domain?
  2. What is the common structure of research presentation?
  3. What are the main outcomes of your research?

Typical questions for seminar classes (labs) within this section

  1. What methods have you applied in your research?
  2. What issues have you face with during your research?
  3. Which sources have you used in the research?

Test questions for final assessment in the course

  1. How your research can be evaluated?
  2. What are the steps of your research process?
  3. What is the novelty of your research?
  4. What research questions have you identified?
  5. What research design have you followed?
Retrieved from "https://eduwiki.innopolis.university/index.php?title=MSc:ResearchMethods&oldid=7690"